2025-09-07T07:44:40.1467014Z Current runner version: '2.328.0' 2025-09-07T07:44:40.1473060Z Runner name: 'i-03028b1668c838483-1006' 2025-09-07T07:44:40.1473953Z Runner group name: 'default' 2025-09-07T07:44:40.1474862Z Machine name: '4325a60d1947' 2025-09-07T07:44:40.1477559Z ##[group]GITHUB_TOKEN Permissions 2025-09-07T07:44:40.1479723Z Contents: read 2025-09-07T07:44:40.1480440Z Metadata: read 2025-09-07T07:44:40.1480995Z ##[endgroup] 2025-09-07T07:44:40.1483833Z Secret source: Actions 2025-09-07T07:44:40.1484662Z Prepare workflow directory 2025-09-07T07:44:40.1988344Z Prepare all required actions 2025-09-07T07:44:40.2028394Z Getting action download info 2025-09-07T07:44:40.5636755Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd) 2025-09-07T07:44:43.4926177Z Download action repository 'pytorch/pytorch@main' (SHA:ada43ed39c80b746b4822c92640a1882619e2795) 2025-09-07T07:45:12.1502702Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-09-07T07:45:12.3310220Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-09-07T07:45:12.4963830Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-09-07T07:45:12.6313424Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T07:45:12.9095632Z Getting action download info 2025-09-07T07:45:12.9979494Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-09-07T07:45:13.1881610Z Getting action download info 2025-09-07T07:45:13.2842482Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-09-07T07:45:13.4502972Z Getting action download info 2025-09-07T07:45:13.5570899Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-09-07T07:45:13.7264223Z Getting action download info 2025-09-07T07:45:13.8451909Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634) 2025-09-07T07:45:13.8456242Z ##[group] Inputs 2025-09-07T07:45:13.8456662Z build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T07:45:13.8463017Z test-matrix: {"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]} 2025-09-07T07:45:13.8469875Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:45:13.8470890Z sync-tag: 2025-09-07T07:45:13.8471688Z timeout-minutes: 1440 2025-09-07T07:45:13.8471960Z use-gha: 2025-09-07T07:45:13.8473212Z 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 2025-09-07T07:45:13.8474541Z s3-bucket: gha-artifacts 2025-09-07T07:45:13.8474830Z aws-role-to-assume: 2025-09-07T07:45:13.8475432Z disable-monitor: false 2025-09-07T07:45:13.8475755Z monitor-log-interval: 15 2025-09-07T07:45:13.8476057Z monitor-data-collect-interval: 4 2025-09-07T07:45:13.8476425Z ##[endgroup] 2025-09-07T07:45:13.8476882Z Complete job name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T07:45:13.8983039Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-09-07T07:45:13.8983813Z with: 2025-09-07T07:45:13.8984365Z github-secret: *** 2025-09-07T07:45:13.8985087Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-09-07T07:45:13.8985876Z activate-with-label: false 2025-09-07T07:45:13.8986151Z label: with-ssh 2025-09-07T07:45:13.8986391Z remove-existing-keys: true 2025-09-07T07:45:13.8986654Z fail-silently: true 2025-09-07T07:45:13.8987103Z env: 2025-09-07T07:45:13.8987318Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:13.8987579Z ##[endgroup] 2025-09-07T07:45:14.0130965Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-09-07T07:45:14.0132002Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-09-07T07:45:14.0340357Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-09-07T07:45:14.0340807Z with: 2025-09-07T07:45:14.0341032Z no-sudo: true 2025-09-07T07:45:14.0341271Z submodules: recursive 2025-09-07T07:45:14.0341533Z fetch-depth: 0 2025-09-07T07:45:14.0341753Z env: 2025-09-07T07:45:14.0341968Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:14.0342238Z ##[endgroup] 2025-09-07T07:45:14.0425746Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:14.0426787Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:14.0444364Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:45:14.0444775Z env: 2025-09-07T07:45:14.0444999Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:14.0445259Z ##[endgroup] 2025-09-07T07:45:14.0610360Z ##[group]Run actions/checkout@v4 2025-09-07T07:45:14.0610660Z with: 2025-09-07T07:45:14.0610909Z ref: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:45:14.0611246Z fetch-depth: 0 2025-09-07T07:45:14.0611488Z submodules: recursive 2025-09-07T07:45:14.0611740Z show-progress: false 2025-09-07T07:45:14.0612076Z repository: pytorch/pytorch 2025-09-07T07:45:14.0612511Z token: *** 2025-09-07T07:45:14.0612743Z ssh-strict: true 2025-09-07T07:45:14.0612981Z ssh-user: git 2025-09-07T07:45:14.0613217Z persist-credentials: true 2025-09-07T07:45:14.0613495Z clean: true 2025-09-07T07:45:14.0613741Z sparse-checkout-cone-mode: true 2025-09-07T07:45:14.0614045Z fetch-tags: false 2025-09-07T07:45:14.0614266Z lfs: false 2025-09-07T07:45:14.0614502Z set-safe-directory: true 2025-09-07T07:45:14.0614984Z env: 2025-09-07T07:45:14.0615204Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:14.0615449Z ##[endgroup] 2025-09-07T07:45:14.1640162Z Syncing repository: pytorch/pytorch 2025-09-07T07:45:14.1641534Z ##[group]Getting Git version info 2025-09-07T07:45:14.1641990Z Working directory is '/home/frank/_work/pytorch/pytorch' 2025-09-07T07:45:14.1642634Z [command]/usr/bin/git version 2025-09-07T07:45:14.1643165Z git version 2.51.0 2025-09-07T07:45:14.1661432Z ##[endgroup] 2025-09-07T07:45:14.1672366Z Temporarily overriding HOME='/home/frank/_work/_temp/d6dbbedc-76b5-4755-a2b1-3fcae7c8c910' before making global git config changes 2025-09-07T07:45:14.1673319Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T07:45:14.1677336Z [command]/usr/bin/git config --global --add safe.directory /home/frank/_work/pytorch/pytorch 2025-09-07T07:45:14.1710243Z Deleting the contents of '/home/frank/_work/pytorch/pytorch' 2025-09-07T07:45:14.1712968Z ##[group]Initializing the repository 2025-09-07T07:45:14.1716030Z [command]/usr/bin/git init /home/frank/_work/pytorch/pytorch 2025-09-07T07:45:14.1755645Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-09-07T07:45:14.1756333Z hint: is subject to change. To configure the initial branch name to use in all 2025-09-07T07:45:14.1756945Z hint: of your new repositories, which will suppress this warning, call: 2025-09-07T07:45:14.1757381Z hint: 2025-09-07T07:45:14.1757708Z hint: git config --global init.defaultBranch 2025-09-07T07:45:14.1758072Z hint: 2025-09-07T07:45:14.1758439Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-09-07T07:45:14.1759038Z hint: 'development'. The just-created branch can be renamed via this command: 2025-09-07T07:45:14.1759515Z hint: 2025-09-07T07:45:14.1759754Z hint: git branch -m 2025-09-07T07:45:14.1760023Z hint: 2025-09-07T07:45:14.1760413Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-09-07T07:45:14.1761084Z Initialized empty Git repository in /home/frank/_work/pytorch/pytorch/.git/ 2025-09-07T07:45:14.1765338Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-09-07T07:45:14.1798817Z ##[endgroup] 2025-09-07T07:45:14.1799280Z ##[group]Disabling automatic garbage collection 2025-09-07T07:45:14.1802002Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:45:14.1827247Z ##[endgroup] 2025-09-07T07:45:14.1827681Z ##[group]Setting up auth 2025-09-07T07:45:14.1833021Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:45:14.1859335Z [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' || :" 2025-09-07T07:45:14.2063497Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T07:45:14.2088293Z [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' || :" 2025-09-07T07:45:14.2284384Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:45:14.2314418Z ##[endgroup] 2025-09-07T07:45:14.2314850Z ##[group]Fetching the repository 2025-09-07T07:45:14.2321800Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:46:33.6669377Z From https://github.com/pytorch/pytorch 2025-09-07T07:46:33.6669925Z * [new branch] 160583 -> origin/160583 2025-09-07T07:46:33.6670425Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-09-07T07:46:33.6671132Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-09-07T07:46:33.6671775Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-09-07T07:46:33.7942344Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-09-07T07:46:33.7942967Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-09-07T07:46:33.7943637Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-09-07T07:46:33.7944333Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-09-07T07:46:33.7944913Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-09-07T07:46:33.7945554Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-09-07T07:46:33.7946173Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-09-07T07:46:33.7946743Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-09-07T07:46:33.7947321Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-09-07T07:46:33.7947930Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-09-07T07:46:33.7948514Z * [new branch] VLA_exp -> origin/VLA_exp 2025-09-07T07:46:33.7949111Z * [new branch] actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor 2025-09-07T07:46:33.7949829Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-09-07T07:46:33.7950521Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-09-07T07:46:33.7951143Z * [new branch] add-vllm-nightly-build -> origin/add-vllm-nightly-build 2025-09-07T07:46:33.7951756Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-09-07T07:46:33.7952421Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-09-07T07:46:33.7952933Z * [new branch] addsimde -> origin/addsimde 2025-09-07T07:46:33.7953647Z * [new branch] addvllmtest -> origin/addvllmtest 2025-09-07T07:46:33.7954162Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-09-07T07:46:33.7954665Z * [new branch] adi/test -> origin/adi/test 2025-09-07T07:46:33.7955157Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-09-07T07:46:33.7955680Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-09-07T07:46:33.7956218Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-09-07T07:46:33.7956909Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-09-07T07:46:33.7957514Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-09-07T07:46:33.7958069Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-09-07T07:46:33.7958652Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-09-07T07:46:33.7959259Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-09-07T07:46:33.7959820Z * [new branch] alt-disable -> origin/alt-disable 2025-09-07T07:46:33.7960423Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-09-07T07:46:33.7961090Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-09-07T07:46:33.7961677Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-09-07T07:46:33.7962247Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-09-07T07:46:33.7963259Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-09-07T07:46:33.7963963Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-09-07T07:46:33.7964581Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-09-07T07:46:33.7965203Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-09-07T07:46:33.7965827Z * [new branch] angelayi/fake_cache_empty -> origin/angelayi/fake_cache_empty 2025-09-07T07:46:33.7966463Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-09-07T07:46:33.7967228Z * [new branch] angelayi/item -> origin/angelayi/item 2025-09-07T07:46:33.7967776Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-09-07T07:46:33.7968346Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-09-07T07:46:33.7968918Z * [new branch] angelayi/pattern -> origin/angelayi/pattern 2025-09-07T07:46:33.7969471Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-09-07T07:46:33.7970027Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-09-07T07:46:33.7970606Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-09-07T07:46:33.7971163Z * [new branch] 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2025-09-07T07:46:33.9768045Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-09-07T07:46:33.9768540Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-09-07T07:46:33.9768716Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-09-07T07:46:33.9769024Z * [new tag] ciflow/binaries/156049 -> ciflow/binaries/156049 2025-09-07T07:46:33.9769219Z * [new tag] ciflow/binaries/156712 -> ciflow/binaries/156712 2025-09-07T07:46:33.9769409Z * [new tag] ciflow/binaries/157432 -> ciflow/binaries/157432 2025-09-07T07:46:33.9769607Z * [new tag] ciflow/binaries/157685 -> ciflow/binaries/157685 2025-09-07T07:46:33.9769795Z * [new tag] ciflow/binaries/157689 -> ciflow/binaries/157689 2025-09-07T07:46:33.9769996Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-09-07T07:46:33.9770181Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-09-07T07:46:33.9770371Z * [new tag] 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tag] ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252 2025-09-07T07:46:33.9772930Z * [new tag] ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325 2025-09-07T07:46:33.9773171Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-09-07T07:46:33.9773390Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-09-07T07:46:33.9773596Z * [new tag] ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984 2025-09-07T07:46:33.9773811Z * [new tag] ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003 2025-09-07T07:46:33.9774013Z * [new tag] ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011 2025-09-07T07:46:33.9774230Z * [new tag] ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026 2025-09-07T07:46:33.9774438Z * [new tag] ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033 2025-09-07T07:46:33.9774643Z * [new tag] ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040 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2025-09-07T07:46:33.9779605Z * [new tag] ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056 2025-09-07T07:46:33.9779807Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-09-07T07:46:33.9779999Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-09-07T07:46:33.9780199Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-09-07T07:46:33.9780499Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-09-07T07:46:33.9780688Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-09-07T07:46:33.9780881Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-09-07T07:46:33.9781072Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-09-07T07:46:33.9781267Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-09-07T07:46:33.9781449Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-09-07T07:46:33.9781633Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-09-07T07:46:33.9781825Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-09-07T07:46:33.9782011Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-09-07T07:46:33.9782210Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-09-07T07:46:33.9782397Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-09-07T07:46:33.9782593Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-09-07T07:46:33.9782776Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-09-07T07:46:33.9782964Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-09-07T07:46:33.9783163Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-09-07T07:46:33.9783348Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-09-07T07:46:33.9783541Z * [new tag] ciflow/inductor/158647 -> ciflow/inductor/158647 2025-09-07T07:46:33.9783723Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-09-07T07:46:33.9783912Z * [new tag] ciflow/inductor/159146 -> ciflow/inductor/159146 2025-09-07T07:46:33.9784207Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-09-07T07:46:33.9784395Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-09-07T07:46:33.9784590Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-09-07T07:46:33.9784774Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-09-07T07:46:33.9784968Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-09-07T07:46:33.9785152Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-09-07T07:46:33.9785337Z * [new tag] ciflow/inductor/160161 -> ciflow/inductor/160161 2025-09-07T07:46:33.9785535Z * [new tag] ciflow/inductor/160174 -> ciflow/inductor/160174 2025-09-07T07:46:33.9785723Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-09-07T07:46:33.9785919Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-09-07T07:46:33.9786109Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-09-07T07:46:33.9786296Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-09-07T07:46:33.9786490Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-09-07T07:46:33.9786675Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-09-07T07:46:33.9786873Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-09-07T07:46:33.9787058Z * [new tag] ciflow/inductor/160480 -> ciflow/inductor/160480 2025-09-07T07:46:33.9787254Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-09-07T07:46:33.9787537Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-09-07T07:46:33.9787721Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-09-07T07:46:33.9787919Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-09-07T07:46:33.9788102Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-09-07T07:46:33.9788290Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-09-07T07:46:33.9788477Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-09-07T07:46:33.9788662Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-09-07T07:46:33.9788851Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-09-07T07:46:33.9789036Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-09-07T07:46:33.9789232Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-09-07T07:46:33.9789413Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-09-07T07:46:33.9789606Z * [new tag] ciflow/inductor/160843 -> ciflow/inductor/160843 2025-09-07T07:46:33.9789788Z * [new tag] ciflow/inductor/160869 -> ciflow/inductor/160869 2025-09-07T07:46:33.9789970Z * [new tag] ciflow/inductor/160920 -> ciflow/inductor/160920 2025-09-07T07:46:33.9790164Z * [new tag] ciflow/inductor/160928 -> ciflow/inductor/160928 2025-09-07T07:46:33.9790348Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-09-07T07:46:33.9790543Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-09-07T07:46:33.9790726Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-09-07T07:46:33.9790909Z * [new tag] ciflow/inductor/161109 -> ciflow/inductor/161109 2025-09-07T07:46:33.9791104Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-09-07T07:46:33.9791384Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-09-07T07:46:33.9791581Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-09-07T07:46:33.9791767Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-09-07T07:46:33.9791957Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-09-07T07:46:33.9792138Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-09-07T07:46:33.9792322Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-09-07T07:46:33.9792510Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-09-07T07:46:33.9792693Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-09-07T07:46:33.9792892Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-09-07T07:46:33.9793084Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-09-07T07:46:33.9793269Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-09-07T07:46:33.9793461Z * [new tag] ciflow/inductor/161442 -> ciflow/inductor/161442 2025-09-07T07:46:33.9793646Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-09-07T07:46:33.9793842Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-09-07T07:46:33.9794029Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-09-07T07:46:33.9794221Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-09-07T07:46:33.9794407Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-09-07T07:46:33.9794678Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-09-07T07:46:33.9794873Z * [new tag] ciflow/inductor/161595 -> ciflow/inductor/161595 2025-09-07T07:46:33.9795062Z * [new tag] ciflow/inductor/161596 -> ciflow/inductor/161596 2025-09-07T07:46:33.9795255Z * [new tag] ciflow/inductor/161630 -> ciflow/inductor/161630 2025-09-07T07:46:33.9795438Z * [new tag] ciflow/inductor/161667 -> ciflow/inductor/161667 2025-09-07T07:46:33.9795627Z * [new tag] ciflow/inductor/161670 -> ciflow/inductor/161670 2025-09-07T07:46:33.9795811Z * [new tag] ciflow/inductor/161673 -> ciflow/inductor/161673 2025-09-07T07:46:33.9795997Z * [new tag] ciflow/inductor/161674 -> ciflow/inductor/161674 2025-09-07T07:46:33.9796191Z * [new tag] ciflow/inductor/161675 -> ciflow/inductor/161675 2025-09-07T07:46:33.9796381Z * [new tag] ciflow/inductor/161693 -> ciflow/inductor/161693 2025-09-07T07:46:33.9796581Z * [new tag] ciflow/inductor/161695 -> ciflow/inductor/161695 2025-09-07T07:46:33.9796765Z * [new tag] ciflow/inductor/161715 -> ciflow/inductor/161715 2025-09-07T07:46:33.9796950Z * [new tag] ciflow/inductor/161730 -> ciflow/inductor/161730 2025-09-07T07:46:33.9797140Z * [new tag] ciflow/inductor/161732 -> ciflow/inductor/161732 2025-09-07T07:46:33.9797324Z * [new tag] ciflow/inductor/161744 -> ciflow/inductor/161744 2025-09-07T07:46:33.9797515Z * [new tag] ciflow/inductor/161746 -> ciflow/inductor/161746 2025-09-07T07:46:33.9797699Z * [new tag] ciflow/inductor/161747 -> ciflow/inductor/161747 2025-09-07T07:46:33.9797891Z * [new tag] ciflow/inductor/161819 -> ciflow/inductor/161819 2025-09-07T07:46:33.9798076Z * [new tag] ciflow/inductor/161821 -> ciflow/inductor/161821 2025-09-07T07:46:33.9798262Z * [new tag] ciflow/inductor/161828 -> ciflow/inductor/161828 2025-09-07T07:46:33.9798541Z * [new tag] ciflow/inductor/161879 -> ciflow/inductor/161879 2025-09-07T07:46:33.9798729Z * [new tag] ciflow/inductor/161880 -> ciflow/inductor/161880 2025-09-07T07:46:33.9798924Z * [new tag] ciflow/inductor/161881 -> ciflow/inductor/161881 2025-09-07T07:46:33.9799110Z * [new tag] ciflow/inductor/161907 -> ciflow/inductor/161907 2025-09-07T07:46:33.9799296Z * [new tag] ciflow/inductor/161914 -> ciflow/inductor/161914 2025-09-07T07:46:33.9799487Z * [new tag] ciflow/inductor/161924 -> ciflow/inductor/161924 2025-09-07T07:46:33.9799673Z * [new tag] ciflow/inductor/161936 -> ciflow/inductor/161936 2025-09-07T07:46:33.9799872Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-09-07T07:46:33.9800055Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-09-07T07:46:33.9800254Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-09-07T07:46:33.9800440Z * [new tag] ciflow/inductor/161955 -> ciflow/inductor/161955 2025-09-07T07:46:33.9800629Z * [new tag] ciflow/inductor/161957 -> ciflow/inductor/161957 2025-09-07T07:46:33.9800820Z * [new tag] ciflow/inductor/161975 -> ciflow/inductor/161975 2025-09-07T07:46:33.9801007Z * [new tag] ciflow/inductor/161977 -> ciflow/inductor/161977 2025-09-07T07:46:33.9801199Z * [new tag] ciflow/inductor/161978 -> ciflow/inductor/161978 2025-09-07T07:46:33.9801383Z * [new tag] ciflow/inductor/161979 -> ciflow/inductor/161979 2025-09-07T07:46:33.9801657Z * [new tag] ciflow/inductor/161980 -> ciflow/inductor/161980 2025-09-07T07:46:33.9801848Z * [new tag] ciflow/inductor/161988 -> ciflow/inductor/161988 2025-09-07T07:46:33.9802039Z * [new tag] ciflow/inductor/161994 -> ciflow/inductor/161994 2025-09-07T07:46:33.9802233Z * [new tag] ciflow/inductor/162013 -> ciflow/inductor/162013 2025-09-07T07:46:33.9802418Z * [new tag] ciflow/inductor/162014 -> ciflow/inductor/162014 2025-09-07T07:46:33.9802611Z * [new tag] ciflow/inductor/162017 -> ciflow/inductor/162017 2025-09-07T07:46:33.9802796Z * [new tag] ciflow/inductor/162021 -> ciflow/inductor/162021 2025-09-07T07:46:33.9803219Z * [new tag] ciflow/inductor/162023 -> ciflow/inductor/162023 2025-09-07T07:46:33.9803416Z * [new tag] ciflow/inductor/162027 -> ciflow/inductor/162027 2025-09-07T07:46:33.9803602Z * [new tag] ciflow/inductor/162029 -> ciflow/inductor/162029 2025-09-07T07:46:33.9803801Z * [new tag] ciflow/inductor/162030 -> ciflow/inductor/162030 2025-09-07T07:46:33.9803991Z * [new tag] ciflow/inductor/162031 -> ciflow/inductor/162031 2025-09-07T07:46:33.9804176Z * [new tag] ciflow/inductor/162033 -> ciflow/inductor/162033 2025-09-07T07:46:33.9804366Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-09-07T07:46:33.9804553Z * [new tag] ciflow/inductor/162053 -> ciflow/inductor/162053 2025-09-07T07:46:33.9804747Z * [new tag] ciflow/inductor/162056 -> ciflow/inductor/162056 2025-09-07T07:46:33.9804931Z * [new tag] ciflow/inductor/162063 -> ciflow/inductor/162063 2025-09-07T07:46:33.9805128Z * [new tag] ciflow/inductor/162066 -> ciflow/inductor/162066 2025-09-07T07:46:33.9805313Z * [new tag] ciflow/inductor/162068 -> ciflow/inductor/162068 2025-09-07T07:46:33.9805501Z * [new tag] ciflow/inductor/162081 -> ciflow/inductor/162081 2025-09-07T07:46:33.9805818Z * [new tag] ciflow/inductor/162088 -> ciflow/inductor/162088 2025-09-07T07:46:33.9806009Z * [new tag] ciflow/inductor/162089 -> ciflow/inductor/162089 2025-09-07T07:46:33.9806209Z * [new tag] ciflow/inductor/162094 -> ciflow/inductor/162094 2025-09-07T07:46:33.9806392Z * [new tag] ciflow/inductor/162098 -> ciflow/inductor/162098 2025-09-07T07:46:33.9806583Z * [new tag] ciflow/inductor/162101 -> ciflow/inductor/162101 2025-09-07T07:46:33.9806782Z * [new tag] ciflow/inductor/162102 -> ciflow/inductor/162102 2025-09-07T07:46:33.9806968Z * [new tag] ciflow/inductor/162104 -> ciflow/inductor/162104 2025-09-07T07:46:33.9807169Z * [new tag] ciflow/inductor/162106 -> ciflow/inductor/162106 2025-09-07T07:46:33.9807357Z * [new tag] ciflow/inductor/162108 -> ciflow/inductor/162108 2025-09-07T07:46:33.9807554Z * [new tag] ciflow/inductor/162126 -> ciflow/inductor/162126 2025-09-07T07:46:33.9807738Z * [new tag] ciflow/inductor/162149 -> ciflow/inductor/162149 2025-09-07T07:46:33.9807926Z * [new tag] ciflow/inductor/162164 -> ciflow/inductor/162164 2025-09-07T07:46:33.9808119Z * [new tag] ciflow/inductor/162166 -> ciflow/inductor/162166 2025-09-07T07:46:33.9808308Z * [new tag] ciflow/inductor/162169 -> ciflow/inductor/162169 2025-09-07T07:46:33.9808501Z * [new tag] ciflow/inductor/162170 -> ciflow/inductor/162170 2025-09-07T07:46:33.9808690Z * [new tag] ciflow/inductor/162171 -> ciflow/inductor/162171 2025-09-07T07:46:33.9808873Z * [new tag] ciflow/inductor/162183 -> ciflow/inductor/162183 2025-09-07T07:46:33.9809269Z * [new tag] ciflow/inductor/162189 -> ciflow/inductor/162189 2025-09-07T07:46:33.9809457Z * [new tag] ciflow/inductor/162190 -> ciflow/inductor/162190 2025-09-07T07:46:33.9809653Z * [new tag] ciflow/inductor/162191 -> ciflow/inductor/162191 2025-09-07T07:46:33.9809835Z * [new tag] ciflow/inductor/162194 -> ciflow/inductor/162194 2025-09-07T07:46:33.9810031Z * [new tag] ciflow/inductor/162200 -> ciflow/inductor/162200 2025-09-07T07:46:33.9810214Z * [new tag] ciflow/inductor/162201 -> ciflow/inductor/162201 2025-09-07T07:46:33.9810402Z * [new tag] ciflow/inductor/162208 -> ciflow/inductor/162208 2025-09-07T07:46:33.9810598Z * [new tag] ciflow/inductor/162211 -> ciflow/inductor/162211 2025-09-07T07:46:33.9810784Z * [new tag] ciflow/inductor/162216 -> ciflow/inductor/162216 2025-09-07T07:46:33.9810985Z * [new tag] ciflow/inductor/162220 -> ciflow/inductor/162220 2025-09-07T07:46:33.9811169Z * [new tag] ciflow/inductor/162222 -> ciflow/inductor/162222 2025-09-07T07:46:33.9811357Z * [new tag] ciflow/inductor/162227 -> ciflow/inductor/162227 2025-09-07T07:46:33.9811546Z * [new tag] ciflow/inductor/162238 -> ciflow/inductor/162238 2025-09-07T07:46:33.9811729Z * [new tag] ciflow/inductor/162239 -> ciflow/inductor/162239 2025-09-07T07:46:33.9811922Z * [new tag] ciflow/inductor/162240 -> ciflow/inductor/162240 2025-09-07T07:46:33.9812109Z * [new tag] ciflow/inductor/162244 -> ciflow/inductor/162244 2025-09-07T07:46:33.9812301Z * [new tag] ciflow/inductor/162245 -> ciflow/inductor/162245 2025-09-07T07:46:33.9812487Z * [new tag] ciflow/inductor/162262 -> ciflow/inductor/162262 2025-09-07T07:46:33.9812676Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-09-07T07:46:33.9812869Z * [new tag] ciflow/inductor/162278 -> ciflow/inductor/162278 2025-09-07T07:46:33.9813143Z * [new tag] ciflow/inductor/162284 -> ciflow/inductor/162284 2025-09-07T07:46:33.9813337Z * [new tag] ciflow/inductor/162286 -> ciflow/inductor/162286 2025-09-07T07:46:33.9813521Z * [new tag] ciflow/inductor/162288 -> ciflow/inductor/162288 2025-09-07T07:46:33.9813713Z * [new tag] ciflow/inductor/162293 -> ciflow/inductor/162293 2025-09-07T07:46:33.9813898Z * [new tag] ciflow/inductor/162294 -> ciflow/inductor/162294 2025-09-07T07:46:33.9814083Z * [new tag] ciflow/inductor/162295 -> ciflow/inductor/162295 2025-09-07T07:46:33.9814273Z * [new tag] ciflow/inductor/162296 -> ciflow/inductor/162296 2025-09-07T07:46:33.9814462Z * [new tag] ciflow/inductor/162298 -> ciflow/inductor/162298 2025-09-07T07:46:33.9814653Z * [new tag] ciflow/inductor/162307 -> ciflow/inductor/162307 2025-09-07T07:46:33.9814839Z * [new tag] ciflow/inductor/162309 -> ciflow/inductor/162309 2025-09-07T07:46:33.9815027Z * [new tag] ciflow/inductor/162311 -> ciflow/inductor/162311 2025-09-07T07:46:33.9815219Z * [new tag] ciflow/inductor/162312 -> ciflow/inductor/162312 2025-09-07T07:46:33.9815406Z * [new tag] ciflow/inductor/162315 -> ciflow/inductor/162315 2025-09-07T07:46:33.9815596Z * [new tag] ciflow/inductor/162316 -> ciflow/inductor/162316 2025-09-07T07:46:33.9815781Z * [new tag] ciflow/inductor/162318 -> ciflow/inductor/162318 2025-09-07T07:46:33.9815975Z * [new tag] ciflow/inductor/162323 -> ciflow/inductor/162323 2025-09-07T07:46:33.9816161Z * [new tag] ciflow/inductor/162341 -> ciflow/inductor/162341 2025-09-07T07:46:33.9816445Z * [new tag] ciflow/inductor/162345 -> ciflow/inductor/162345 2025-09-07T07:46:33.9816657Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-09-07T07:46:33.9816853Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-09-07T07:46:33.9817054Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-09-07T07:46:33.9817264Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-09-07T07:46:33.9817565Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-09-07T07:46:33.9817786Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-09-07T07:46:33.9817958Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-09-07T07:46:33.9818135Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-09-07T07:46:33.9818305Z * [new tag] ciflow/mps/161988 -> ciflow/mps/161988 2025-09-07T07:46:33.9818484Z * [new tag] ciflow/mps/162108 -> ciflow/mps/162108 2025-09-07T07:46:33.9818649Z * [new tag] ciflow/mps/162153 -> ciflow/mps/162153 2025-09-07T07:46:33.9818814Z * [new tag] ciflow/mps/162281 -> ciflow/mps/162281 2025-09-07T07:46:33.9819006Z * [new tag] ciflow/nightly/156049 -> ciflow/nightly/156049 2025-09-07T07:46:33.9819192Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-09-07T07:46:33.9819409Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-09-07T07:46:33.9819686Z * [new tag] ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529 2025-09-07T07:46:33.9819958Z * [new tag] ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715 2025-09-07T07:46:33.9820172Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-09-07T07:46:33.9820459Z * [new tag] ciflow/periodic/156703 -> ciflow/periodic/156703 2025-09-07T07:46:33.9820656Z * [new tag] ciflow/periodic/161715 -> ciflow/periodic/161715 2025-09-07T07:46:33.9820847Z * [new tag] ciflow/periodic/162021 -> ciflow/periodic/162021 2025-09-07T07:46:33.9821039Z * [new tag] ciflow/periodic/162323 -> ciflow/periodic/162323 2025-09-07T07:46:33.9821234Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-09-07T07:46:33.9821426Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-09-07T07:46:33.9821617Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-09-07T07:46:33.9821808Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-09-07T07:46:33.9822034Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-09-07T07:46:33.9822277Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-09-07T07:46:33.9822505Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-09-07T07:46:33.9822745Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-09-07T07:46:33.9822968Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-09-07T07:46:33.9823221Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-09-07T07:46:33.9823438Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-09-07T07:46:33.9823641Z * [new tag] ciflow/rocm-mi300/154170 -> ciflow/rocm-mi300/154170 2025-09-07T07:46:33.9823919Z * [new tag] ciflow/rocm-mi300/158747 -> ciflow/rocm-mi300/158747 2025-09-07T07:46:33.9824106Z * [new tag] ciflow/rocm-mi300/159146 -> ciflow/rocm-mi300/159146 2025-09-07T07:46:33.9824304Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-09-07T07:46:33.9824491Z * [new tag] ciflow/rocm-mi300/161715 -> ciflow/rocm-mi300/161715 2025-09-07T07:46:33.9824682Z * [new tag] ciflow/rocm-mi300/161957 -> ciflow/rocm-mi300/161957 2025-09-07T07:46:33.9824870Z * [new tag] ciflow/rocm-mi300/162053 -> ciflow/rocm-mi300/162053 2025-09-07T07:46:33.9825066Z * [new tag] ciflow/rocm-mi300/162056 -> ciflow/rocm-mi300/162056 2025-09-07T07:46:33.9825250Z * [new tag] ciflow/rocm-mi300/162112 -> ciflow/rocm-mi300/162112 2025-09-07T07:46:33.9825438Z * [new tag] ciflow/rocm-mi300/162245 -> ciflow/rocm-mi300/162245 2025-09-07T07:46:33.9825635Z * [new tag] ciflow/rocm-mi300/162278 -> ciflow/rocm-mi300/162278 2025-09-07T07:46:33.9825823Z * [new tag] ciflow/rocm-mi300/162288 -> ciflow/rocm-mi300/162288 2025-09-07T07:46:33.9826017Z * [new tag] ciflow/rocm-mi355/162053 -> ciflow/rocm-mi355/162053 2025-09-07T07:46:33.9826203Z * [new tag] ciflow/rocm-mi355/162056 -> ciflow/rocm-mi355/162056 2025-09-07T07:46:33.9826374Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-09-07T07:46:33.9826553Z * [new tag] ciflow/rocm/154170 -> ciflow/rocm/154170 2025-09-07T07:46:33.9826717Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-09-07T07:46:33.9826889Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-09-07T07:46:33.9827056Z * [new tag] ciflow/rocm/158747 -> ciflow/rocm/158747 2025-09-07T07:46:33.9827227Z * [new tag] ciflow/rocm/159146 -> ciflow/rocm/159146 2025-09-07T07:46:33.9827394Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-09-07T07:46:33.9827656Z * [new tag] ciflow/rocm/161715 -> ciflow/rocm/161715 2025-09-07T07:46:33.9827831Z * [new tag] ciflow/rocm/161972 -> ciflow/rocm/161972 2025-09-07T07:46:33.9827999Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-09-07T07:46:33.9828171Z * [new tag] ciflow/rocm/162053 -> ciflow/rocm/162053 2025-09-07T07:46:33.9828336Z * [new tag] ciflow/rocm/162056 -> ciflow/rocm/162056 2025-09-07T07:46:33.9828497Z * [new tag] ciflow/rocm/162112 -> ciflow/rocm/162112 2025-09-07T07:46:33.9828667Z * [new tag] ciflow/rocm/162278 -> ciflow/rocm/162278 2025-09-07T07:46:33.9828832Z * [new tag] ciflow/rocm/162288 -> ciflow/rocm/162288 2025-09-07T07:46:33.9829009Z * [new tag] ciflow/rocm/162305 -> ciflow/rocm/162305 2025-09-07T07:46:33.9829182Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-09-07T07:46:33.9829352Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-09-07T07:46:33.9829893Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-09-07T07:46:33.9830067Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-09-07T07:46:33.9830240Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-09-07T07:46:33.9830412Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-09-07T07:46:33.9830590Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-09-07T07:46:33.9830761Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-09-07T07:46:33.9831033Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-09-07T07:46:33.9831216Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-09-07T07:46:33.9831386Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-09-07T07:46:33.9831560Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-09-07T07:46:33.9831730Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-09-07T07:46:33.9832224Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-09-07T07:46:33.9832392Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-09-07T07:46:33.9832564Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-09-07T07:46:33.9832741Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-09-07T07:46:33.9832913Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-09-07T07:46:33.9833092Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-09-07T07:46:33.9833608Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-09-07T07:46:33.9833834Z * [new tag] ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329 2025-09-07T07:46:33.9834013Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-09-07T07:46:33.9834181Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-09-07T07:46:33.9834358Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-09-07T07:46:33.9834528Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-09-07T07:46:33.9834707Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-09-07T07:46:33.9834877Z * [new tag] ciflow/trunk/148919 -> ciflow/trunk/148919 2025-09-07T07:46:33.9835136Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-09-07T07:46:33.9835319Z * [new tag] ciflow/trunk/154170 -> ciflow/trunk/154170 2025-09-07T07:46:33.9835489Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-09-07T07:46:33.9835666Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-09-07T07:46:33.9835837Z * [new tag] ciflow/trunk/156703 -> ciflow/trunk/156703 2025-09-07T07:46:33.9836007Z * [new tag] ciflow/trunk/156711 -> ciflow/trunk/156711 2025-09-07T07:46:33.9836183Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-09-07T07:46:33.9836355Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-09-07T07:46:33.9836536Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-09-07T07:46:33.9836710Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-09-07T07:46:33.9836886Z * [new tag] ciflow/trunk/157813 -> ciflow/trunk/157813 2025-09-07T07:46:33.9837057Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-09-07T07:46:33.9837225Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-09-07T07:46:33.9837404Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-09-07T07:46:33.9837577Z * [new tag] ciflow/trunk/158404 -> ciflow/trunk/158404 2025-09-07T07:46:33.9837754Z * [new tag] ciflow/trunk/158647 -> ciflow/trunk/158647 2025-09-07T07:46:33.9837922Z * [new tag] ciflow/trunk/158846 -> ciflow/trunk/158846 2025-09-07T07:46:33.9838201Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-09-07T07:46:33.9838381Z * [new tag] ciflow/trunk/159682 -> ciflow/trunk/159682 2025-09-07T07:46:33.9838553Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-09-07T07:46:33.9838732Z * [new tag] ciflow/trunk/160161 -> ciflow/trunk/160161 2025-09-07T07:46:33.9838902Z * [new tag] ciflow/trunk/160236 -> ciflow/trunk/160236 2025-09-07T07:46:33.9839082Z * [new tag] ciflow/trunk/160329 -> ciflow/trunk/160329 2025-09-07T07:46:33.9839251Z * [new tag] ciflow/trunk/160480 -> ciflow/trunk/160480 2025-09-07T07:46:33.9839417Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-09-07T07:46:33.9839598Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-09-07T07:46:33.9839766Z * [new tag] ciflow/trunk/160843 -> ciflow/trunk/160843 2025-09-07T07:46:33.9839944Z * [new tag] ciflow/trunk/160869 -> ciflow/trunk/160869 2025-09-07T07:46:33.9840117Z * [new tag] ciflow/trunk/160928 -> ciflow/trunk/160928 2025-09-07T07:46:33.9840281Z * [new tag] ciflow/trunk/160940 -> ciflow/trunk/160940 2025-09-07T07:46:33.9840460Z * [new tag] ciflow/trunk/160943 -> ciflow/trunk/160943 2025-09-07T07:46:33.9840627Z * [new tag] ciflow/trunk/160953 -> ciflow/trunk/160953 2025-09-07T07:46:33.9840806Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-09-07T07:46:33.9840977Z * [new tag] ciflow/trunk/161178 -> ciflow/trunk/161178 2025-09-07T07:46:33.9841150Z * [new tag] ciflow/trunk/161349 -> ciflow/trunk/161349 2025-09-07T07:46:33.9841319Z * [new tag] ciflow/trunk/161350 -> ciflow/trunk/161350 2025-09-07T07:46:33.9841491Z * [new tag] ciflow/trunk/161351 -> ciflow/trunk/161351 2025-09-07T07:46:33.9841755Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-09-07T07:46:33.9841929Z * [new tag] ciflow/trunk/161405 -> ciflow/trunk/161405 2025-09-07T07:46:33.9842107Z * [new tag] ciflow/trunk/161406 -> ciflow/trunk/161406 2025-09-07T07:46:33.9842274Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-09-07T07:46:33.9842438Z * [new tag] ciflow/trunk/161468 -> ciflow/trunk/161468 2025-09-07T07:46:33.9842618Z * [new tag] ciflow/trunk/161499 -> ciflow/trunk/161499 2025-09-07T07:46:33.9842787Z * [new tag] ciflow/trunk/161527 -> ciflow/trunk/161527 2025-09-07T07:46:33.9843084Z * [new tag] ciflow/trunk/161534 -> ciflow/trunk/161534 2025-09-07T07:46:33.9843260Z * [new tag] ciflow/trunk/161591 -> ciflow/trunk/161591 2025-09-07T07:46:33.9843439Z * [new tag] ciflow/trunk/161595 -> ciflow/trunk/161595 2025-09-07T07:46:33.9843612Z * [new tag] ciflow/trunk/161596 -> ciflow/trunk/161596 2025-09-07T07:46:33.9843784Z * [new tag] ciflow/trunk/161633 -> ciflow/trunk/161633 2025-09-07T07:46:33.9843963Z * [new tag] ciflow/trunk/161634 -> ciflow/trunk/161634 2025-09-07T07:46:33.9844130Z * [new tag] ciflow/trunk/161635 -> ciflow/trunk/161635 2025-09-07T07:46:33.9844300Z * [new tag] ciflow/trunk/161667 -> ciflow/trunk/161667 2025-09-07T07:46:33.9844465Z * [new tag] ciflow/trunk/161670 -> ciflow/trunk/161670 2025-09-07T07:46:33.9844632Z * [new tag] ciflow/trunk/161692 -> ciflow/trunk/161692 2025-09-07T07:46:33.9844806Z * [new tag] ciflow/trunk/161693 -> ciflow/trunk/161693 2025-09-07T07:46:33.9845100Z * [new tag] ciflow/trunk/161695 -> ciflow/trunk/161695 2025-09-07T07:46:33.9845284Z * [new tag] ciflow/trunk/161730 -> ciflow/trunk/161730 2025-09-07T07:46:33.9845454Z * [new tag] ciflow/trunk/161744 -> ciflow/trunk/161744 2025-09-07T07:46:33.9845630Z * [new tag] ciflow/trunk/161749 -> ciflow/trunk/161749 2025-09-07T07:46:33.9845800Z * [new tag] ciflow/trunk/161881 -> ciflow/trunk/161881 2025-09-07T07:46:33.9845970Z * [new tag] ciflow/trunk/161924 -> ciflow/trunk/161924 2025-09-07T07:46:33.9846146Z * [new tag] ciflow/trunk/161926 -> ciflow/trunk/161926 2025-09-07T07:46:33.9846315Z * [new tag] ciflow/trunk/161936 -> ciflow/trunk/161936 2025-09-07T07:46:33.9846493Z * [new tag] ciflow/trunk/161952 -> ciflow/trunk/161952 2025-09-07T07:46:33.9846669Z * [new tag] ciflow/trunk/161955 -> ciflow/trunk/161955 2025-09-07T07:46:33.9846840Z * [new tag] ciflow/trunk/161957 -> ciflow/trunk/161957 2025-09-07T07:46:33.9847019Z * [new tag] ciflow/trunk/161959 -> ciflow/trunk/161959 2025-09-07T07:46:33.9847186Z * [new tag] ciflow/trunk/161977 -> ciflow/trunk/161977 2025-09-07T07:46:33.9847364Z * [new tag] ciflow/trunk/161988 -> ciflow/trunk/161988 2025-09-07T07:46:33.9847533Z * [new tag] ciflow/trunk/161994 -> ciflow/trunk/161994 2025-09-07T07:46:33.9847699Z * [new tag] ciflow/trunk/162007 -> ciflow/trunk/162007 2025-09-07T07:46:33.9847875Z * [new tag] ciflow/trunk/162013 -> ciflow/trunk/162013 2025-09-07T07:46:33.9848044Z * [new tag] ciflow/trunk/162017 -> ciflow/trunk/162017 2025-09-07T07:46:33.9848222Z * [new tag] ciflow/trunk/162021 -> ciflow/trunk/162021 2025-09-07T07:46:33.9848389Z * [new tag] ciflow/trunk/162022 -> ciflow/trunk/162022 2025-09-07T07:46:33.9848673Z * [new tag] ciflow/trunk/162040 -> ciflow/trunk/162040 2025-09-07T07:46:33.9848845Z * [new tag] ciflow/trunk/162041 -> ciflow/trunk/162041 2025-09-07T07:46:33.9849012Z * [new tag] ciflow/trunk/162062 -> ciflow/trunk/162062 2025-09-07T07:46:33.9849186Z * [new tag] ciflow/trunk/162066 -> ciflow/trunk/162066 2025-09-07T07:46:33.9849353Z * [new tag] ciflow/trunk/162089 -> ciflow/trunk/162089 2025-09-07T07:46:33.9849528Z * [new tag] ciflow/trunk/162099 -> ciflow/trunk/162099 2025-09-07T07:46:33.9849697Z * [new tag] ciflow/trunk/162104 -> ciflow/trunk/162104 2025-09-07T07:46:33.9849866Z * [new tag] ciflow/trunk/162106 -> ciflow/trunk/162106 2025-09-07T07:46:33.9850048Z * [new tag] ciflow/trunk/162112 -> ciflow/trunk/162112 2025-09-07T07:46:33.9850221Z * [new tag] ciflow/trunk/162119 -> ciflow/trunk/162119 2025-09-07T07:46:33.9850397Z * [new tag] ciflow/trunk/162142 -> ciflow/trunk/162142 2025-09-07T07:46:33.9850571Z * [new tag] ciflow/trunk/162169 -> ciflow/trunk/162169 2025-09-07T07:46:33.9850754Z * [new tag] ciflow/trunk/162183 -> ciflow/trunk/162183 2025-09-07T07:46:33.9850922Z * [new tag] ciflow/trunk/162190 -> ciflow/trunk/162190 2025-09-07T07:46:33.9851092Z * [new tag] ciflow/trunk/162194 -> ciflow/trunk/162194 2025-09-07T07:46:33.9851276Z * [new tag] ciflow/trunk/162200 -> ciflow/trunk/162200 2025-09-07T07:46:33.9851444Z * [new tag] ciflow/trunk/162206 -> ciflow/trunk/162206 2025-09-07T07:46:33.9851713Z * [new tag] ciflow/trunk/162208 -> ciflow/trunk/162208 2025-09-07T07:46:33.9851884Z * [new tag] ciflow/trunk/162222 -> ciflow/trunk/162222 2025-09-07T07:46:33.9852055Z * [new tag] ciflow/trunk/162238 -> ciflow/trunk/162238 2025-09-07T07:46:33.9852237Z * [new tag] ciflow/trunk/162244 -> ciflow/trunk/162244 2025-09-07T07:46:33.9852405Z * [new tag] ciflow/trunk/162267 -> ciflow/trunk/162267 2025-09-07T07:46:33.9852588Z * [new tag] ciflow/trunk/162269 -> ciflow/trunk/162269 2025-09-07T07:46:33.9852759Z * [new tag] ciflow/trunk/162278 -> ciflow/trunk/162278 2025-09-07T07:46:33.9852941Z * [new tag] ciflow/trunk/162286 -> ciflow/trunk/162286 2025-09-07T07:46:33.9853112Z * [new tag] ciflow/trunk/162288 -> ciflow/trunk/162288 2025-09-07T07:46:33.9853283Z * [new tag] ciflow/trunk/162293 -> ciflow/trunk/162293 2025-09-07T07:46:33.9853468Z * [new tag] ciflow/trunk/162310 -> ciflow/trunk/162310 2025-09-07T07:46:33.9853646Z * [new tag] ciflow/trunk/162311 -> ciflow/trunk/162311 2025-09-07T07:46:33.9853827Z * [new tag] ciflow/trunk/162315 -> ciflow/trunk/162315 2025-09-07T07:46:33.9853999Z * [new tag] ciflow/trunk/162325 -> ciflow/trunk/162325 2025-09-07T07:46:33.9854171Z * [new tag] ciflow/trunk/162328 -> ciflow/trunk/162328 2025-09-07T07:46:33.9854361Z * [new tag] ciflow/trunk/162329 -> ciflow/trunk/162329 2025-09-07T07:46:33.9854535Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-09-07T07:46:33.9854716Z * [new tag] ciflow/vllm/162292 -> ciflow/vllm/162292 2025-09-07T07:46:33.9854908Z * [new tag] ciflow/win-arm64/156049 -> ciflow/win-arm64/156049 2025-09-07T07:46:33.9855110Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-09-07T07:46:33.9855282Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-09-07T07:46:33.9855542Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-09-07T07:46:33.9855725Z * [new tag] ciflow/xpu/159459 -> ciflow/xpu/159459 2025-09-07T07:46:33.9855892Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-09-07T07:46:33.9856064Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-09-07T07:46:33.9856231Z * [new tag] ciflow/xpu/160867 -> ciflow/xpu/160867 2025-09-07T07:46:33.9856393Z * [new tag] ciflow/xpu/160938 -> ciflow/xpu/160938 2025-09-07T07:46:33.9856570Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-09-07T07:46:33.9856735Z * [new tag] ciflow/xpu/160953 -> ciflow/xpu/160953 2025-09-07T07:46:33.9856913Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-09-07T07:46:33.9857084Z * [new tag] ciflow/xpu/161058 -> ciflow/xpu/161058 2025-09-07T07:46:33.9857262Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-09-07T07:46:33.9857504Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-09-07T07:46:33.9857670Z * [new tag] ciflow/xpu/161485 -> ciflow/xpu/161485 2025-09-07T07:46:33.9857843Z * [new tag] ciflow/xpu/161988 -> ciflow/xpu/161988 2025-09-07T07:46:33.9858011Z * [new tag] ciflow/xpu/162062 -> ciflow/xpu/162062 2025-09-07T07:46:33.9858173Z * [new tag] cslpull75 -> cslpull75 2025-09-07T07:46:33.9858324Z * [new tag] cslpull76 -> cslpull76 2025-09-07T07:46:33.9858576Z * [new tag] cslpull77 -> cslpull77 2025-09-07T07:46:33.9858728Z * [new tag] cslpull78 -> cslpull78 2025-09-07T07:46:33.9858875Z * [new tag] cslpull79 -> cslpull79 2025-09-07T07:46:33.9859034Z * [new tag] cslpull80 -> cslpull80 2025-09-07T07:46:33.9859180Z * [new tag] cslpull81 -> cslpull81 2025-09-07T07:46:33.9859324Z * [new tag] cslpull82 -> cslpull82 2025-09-07T07:46:33.9859480Z * [new tag] cslpull83 -> cslpull83 2025-09-07T07:46:33.9859622Z * [new tag] cslpull84 -> cslpull84 2025-09-07T07:46:33.9859779Z * [new tag] cslpull85 -> cslpull85 2025-09-07T07:46:33.9859923Z * [new tag] cslpull86 -> cslpull86 2025-09-07T07:46:33.9860074Z * [new tag] cslpull87 -> cslpull87 2025-09-07T07:46:33.9860221Z * [new tag] cslpull88 -> cslpull88 2025-09-07T07:46:33.9860367Z * [new tag] cslpull89 -> cslpull89 2025-09-07T07:46:33.9860525Z * [new tag] cslpull90 -> cslpull90 2025-09-07T07:46:33.9860670Z * [new tag] cslpull91 -> cslpull91 2025-09-07T07:46:33.9860826Z * [new tag] cslpull92 -> cslpull92 2025-09-07T07:46:33.9860975Z * [new tag] flight_5 -> flight_5 2025-09-07T07:46:33.9861123Z * [new tag] flight_5.1 -> flight_5.1 2025-09-07T07:46:33.9861280Z * [new tag] flight_5.2 -> flight_5.2 2025-09-07T07:46:33.9861425Z * [new tag] flight_5.3 -> flight_5.3 2025-09-07T07:46:33.9861585Z * [new tag] forpull1 -> forpull1 2025-09-07T07:46:33.9861762Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-09-07T07:46:33.9861934Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-09-07T07:46:33.9862224Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-09-07T07:46:33.9862401Z * [new tag] nightly-binary -> nightly-binary 2025-09-07T07:46:33.9862596Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-09-07T07:46:33.9862763Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-09-07T07:46:33.9863148Z * [new tag] trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608 2025-09-07T07:46:33.9863539Z * [new tag] trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 2025-09-07T07:46:33.9863924Z * [new tag] trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544 2025-09-07T07:46:33.9864344Z * [new tag] trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b 2025-09-07T07:46:33.9864726Z * [new tag] trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388 2025-09-07T07:46:33.9865118Z * [new tag] trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 2025-09-07T07:46:33.9865493Z * [new tag] trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4 2025-09-07T07:46:33.9865892Z * [new tag] trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 2025-09-07T07:46:33.9866269Z * [new tag] trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23 2025-09-07T07:46:33.9866746Z * [new tag] trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 2025-09-07T07:46:33.9867133Z * [new tag] trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 2025-09-07T07:46:33.9867512Z * [new tag] trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 2025-09-07T07:46:33.9867906Z * [new tag] trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 2025-09-07T07:46:33.9868290Z * [new tag] trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 2025-09-07T07:46:33.9868692Z * [new tag] trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 2025-09-07T07:46:33.9869085Z * [new tag] trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c 2025-09-07T07:46:33.9869495Z * [new tag] trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 2025-09-07T07:46:33.9869878Z * [new tag] trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e 2025-09-07T07:46:33.9870260Z * [new tag] trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 2025-09-07T07:46:33.9870675Z * [new tag] trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f 2025-09-07T07:46:33.9871056Z * [new tag] trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f 2025-09-07T07:46:33.9871450Z * [new tag] trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0 2025-09-07T07:46:33.9871840Z * [new tag] trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c 2025-09-07T07:46:33.9872330Z * [new tag] trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 2025-09-07T07:46:33.9872724Z * [new tag] trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 2025-09-07T07:46:33.9873113Z * [new tag] trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb 2025-09-07T07:46:33.9873503Z * [new tag] trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 2025-09-07T07:46:33.9873893Z * [new tag] trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 2025-09-07T07:46:33.9874284Z * [new tag] trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c 2025-09-07T07:46:33.9874679Z * [new tag] trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 2025-09-07T07:46:33.9875084Z * [new tag] trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 2025-09-07T07:46:33.9875467Z * [new tag] trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 2025-09-07T07:46:33.9875868Z * [new tag] trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a 2025-09-07T07:46:33.9876264Z * [new tag] trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 2025-09-07T07:46:33.9876670Z * [new tag] trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 2025-09-07T07:46:33.9877050Z * [new tag] trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a 2025-09-07T07:46:33.9877541Z * [new tag] trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b 2025-09-07T07:46:33.9877924Z * [new tag] trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc 2025-09-07T07:46:33.9878299Z * [new tag] trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05 2025-09-07T07:46:33.9878693Z * [new tag] trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 2025-09-07T07:46:33.9879075Z * [new tag] trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd 2025-09-07T07:46:33.9879473Z * [new tag] trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 2025-09-07T07:46:33.9879860Z * [new tag] trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f 2025-09-07T07:46:33.9880247Z * [new tag] trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23 2025-09-07T07:46:33.9880634Z * [new tag] trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 2025-09-07T07:46:33.9881007Z * [new tag] trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f 2025-09-07T07:46:33.9881412Z * [new tag] trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 2025-09-07T07:46:33.9881780Z * [new tag] trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9 2025-09-07T07:46:33.9882174Z * [new tag] trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 2025-09-07T07:46:33.9882561Z * [new tag] trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef 2025-09-07T07:46:33.9883185Z * [new tag] trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c 2025-09-07T07:46:33.9883565Z * [new tag] trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6 2025-09-07T07:46:33.9883957Z * [new tag] trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 2025-09-07T07:46:33.9884357Z * [new tag] trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a 2025-09-07T07:46:33.9884746Z * [new tag] trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 2025-09-07T07:46:33.9885151Z * [new tag] trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 2025-09-07T07:46:33.9885543Z * [new tag] trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 2025-09-07T07:46:33.9885943Z * [new tag] trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 2025-09-07T07:46:33.9886319Z * [new tag] trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176 2025-09-07T07:46:33.9886698Z * [new tag] trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 2025-09-07T07:46:33.9887099Z * [new tag] trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b 2025-09-07T07:46:33.9887480Z * [new tag] trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 2025-09-07T07:46:33.9887973Z * [new tag] trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287 2025-09-07T07:46:33.9888351Z * [new tag] trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f 2025-09-07T07:46:33.9888742Z * [new tag] trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 2025-09-07T07:46:33.9889137Z * [new tag] trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 2025-09-07T07:46:33.9889540Z * [new tag] trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f 2025-09-07T07:46:33.9889935Z * [new tag] trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf 2025-09-07T07:46:33.9890323Z * [new tag] trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 2025-09-07T07:46:33.9890726Z * [new tag] trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d 2025-09-07T07:46:33.9891108Z * [new tag] trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa 2025-09-07T07:46:33.9891502Z * [new tag] trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 2025-09-07T07:46:33.9891881Z * [new tag] trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336 2025-09-07T07:46:33.9892264Z * [new tag] trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63 2025-09-07T07:46:33.9892656Z * [new tag] trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3 2025-09-07T07:46:33.9893042Z * [new tag] trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c 2025-09-07T07:46:33.9893523Z * [new tag] trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 2025-09-07T07:46:33.9893917Z * [new tag] trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf 2025-09-07T07:46:33.9894331Z * [new tag] trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e 2025-09-07T07:46:33.9894729Z * [new tag] trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 2025-09-07T07:46:33.9895121Z * [new tag] trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215 2025-09-07T07:46:33.9895513Z * [new tag] trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d 2025-09-07T07:46:33.9895905Z * [new tag] trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 2025-09-07T07:46:33.9896296Z * [new tag] trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c 2025-09-07T07:46:33.9896698Z * [new tag] trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 2025-09-07T07:46:33.9897083Z * [new tag] trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b 2025-09-07T07:46:33.9897538Z * [new tag] trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 2025-09-07T07:46:33.9897926Z * [new tag] trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503 2025-09-07T07:46:33.9898421Z * [new tag] trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 2025-09-07T07:46:33.9898825Z * [new tag] trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 2025-09-07T07:46:33.9899219Z * [new tag] trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 2025-09-07T07:46:33.9899610Z * [new tag] trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 2025-09-07T07:46:33.9899998Z * [new tag] trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a 2025-09-07T07:46:33.9900375Z * [new tag] trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 2025-09-07T07:46:33.9900777Z * [new tag] trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 2025-09-07T07:46:33.9901171Z * [new tag] trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c 2025-09-07T07:46:33.9901580Z * [new tag] trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 2025-09-07T07:46:33.9901961Z * [new tag] trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806 2025-09-07T07:46:33.9902367Z * [new tag] trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 2025-09-07T07:46:33.9902753Z * [new tag] trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 2025-09-07T07:46:33.9903146Z * [new tag] trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 2025-09-07T07:46:33.9903527Z * [new tag] trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251 2025-09-07T07:46:33.9904016Z * [new tag] trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 2025-09-07T07:46:33.9904403Z * [new tag] trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c 2025-09-07T07:46:33.9904785Z * [new tag] trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a 2025-09-07T07:46:33.9905180Z * [new tag] trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db 2025-09-07T07:46:33.9905558Z * [new tag] trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536 2025-09-07T07:46:33.9905956Z * [new tag] trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f 2025-09-07T07:46:33.9906343Z * [new tag] trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 2025-09-07T07:46:33.9906729Z * [new tag] trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b 2025-09-07T07:46:33.9907118Z * [new tag] trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda 2025-09-07T07:46:33.9907503Z * [new tag] trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b 2025-09-07T07:46:33.9907909Z * [new tag] trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 2025-09-07T07:46:33.9908291Z * [new tag] trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8 2025-09-07T07:46:33.9908698Z * [new tag] trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b 2025-09-07T07:46:33.9909166Z * [new tag] trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab 2025-09-07T07:46:33.9909564Z * [new tag] trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 2025-09-07T07:46:33.9909938Z * [new tag] trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe 2025-09-07T07:46:33.9910332Z * [new tag] trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 2025-09-07T07:46:33.9910742Z * [new tag] trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 2025-09-07T07:46:33.9911124Z * [new tag] trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 2025-09-07T07:46:33.9911534Z * [new tag] trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c 2025-09-07T07:46:33.9911913Z * [new tag] trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d 2025-09-07T07:46:33.9912292Z * [new tag] trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429 2025-09-07T07:46:33.9917971Z * [new tag] trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 2025-09-07T07:46:33.9918452Z * [new tag] trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c 2025-09-07T07:46:33.9918850Z * [new tag] trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895 2025-09-07T07:46:33.9919250Z * [new tag] trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 2025-09-07T07:46:33.9919649Z * [new tag] trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435 2025-09-07T07:46:33.9920221Z * [new tag] trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965 2025-09-07T07:46:33.9920612Z * [new tag] trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 2025-09-07T07:46:33.9921001Z * [new tag] trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 2025-09-07T07:46:33.9921398Z * [new tag] trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 2025-09-07T07:46:33.9921781Z * [new tag] trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 2025-09-07T07:46:33.9922169Z * [new tag] trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 2025-09-07T07:46:33.9922556Z * [new tag] trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f 2025-09-07T07:46:33.9923108Z * [new tag] trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 2025-09-07T07:46:33.9923493Z * [new tag] trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610 2025-09-07T07:46:33.9923874Z * [new tag] trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 2025-09-07T07:46:33.9924274Z * [new tag] trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af 2025-09-07T07:46:33.9924665Z * [new tag] trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 2025-09-07T07:46:33.9925198Z * [new tag] trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d 2025-09-07T07:46:33.9925578Z * [new tag] trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 2025-09-07T07:46:33.9925973Z * [new tag] trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 2025-09-07T07:46:33.9926352Z * [new tag] trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab 2025-09-07T07:46:33.9926747Z * [new tag] trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d 2025-09-07T07:46:33.9927127Z * [new tag] trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:33.9927517Z * [new tag] trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c 2025-09-07T07:46:33.9927912Z * [new tag] trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e 2025-09-07T07:46:33.9928299Z * [new tag] trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 2025-09-07T07:46:33.9928682Z * [new tag] trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1 2025-09-07T07:46:33.9929069Z * [new tag] trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 2025-09-07T07:46:33.9929456Z * [new tag] trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a 2025-09-07T07:46:33.9929840Z * [new tag] trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500 2025-09-07T07:46:33.9930236Z * [new tag] trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 2025-09-07T07:46:33.9930770Z * [new tag] trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6 2025-09-07T07:46:33.9931162Z * [new tag] trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 2025-09-07T07:46:33.9931559Z * [new tag] trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd 2025-09-07T07:46:33.9931939Z * [new tag] trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57 2025-09-07T07:46:33.9932321Z * [new tag] trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4 2025-09-07T07:46:33.9932713Z * [new tag] trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e 2025-09-07T07:46:33.9933116Z * [new tag] trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839 2025-09-07T07:46:33.9933498Z * [new tag] trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60 2025-09-07T07:46:33.9933877Z * [new tag] trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 2025-09-07T07:46:33.9934280Z * [new tag] trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 2025-09-07T07:46:33.9934670Z * [new tag] trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 2025-09-07T07:46:33.9935066Z * [new tag] trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 2025-09-07T07:46:33.9935438Z * [new tag] trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d 2025-09-07T07:46:33.9935939Z * [new tag] trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 2025-09-07T07:46:33.9936316Z * [new tag] trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92 2025-09-07T07:46:33.9936714Z * [new tag] trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098 2025-09-07T07:46:33.9937092Z * [new tag] trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356 2025-09-07T07:46:33.9937558Z * [new tag] trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae 2025-09-07T07:46:33.9937967Z * [new tag] trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 2025-09-07T07:46:33.9938357Z * [new tag] trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e 2025-09-07T07:46:33.9938762Z * [new tag] trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 2025-09-07T07:46:33.9939146Z * [new tag] trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 2025-09-07T07:46:33.9939549Z * [new tag] trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c 2025-09-07T07:46:33.9939939Z * [new tag] trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 2025-09-07T07:46:33.9940332Z * [new tag] trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d 2025-09-07T07:46:33.9940723Z * [new tag] trunk/ada43ed39c80b746b4822c92640a1882619e2795 -> trunk/ada43ed39c80b746b4822c92640a1882619e2795 2025-09-07T07:46:33.9941119Z * [new tag] trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa 2025-09-07T07:46:33.9941620Z * [new tag] trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c 2025-09-07T07:46:33.9942004Z * [new tag] trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d 2025-09-07T07:46:33.9942388Z * [new tag] trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 2025-09-07T07:46:33.9942778Z * [new tag] trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f 2025-09-07T07:46:33.9943173Z * [new tag] trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 2025-09-07T07:46:33.9943551Z * [new tag] trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 2025-09-07T07:46:33.9943951Z * [new tag] trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de 2025-09-07T07:46:33.9944331Z * [new tag] trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b 2025-09-07T07:46:33.9944724Z * [new tag] trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 2025-09-07T07:46:33.9945123Z * [new tag] trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 2025-09-07T07:46:33.9945504Z * [new tag] trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b 2025-09-07T07:46:33.9945893Z * [new tag] trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde 2025-09-07T07:46:33.9946408Z * [new tag] trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c 2025-09-07T07:46:33.9946809Z * [new tag] trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 2025-09-07T07:46:33.9947191Z * [new tag] trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052 2025-09-07T07:46:33.9947569Z * [new tag] trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e 2025-09-07T07:46:33.9947962Z * [new tag] trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 2025-09-07T07:46:33.9948355Z * [new tag] trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 2025-09-07T07:46:33.9948738Z * [new tag] trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85 2025-09-07T07:46:33.9949132Z * [new tag] trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d 2025-09-07T07:46:33.9949542Z * [new tag] trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 2025-09-07T07:46:33.9949915Z * [new tag] trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865 2025-09-07T07:46:33.9950312Z * [new tag] trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 2025-09-07T07:46:33.9950709Z * [new tag] trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 2025-09-07T07:46:33.9951100Z * [new tag] trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 2025-09-07T07:46:33.9951506Z * [new tag] trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf 2025-09-07T07:46:33.9952016Z * [new tag] trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 2025-09-07T07:46:33.9952417Z * [new tag] trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad 2025-09-07T07:46:33.9952800Z * [new tag] trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 2025-09-07T07:46:33.9953183Z * [new tag] trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 2025-09-07T07:46:33.9953552Z * [new tag] trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76 2025-09-07T07:46:33.9953931Z * [new tag] trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5 2025-09-07T07:46:33.9954329Z * [new tag] trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 2025-09-07T07:46:33.9954722Z * [new tag] trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd 2025-09-07T07:46:33.9955104Z * [new tag] trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741 2025-09-07T07:46:33.9955488Z * [new tag] trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b 2025-09-07T07:46:33.9955878Z * [new tag] trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 2025-09-07T07:46:33.9956279Z * [new tag] trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 2025-09-07T07:46:33.9956672Z * [new tag] trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b 2025-09-07T07:46:34.0909007Z * [new tag] trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8 2025-09-07T07:46:34.0909399Z * [new tag] trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 2025-09-07T07:46:34.0909792Z * [new tag] trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7 2025-09-07T07:46:34.0910169Z * [new tag] trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87 2025-09-07T07:46:34.0910561Z * [new tag] trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e 2025-09-07T07:46:34.0910933Z * [new tag] trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e 2025-09-07T07:46:34.0911334Z * [new tag] trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d 2025-09-07T07:46:34.0911720Z * [new tag] trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 2025-09-07T07:46:34.0912118Z * [new tag] trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e 2025-09-07T07:46:34.0912495Z * [new tag] trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 2025-09-07T07:46:34.0912878Z * [new tag] trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 2025-09-07T07:46:34.0913263Z * [new tag] trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 2025-09-07T07:46:34.0913639Z * [new tag] trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462 2025-09-07T07:46:34.0914031Z * [new tag] trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 2025-09-07T07:46:34.0914508Z * [new tag] trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285 2025-09-07T07:46:34.0914899Z * [new tag] trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643 2025-09-07T07:46:34.0915291Z * [new tag] trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 2025-09-07T07:46:34.0915667Z * [new tag] trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661 2025-09-07T07:46:34.0916068Z * [new tag] trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab 2025-09-07T07:46:34.0916470Z * [new tag] trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 2025-09-07T07:46:34.0916887Z * [new tag] trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 2025-09-07T07:46:34.0917268Z * [new tag] trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061 2025-09-07T07:46:34.0917660Z * [new tag] trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a 2025-09-07T07:46:34.0918045Z * [new tag] trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 2025-09-07T07:46:34.0918455Z * [new tag] trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d 2025-09-07T07:46:34.0918833Z * [new tag] trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717 2025-09-07T07:46:34.0919301Z * [new tag] trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 2025-09-07T07:46:34.0919703Z * [new tag] trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 2025-09-07T07:46:34.0920085Z * [new tag] trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439 2025-09-07T07:46:34.0920573Z * [new tag] trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 2025-09-07T07:46:34.0920961Z * [new tag] trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 2025-09-07T07:46:34.0921364Z * [new tag] trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 2025-09-07T07:46:34.0921735Z * [new tag] trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b 2025-09-07T07:46:34.0922117Z * [new tag] trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090 2025-09-07T07:46:34.0922521Z * [new tag] trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087 2025-09-07T07:46:34.0923136Z * [new tag] trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 2025-09-07T07:46:34.0923536Z * [new tag] trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de 2025-09-07T07:46:34.0923926Z * [new tag] trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 2025-09-07T07:46:34.0924333Z * [new tag] trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 2025-09-07T07:46:34.0924725Z * [new tag] trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b 2025-09-07T07:46:34.0925215Z * [new tag] trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37 2025-09-07T07:46:34.0925598Z * [new tag] trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 2025-09-07T07:46:34.0925973Z * [new tag] trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd 2025-09-07T07:46:34.0926370Z * [new tag] trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb 2025-09-07T07:46:34.0926763Z * [new tag] trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c 2025-09-07T07:46:34.0927154Z * [new tag] trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8 2025-09-07T07:46:34.0927542Z * [new tag] trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c 2025-09-07T07:46:34.0927936Z * [new tag] trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c 2025-09-07T07:46:34.0928316Z * [new tag] trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 2025-09-07T07:46:34.0928725Z * [new tag] trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 2025-09-07T07:46:34.0929109Z * [new tag] trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa 2025-09-07T07:46:34.0929494Z * [new tag] trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab 2025-09-07T07:46:34.0929976Z * [new tag] trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd 2025-09-07T07:46:34.0930118Z * [new tag] v0.1.1 -> v0.1.1 2025-09-07T07:46:34.0930271Z * [new tag] v0.1.10 -> v0.1.10 2025-09-07T07:46:34.0930404Z * [new tag] v0.1.11 -> v0.1.11 2025-09-07T07:46:34.0930535Z * [new tag] v0.1.12 -> v0.1.12 2025-09-07T07:46:34.0930681Z * [new tag] v0.1.2 -> v0.1.2 2025-09-07T07:46:34.0930814Z * [new tag] v0.1.3 -> v0.1.3 2025-09-07T07:46:34.0930953Z * [new tag] v0.1.4 -> v0.1.4 2025-09-07T07:46:34.0931083Z * [new tag] v0.1.5 -> v0.1.5 2025-09-07T07:46:34.0931223Z * [new tag] v0.1.6 -> v0.1.6 2025-09-07T07:46:34.0931357Z * [new tag] v0.1.7 -> v0.1.7 2025-09-07T07:46:34.0931488Z * [new tag] v0.1.8 -> v0.1.8 2025-09-07T07:46:34.0931630Z * [new tag] v0.1.9 -> v0.1.9 2025-09-07T07:46:34.0931758Z * [new tag] v0.2.0 -> v0.2.0 2025-09-07T07:46:34.0931901Z * [new tag] v0.3.0 -> v0.3.0 2025-09-07T07:46:34.0932031Z * [new tag] v0.3.1 -> v0.3.1 2025-09-07T07:46:34.0932161Z * [new tag] v0.4.0 -> v0.4.0 2025-09-07T07:46:34.0932301Z * [new tag] v0.4.1 -> v0.4.1 2025-09-07T07:46:34.0932433Z * [new tag] v1.0.0 -> v1.0.0 2025-09-07T07:46:34.0932590Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-09-07T07:46:34.0932722Z * [new tag] v1.0.1 -> v1.0.1 2025-09-07T07:46:34.0932865Z * [new tag] v1.0rc0 -> v1.0rc0 2025-09-07T07:46:34.0933014Z * [new tag] v1.0rc1 -> v1.0rc1 2025-09-07T07:46:34.0933227Z * [new tag] v1.1.0 -> v1.1.0 2025-09-07T07:46:34.0933381Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-09-07T07:46:34.0933515Z * [new tag] v1.10.0 -> v1.10.0 2025-09-07T07:46:34.0933671Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-09-07T07:46:34.0933816Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-09-07T07:46:34.0933960Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-09-07T07:46:34.0934109Z * [new tag] v1.10.1 -> v1.10.1 2025-09-07T07:46:34.0934250Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-09-07T07:46:34.0934400Z * [new tag] v1.10.2 -> v1.10.2 2025-09-07T07:46:34.0934542Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-09-07T07:46:34.0934678Z * [new tag] v1.11.0 -> v1.11.0 2025-09-07T07:46:34.0934830Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-09-07T07:46:34.0934970Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-09-07T07:46:34.0935123Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-09-07T07:46:34.0935264Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-09-07T07:46:34.0935405Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-09-07T07:46:34.0935559Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-09-07T07:46:34.0935701Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-09-07T07:46:34.0935842Z * [new tag] v1.12.0 -> v1.12.0 2025-09-07T07:46:34.0936093Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-09-07T07:46:34.0936238Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-09-07T07:46:34.0936392Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-09-07T07:46:34.0936532Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-09-07T07:46:34.0936683Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-09-07T07:46:34.0936822Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-09-07T07:46:34.0936973Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-09-07T07:46:34.0937115Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-09-07T07:46:34.0937251Z * [new tag] v1.12.1 -> v1.12.1 2025-09-07T07:46:34.0937473Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-09-07T07:46:34.0937621Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-09-07T07:46:34.0937772Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-09-07T07:46:34.0937917Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-09-07T07:46:34.0938058Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-09-07T07:46:34.0938203Z * [new tag] v1.13.0 -> v1.13.0 2025-09-07T07:46:34.0938347Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-09-07T07:46:34.0938499Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-09-07T07:46:34.0938641Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-09-07T07:46:34.0938783Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-09-07T07:46:34.0938939Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-09-07T07:46:34.0939084Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-09-07T07:46:34.0939232Z * [new tag] v1.13.1 -> v1.13.1 2025-09-07T07:46:34.0939460Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-09-07T07:46:34.0939612Z * [new tag] v1.2.0 -> v1.2.0 2025-09-07T07:46:34.0939752Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-09-07T07:46:34.0939886Z * [new tag] v1.3.0 -> v1.3.0 2025-09-07T07:46:34.0940033Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-09-07T07:46:34.0940166Z * [new tag] v1.3.1 -> v1.3.1 2025-09-07T07:46:34.0940311Z * [new tag] v1.4.0 -> v1.4.0 2025-09-07T07:46:34.0940448Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-09-07T07:46:34.0940578Z * [new tag] v1.4.1 -> v1.4.1 2025-09-07T07:46:34.0940727Z * [new tag] v1.5.0 -> v1.5.0 2025-09-07T07:46:34.0940876Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-09-07T07:46:34.0941032Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-09-07T07:46:34.0941174Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-09-07T07:46:34.0941314Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-09-07T07:46:34.0941464Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-09-07T07:46:34.0941597Z * [new tag] v1.5.1 -> v1.5.1 2025-09-07T07:46:34.0941751Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-09-07T07:46:34.0941883Z * [new tag] v1.6.0 -> v1.6.0 2025-09-07T07:46:34.0942034Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-09-07T07:46:34.0942255Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-09-07T07:46:34.0942394Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-09-07T07:46:34.0942549Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-09-07T07:46:34.0942687Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-09-07T07:46:34.0942838Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-09-07T07:46:34.0942979Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-09-07T07:46:34.0943114Z * [new tag] v1.7.0 -> v1.7.0 2025-09-07T07:46:34.0943262Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-09-07T07:46:34.0943403Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-09-07T07:46:34.0943553Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-09-07T07:46:34.0943697Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-09-07T07:46:34.0943831Z * [new tag] v1.7.1 -> v1.7.1 2025-09-07T07:46:34.0943987Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-09-07T07:46:34.0944126Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-09-07T07:46:34.0944300Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-09-07T07:46:34.0944435Z * [new tag] v1.8.0 -> v1.8.0 2025-09-07T07:46:34.0944587Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-09-07T07:46:34.0944743Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-09-07T07:46:34.0944881Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-09-07T07:46:34.0945027Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-09-07T07:46:34.0945165Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-09-07T07:46:34.0945314Z * [new tag] v1.8.1 -> v1.8.1 2025-09-07T07:46:34.0945533Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-09-07T07:46:34.0945673Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-09-07T07:46:34.0945817Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-09-07T07:46:34.0945949Z * [new tag] v1.8.2 -> v1.8.2 2025-09-07T07:46:34.0946095Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-09-07T07:46:34.0946228Z * [new tag] v1.9.0 -> v1.9.0 2025-09-07T07:46:34.0946368Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-09-07T07:46:34.0946513Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-09-07T07:46:34.0946650Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-09-07T07:46:34.0946801Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-09-07T07:46:34.0946932Z * [new tag] v1.9.1 -> v1.9.1 2025-09-07T07:46:34.0947086Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-09-07T07:46:34.0947222Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-09-07T07:46:34.0947354Z * [new tag] v2.0.0 -> v2.0.0 2025-09-07T07:46:34.0947503Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-09-07T07:46:34.0947643Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-09-07T07:46:34.0947791Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-09-07T07:46:34.0947930Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-09-07T07:46:34.0948066Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-09-07T07:46:34.0948301Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-09-07T07:46:34.0948434Z * [new tag] v2.0.1 -> v2.0.1 2025-09-07T07:46:34.0948586Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-09-07T07:46:34.0948724Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-09-07T07:46:34.0948861Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-09-07T07:46:34.0949008Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-09-07T07:46:34.0949140Z * [new tag] v2.1.0 -> v2.1.0 2025-09-07T07:46:34.0949290Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-09-07T07:46:34.0949426Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-09-07T07:46:34.0949573Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-09-07T07:46:34.0949710Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-09-07T07:46:34.0949851Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-09-07T07:46:34.0950004Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-09-07T07:46:34.0950135Z * [new tag] v2.1.1 -> v2.1.1 2025-09-07T07:46:34.0950278Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-09-07T07:46:34.0950413Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-09-07T07:46:34.0950551Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-09-07T07:46:34.0950699Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-09-07T07:46:34.0950836Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-09-07T07:46:34.0950985Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-09-07T07:46:34.0951117Z * [new tag] v2.1.2 -> v2.1.2 2025-09-07T07:46:34.0951259Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-09-07T07:46:34.0951407Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-09-07T07:46:34.0951628Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-09-07T07:46:34.0951774Z * [new tag] v2.2.0 -> v2.2.0 2025-09-07T07:46:34.0951910Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-09-07T07:46:34.0952049Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-09-07T07:46:34.0952194Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-09-07T07:46:34.0952334Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-09-07T07:46:34.0952485Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-09-07T07:46:34.0952623Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-09-07T07:46:34.0952777Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-09-07T07:46:34.0952914Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-09-07T07:46:34.0953050Z * [new tag] v2.2.1 -> v2.2.1 2025-09-07T07:46:34.0953203Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-09-07T07:46:34.0953341Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-09-07T07:46:34.0953489Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-09-07T07:46:34.0953620Z * [new tag] v2.2.2 -> v2.2.2 2025-09-07T07:46:34.0953757Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-09-07T07:46:34.0953901Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-09-07T07:46:34.0954037Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-09-07T07:46:34.0954256Z * [new tag] v2.3.0 -> v2.3.0 2025-09-07T07:46:34.0954392Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-09-07T07:46:34.0954538Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-09-07T07:46:34.0954687Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-09-07T07:46:34.0954826Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-09-07T07:46:34.0954976Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-09-07T07:46:34.0955113Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-09-07T07:46:34.0955262Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-09-07T07:46:34.0955399Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-09-07T07:46:34.0955536Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-09-07T07:46:34.0955678Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-09-07T07:46:34.0955823Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-09-07T07:46:34.0955969Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-09-07T07:46:34.0956103Z * [new tag] v2.3.1 -> v2.3.1 2025-09-07T07:46:34.0956242Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-09-07T07:46:34.0956387Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-09-07T07:46:34.0956526Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-09-07T07:46:34.0956667Z * [new tag] v2.4.0 -> v2.4.0 2025-09-07T07:46:34.0956802Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-09-07T07:46:34.0956936Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-09-07T07:46:34.0957084Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-09-07T07:46:34.0957223Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-09-07T07:46:34.0957371Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-09-07T07:46:34.0957599Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-09-07T07:46:34.0957751Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-09-07T07:46:34.0957891Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-09-07T07:46:34.0958027Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-09-07T07:46:34.0958168Z * [new tag] v2.4.1 -> v2.4.1 2025-09-07T07:46:34.0958305Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-09-07T07:46:34.0958456Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-09-07T07:46:34.0958594Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-09-07T07:46:34.0958731Z * [new tag] v2.5.0 -> v2.5.0 2025-09-07T07:46:34.0958877Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-09-07T07:46:34.0959020Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-09-07T07:46:34.0959170Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-09-07T07:46:34.0959310Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-09-07T07:46:34.0959447Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-09-07T07:46:34.0959596Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-09-07T07:46:34.0959736Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-09-07T07:46:34.0959887Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-09-07T07:46:34.0960027Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-09-07T07:46:34.0960178Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-09-07T07:46:34.0960388Z * [new tag] v2.5.1 -> v2.5.1 2025-09-07T07:46:34.0960530Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-09-07T07:46:34.0960673Z * [new tag] v2.6.0 -> v2.6.0 2025-09-07T07:46:34.0960815Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-09-07T07:46:34.0960962Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-09-07T07:46:34.0961097Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-09-07T07:46:34.0961234Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-09-07T07:46:34.0961384Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-09-07T07:46:34.0961526Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-09-07T07:46:34.0961683Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-09-07T07:46:34.0961824Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-09-07T07:46:34.0961962Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-09-07T07:46:34.0962105Z * [new tag] v2.7.0 -> v2.7.0 2025-09-07T07:46:34.0962240Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-09-07T07:46:34.0962391Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-09-07T07:46:34.0962530Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-09-07T07:46:34.0962676Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-09-07T07:46:34.0962813Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-09-07T07:46:34.0963086Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-09-07T07:46:34.0963234Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-09-07T07:46:34.0963374Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-09-07T07:46:34.0963521Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-09-07T07:46:34.0963754Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-09-07T07:46:34.0963887Z * [new tag] v2.7.1 -> v2.7.1 2025-09-07T07:46:34.0964032Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-09-07T07:46:34.0964167Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-09-07T07:46:34.0964316Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-09-07T07:46:34.0964455Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-09-07T07:46:34.0964593Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-09-07T07:46:34.0964734Z * [new tag] v2.8.0 -> v2.8.0 2025-09-07T07:46:34.0964870Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-09-07T07:46:34.0965024Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-09-07T07:46:34.0965164Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-09-07T07:46:34.0965311Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-09-07T07:46:34.0965449Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-09-07T07:46:34.0965586Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-09-07T07:46:34.0965734Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-09-07T07:46:34.0965871Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-09-07T07:46:34.0966032Z * [new tag] whc_flight_1 -> whc_flight_1 2025-09-07T07:46:34.0966183Z * [new tag] whc_flight_2 -> whc_flight_2 2025-09-07T07:46:34.0966328Z * [new tag] whc_flight_4 -> whc_flight_4 2025-09-07T07:46:36.4371186Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:46:36.4396989Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:36.4400584Z ##[endgroup] 2025-09-07T07:46:36.4401016Z ##[group]Determining the checkout info 2025-09-07T07:46:36.4401977Z ##[endgroup] 2025-09-07T07:46:36.4405905Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:46:36.4446839Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:46:36.4470825Z ##[group]Checking out the ref 2025-09-07T07:46:36.4474260Z [command]/usr/bin/git checkout --progress 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You can look around, make experimental 2025-09-07T07:46:40.2856999Z changes and commit them, and you can discard any commits you make in this 2025-09-07T07:46:40.2857658Z state without impacting any branches by switching back to a branch. 2025-09-07T07:46:40.2857998Z 2025-09-07T07:46:40.2858207Z If you want to create a new branch to retain commits you create, you may 2025-09-07T07:46:40.2858723Z do so (now or later) by using -c with the switch command. Example: 2025-09-07T07:46:40.2859017Z 2025-09-07T07:46:40.2859143Z git switch -c 2025-09-07T07:46:40.2859341Z 2025-09-07T07:46:40.2859446Z Or undo this operation with: 2025-09-07T07:46:40.2859636Z 2025-09-07T07:46:40.2859722Z git switch - 2025-09-07T07:46:40.2859885Z 2025-09-07T07:46:40.2860124Z Turn off this advice by setting config variable advice.detachedHead to false 2025-09-07T07:46:40.2860501Z 2025-09-07T07:46:40.2860680Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:46:40.2965197Z ##[endgroup] 2025-09-07T07:46:40.2965651Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:46:40.2970751Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:46:40.3009452Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:46:40.3037535Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:46:40.3064884Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:46:40.3088781Z ##[endgroup] 2025-09-07T07:46:40.3089186Z ##[group]Fetching submodules 2025-09-07T07:46:40.3092483Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:46:40.3344627Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:46:40.3607588Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-09-07T07:46:40.3617430Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-09-07T07:46:40.3630091Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-09-07T07:46:40.3640759Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-09-07T07:46:40.3653505Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-09-07T07:46:40.3665361Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-09-07T07:46:40.3677142Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-09-07T07:46:40.3687712Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-09-07T07:46:40.3699282Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-09-07T07:46:40.3710727Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-09-07T07:46:40.3721893Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-09-07T07:46:40.3732882Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-09-07T07:46:40.3743865Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-09-07T07:46:40.3755142Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-09-07T07:46:40.3767232Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-09-07T07:46:40.3778726Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-09-07T07:46:40.3789966Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-09-07T07:46:40.3800901Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-09-07T07:46:40.3812378Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:46:40.3823152Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-09-07T07:46:40.3835186Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-09-07T07:46:40.3846392Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-09-07T07:46:40.3857827Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-09-07T07:46:40.3869109Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-09-07T07:46:40.3880289Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-09-07T07:46:40.3891332Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-09-07T07:46:40.3903022Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-09-07T07:46:40.3914174Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-09-07T07:46:40.3925451Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-09-07T07:46:40.3937273Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-09-07T07:46:40.3949395Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-09-07T07:46:40.3960163Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-09-07T07:46:40.3972341Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-09-07T07:46:40.3983699Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-09-07T07:46:40.3995389Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-09-07T07:46:40.4007703Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-09-07T07:46:40.4019633Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-09-07T07:46:40.4052671Z Cloning into '/home/frank/_work/pytorch/pytorch/android/libs/fbjni'... 2025-09-07T07:46:40.6497715Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/FP16'... 2025-09-07T07:46:40.8709834Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/FXdiv'... 2025-09-07T07:46:41.0809975Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/NNPACK'... 2025-09-07T07:46:41.3270174Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/NVTX'... 2025-09-07T07:46:41.7561560Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-09-07T07:46:43.1495246Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-09-07T07:47:01.3336929Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/aiter'... 2025-09-07T07:47:09.2467779Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/benchmark'... 2025-09-07T07:47:10.0227840Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-09-07T07:47:15.5933737Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-09-07T07:47:16.5157463Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-09-07T07:47:17.4550549Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-09-07T07:47:19.8326975Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/cutlass'... 2025-09-07T07:47:21.9945673Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm'... 2025-09-07T07:47:24.0466070Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/flash-attention'... 2025-09-07T07:47:24.6659614Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-09-07T07:47:26.0250553Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fmt'... 2025-09-07T07:47:27.9131924Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-09-07T07:47:28.4942439Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/gloo'... 2025-09-07T07:47:28.8613415Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/googletest'... 2025-09-07T07:47:29.8510355Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/ideep'... 2025-09-07T07:47:30.1929858Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/ittapi'... 2025-09-07T07:47:30.6286986Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto'... 2025-09-07T07:47:33.0706693Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kleidiai'... 2025-09-07T07:47:33.5428289Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/mimalloc'... 2025-09-07T07:47:34.4661158Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/nlohmann'... 2025-09-07T07:47:45.2633513Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/onnx'... 2025-09-07T07:47:48.8688978Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-09-07T07:47:56.9333829Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/pocketfft'... 2025-09-07T07:47:57.1864304Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/protobuf'... 2025-09-07T07:48:08.9294801Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/psimd'... 2025-09-07T07:48:09.9907595Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-09-07T07:48:11.0182503Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/pybind11'... 2025-09-07T07:48:12.1355194Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-09-07T07:48:12.4421355Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/sleef'... 2025-09-07T07:48:13.2897548Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-09-07T07:48:13.7091183Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:48:13.7215523Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:48:13.7310784Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:48:13.7552531Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:48:13.8436243Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:48:13.9016696Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:48:14.6223471Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:48:14.7819891Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:48:14.7850908Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:48:14.7878913Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-09-07T07:48:18.3909929Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:48:18.4948185Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:48:18.8716487Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:48:19.0258271Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:48:19.3117288Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:48:19.4574644Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:48:20.3313973Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:48:20.4804892Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:48:20.4836361Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-09-07T07:48:20.4845065Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:48:20.4854227Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:48:20.4864168Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-09-07T07:48:20.4873558Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-09-07T07:48:20.4883447Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:48:20.4892945Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-09-07T07:48:20.4920337Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-09-07T07:48:21.6249796Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-09-07T07:48:22.6315298Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-09-07T07:48:24.1988270Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-09-07T07:48:27.6043333Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-09-07T07:48:29.0771254Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-09-07T07:48:29.6844723Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-09-07T07:48:43.9791099Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:48:44.4154619Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:48:44.5682379Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:48:45.6473036Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:48:45.7171828Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:45.7529320Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:48:45.8855683Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:48:45.9894282Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:48:46.0215415Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:48:46.0719166Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:48:46.0745639Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-09-07T07:48:52.0443746Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-09-07T07:48:57.2137866Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:48:57.8054397Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:48:58.2557307Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:48:58.3214328Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:48:58.3821343Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:48:58.4480593Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:48:58.5185496Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:58.5606687Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:48:58.7089345Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-09-07T07:48:58.7114335Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-09-07T07:49:19.4333533Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:49:19.4769682Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:49:19.5883226Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:49:19.6101935Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:49:19.6479678Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:49:19.6686983Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:49:19.6714727Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-09-07T07:49:20.8249046Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-09-07T07:49:22.6466156Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-09-07T07:49:24.7038358Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:49:24.8892756Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:49:24.9307065Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:49:25.0312948Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:49:25.0773516Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:49:25.2406283Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:49:25.2799177Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:49:25.3113994Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:49:25.3435396Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:49:25.3468150Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-09-07T07:49:28.1143657Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-09-07T07:49:29.4501285Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-09-07T07:49:32.0701769Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-09-07T07:49:32.7917985Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-09-07T07:49:33.8119001Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-09-07T07:49:35.6545432Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-09-07T07:49:52.3719353Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-09-07T07:49:53.9466247Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:49:54.0258065Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:49:54.1734010Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:49:54.2145557Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:49:54.2405265Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:49:54.2434488Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-09-07T07:49:55.3678357Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:49:55.4147786Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:49:55.4778476Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:49:55.7943570Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:49:55.9048528Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:49:56.1875834Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:49:56.2637081Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:49:56.3206184Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:49:56.3695545Z Submodule path 'third_party/mimalloc': checked out 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'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:49:59.2048673Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:49:59.2194378Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:49:59.2366727Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:49:59.2486145Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:49:59.2611889Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:49:59.2793352Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:49:59.3010227Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:49:59.3037728Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-09-07T07:50:00.0478542Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-09-07T07:50:02.0035378Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-09-07T07:50:02.6129035Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-09-07T07:50:17.0623944Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-09-07T07:50:17.7171042Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-09-07T07:50:18.2608975Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-09-07T07:50:18.8581361Z Cloning into '/home/frank/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-09-07T07:50:28.5150572Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:50:28.5745325Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:50:28.6143602Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:50:28.7450066Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:50:28.7666212Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:50:28.7979512Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:50:28.8341510Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:50:28.8546937Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:28.9648929Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 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file:/home/frank/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:50:40.6866470Z Entering 'third_party/FP16' 2025-09-07T07:50:40.6907099Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:50:40.6925092Z Entering 'third_party/FXdiv' 2025-09-07T07:50:40.6963075Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:50:40.6981912Z Entering 'third_party/NNPACK' 2025-09-07T07:50:40.7020853Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:50:40.7038850Z Entering 'third_party/NVTX' 2025-09-07T07:50:40.7076483Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:50:40.7096321Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:40.7133925Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:50:40.7152257Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:40.7192176Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:50:40.7226901Z Entering 'third_party/aiter' 2025-09-07T07:50:40.7264406Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:50:40.7283589Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:40.7321283Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:50:40.7348663Z Entering 'third_party/benchmark' 2025-09-07T07:50:40.7386512Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:40.7405727Z Entering 'third_party/composable_kernel' 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2025-09-07T07:50:41.9160819Z submodules: recursive 2025-09-07T07:50:41.9161088Z show-progress: false 2025-09-07T07:50:41.9161372Z repository: pytorch/pytorch 2025-09-07T07:50:41.9161789Z token: *** 2025-09-07T07:50:41.9162017Z ssh-strict: true 2025-09-07T07:50:41.9162254Z ssh-user: git 2025-09-07T07:50:41.9162501Z persist-credentials: true 2025-09-07T07:50:41.9162764Z clean: true 2025-09-07T07:50:41.9163873Z sparse-checkout-cone-mode: true 2025-09-07T07:50:41.9164181Z fetch-tags: false 2025-09-07T07:50:41.9164421Z lfs: false 2025-09-07T07:50:41.9164653Z set-safe-directory: true 2025-09-07T07:50:41.9164919Z env: 2025-09-07T07:50:41.9165139Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:41.9165404Z ##[endgroup] 2025-09-07T07:50:42.0124147Z Syncing repository: pytorch/pytorch 2025-09-07T07:50:42.0126996Z ##[group]Getting Git version info 2025-09-07T07:50:42.0127395Z Working directory is '/home/frank/_work/pytorch/pytorch' 2025-09-07T07:50:42.0159917Z [command]/usr/bin/git version 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2025-09-07T07:50:42.0635702Z 7e1e1fe3858c63c251c637ae41a20de425dde96f android/libs/fbjni (v0.1.0-12-g7e1e1fe) 2025-09-07T07:50:42.0713605Z 4dfe081cf6bcd15db339cf2680b9281b8451eeb3 third_party/FP16 (4dfe081) 2025-09-07T07:50:42.0791318Z b408327ac2a15ec3e43352421954f5b1967701d1 third_party/FXdiv (b408327) 2025-09-07T07:50:42.0885281Z c07e3a0400713d546e0dea2d5466dd22ea389c73 third_party/NNPACK (c07e3a0) 2025-09-07T07:50:42.0940764Z 2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07 third_party/NVTX (v3.1.0-263-g2942f16) 2025-09-07T07:50:42.1032570Z 1d8f600fd424278486eade7ed3e877c99f0846b1 third_party/VulkanMemoryAllocator (v2.1.0-982-g1d8f600) 2025-09-07T07:50:42.1557189Z 51a0103656eff6fc9bfd39a4597923c4b542c883 third_party/XNNPACK (remotes/origin/ds/ndk-1243-g51a0103656) 2025-09-07T07:50:42.1598528Z 01aae101b9e5e94d6c16a9514c9fb8df99c93150 third_party/aiter (v0.1.1-92-g01aae101) 2025-09-07T07:50:42.1625954Z 299e5928955cc62af9968370293b916f5130916f third_party/benchmark (v1.9.3) 2025-09-07T07:50:42.1886024Z 7fe50dc3da2069d6645d9deb8c017a876472a977 third_party/composable_kernel (rocm-6.4.3-459-g7fe50dc3d) 2025-09-07T07:50:42.2031601Z 89c932f313c6437c38f2982869beacc89c2f2246 third_party/cpp-httplib (v0.26.0) 2025-09-07T07:50:42.2156756Z 5e3d2445e6a84d9599bee2bf78edbb4d80865e1d third_party/cpuinfo (5e3d244) 2025-09-07T07:50:42.2198201Z f937055efc6d414d11f4c6577e3977fe74f35fb6 third_party/cudnn_frontend (v0.5-52-gf937055) 2025-09-07T07:50:42.2300359Z e51efbfe18fe4f4cbb66ab814c55bf4aa0185491 third_party/cutlass (v4.1.0) 2025-09-07T07:50:42.2363766Z 4b39c551efe15e6bbade20565b0ceb2d8ce3352d third_party/fbgemm (v1.3.0-rc1-342-g4b39c551) 2025-09-07T07:50:42.2458195Z 979702c87a8713a8e0a5e9fee122b90d2ef13be5 third_party/flash-attention (v2.7.4) 2025-09-07T07:50:42.2485565Z a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757 third_party/flatbuffers (v24.12.23) 2025-09-07T07:50:42.2919600Z 40626af88bd7df9a5fb80be7b25ac85b122d6c21 third_party/fmt (11.2.0) 2025-09-07T07:50:42.3033748Z 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third_party/nlohmann (v3.12.0) 2025-09-07T07:50:42.4276213Z e709452ef2bbc1d113faf678c24e6d3467696e83 third_party/onnx (v1.18.0) 2025-09-07T07:50:42.4304588Z a799f4aed9c94b765dcdaabaeab7d5e7e2310878 third_party/opentelemetry-cpp (v1.14.2) 2025-09-07T07:50:42.4334869Z 0fa0ef591e38c2758e3184c6c23e497b9f732ffa third_party/pocketfft (release_for_eigen-40-g0fa0ef5) 2025-09-07T07:50:42.4709740Z d1eca4e4b421cd2997495c4b4e65cea6be4e9b8a third_party/protobuf (v3.7.0-rc.2-1279-gd1eca4e4b) 2025-09-07T07:50:42.4789451Z 072586a71b55b7f8c584153d223e95687148a900 third_party/psimd (heads/master) 2025-09-07T07:50:42.4850119Z 4fe0e1e183925bf8cfa6aae24237e724a96479b8 third_party/pthreadpool (0.1-144-g4fe0e1e) 2025-09-07T07:50:42.4877289Z f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8 third_party/pybind11 (v3.0.1) 2025-09-07T07:50:42.4956084Z f45429b087dd7d5bc78bb40dc7cf06425c252d67 third_party/python-peachpy (remotes/origin/pre-generated) 2025-09-07T07:50:42.5038541Z 5a1d179df9cf652951b59010a2d2075372d67f68 third_party/sleef (3.8) 2025-09-07T07:50:42.5111603Z af0118d13e52f5a08841464a768e01a0bf3e3075 third_party/tensorpipe (heads/main) 2025-09-07T07:50:42.5123263Z ##[group]Cleaning the repository 2025-09-07T07:50:42.5127745Z [command]/usr/bin/git clean -ffdx 2025-09-07T07:50:42.5439607Z [command]/usr/bin/git reset --hard HEAD 2025-09-07T07:50:42.9156344Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:50:42.9183470Z ##[endgroup] 2025-09-07T07:50:42.9186413Z ##[group]Disabling automatic garbage collection 2025-09-07T07:50:42.9195764Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:50:42.9233880Z ##[endgroup] 2025-09-07T07:50:42.9234261Z ##[group]Setting up auth 2025-09-07T07:50:42.9244239Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:50:42.9280139Z [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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Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:43.0918968Z Entering 'third_party/gloo' 2025-09-07T07:50:43.0964842Z Entering 'third_party/googletest' 2025-09-07T07:50:43.1010144Z Entering 'third_party/ideep' 2025-09-07T07:50:43.1053882Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:43.1104784Z Entering 'third_party/ittapi' 2025-09-07T07:50:43.1148739Z Entering 'third_party/kineto' 2025-09-07T07:50:43.1190725Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:43.1248725Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:43.1293412Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:43.1337285Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:43.1377900Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:43.1418509Z Entering 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2025-09-07T07:50:43.1970018Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:43.2023974Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:43.2058241Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:43.2100603Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:43.2144668Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:43.2191054Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:43.2233519Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:43.2276000Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:43.2318263Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:43.2362794Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:43.2407830Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:43.2478099Z Entering 'third_party/pocketfft' 2025-09-07T07:50:43.2523098Z Entering 'third_party/protobuf' 2025-09-07T07:50:43.2572903Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:43.2614492Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:43.2659520Z Entering 'third_party/psimd' 2025-09-07T07:50:43.2703023Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:43.2747553Z Entering 'third_party/pybind11' 2025-09-07T07:50:43.2792369Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:43.2838622Z Entering 'third_party/sleef' 2025-09-07T07:50:43.2883879Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:43.2928658Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:43.2972716Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:43.3017240Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:43.3060458Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:43.3101935Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:43.3171575Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T07:50:43.3198380Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3208751Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-09-07T07:50:43.3246662Z [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' || :" 2025-09-07T07:50:43.3491766Z Entering 'android/libs/fbjni' 2025-09-07T07:50:43.3518147Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3551511Z Entering 'third_party/FP16' 2025-09-07T07:50:43.3578328Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3610608Z Entering 'third_party/FXdiv' 2025-09-07T07:50:43.3634864Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3666981Z Entering 'third_party/NNPACK' 2025-09-07T07:50:43.3694099Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3728749Z Entering 'third_party/NVTX' 2025-09-07T07:50:43.3754855Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3787862Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:43.3813495Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3847206Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:43.3872834Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3920991Z Entering 'third_party/aiter' 2025-09-07T07:50:43.3948305Z http.https://github.com/.extraheader 2025-09-07T07:50:43.3983781Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:43.4009486Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4050651Z Entering 'third_party/benchmark' 2025-09-07T07:50:43.4075841Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4108197Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:43.4134485Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4180052Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:43.4208068Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4238744Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:43.4264388Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4296811Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:43.4321659Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4358184Z Entering 'third_party/cutlass' 2025-09-07T07:50:43.4384548Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4428040Z Entering 'third_party/fbgemm' 2025-09-07T07:50:43.4452866Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4487842Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:43.4511963Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4543679Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:43.4569016Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4608398Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:43.4635461Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4668425Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:43.4693343Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4735014Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:43.4761205Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4793076Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:43.4819407Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4849470Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:43.4874252Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4909688Z Entering 'third_party/flash-attention' 2025-09-07T07:50:43.4935467Z http.https://github.com/.extraheader 2025-09-07T07:50:43.4971970Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:43.4995611Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5037547Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:43.5062800Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5106121Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:43.5133448Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5168632Z Entering 'third_party/fmt' 2025-09-07T07:50:43.5194351Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5226838Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:43.5252769Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5290033Z Entering 'third_party/gloo' 2025-09-07T07:50:43.5315094Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5348152Z Entering 'third_party/googletest' 2025-09-07T07:50:43.5373661Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5408053Z Entering 'third_party/ideep' 2025-09-07T07:50:43.5433805Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5464765Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:43.5489136Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5530370Z Entering 'third_party/ittapi' 2025-09-07T07:50:43.5556238Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5587684Z Entering 'third_party/kineto' 2025-09-07T07:50:43.5615144Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5647301Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:43.5672326Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5704543Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:43.5732917Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5766849Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:43.5791812Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5824345Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:43.5849497Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5884639Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:43.5909135Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5940330Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:43.5965094Z http.https://github.com/.extraheader 2025-09-07T07:50:43.5999314Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:43.6025014Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6056858Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:43.6083828Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6115743Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:43.6141608Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6174949Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:43.6200242Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6234040Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:43.6258838Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6292214Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:43.6317635Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6351453Z Entering 'third_party/kleidiai' 2025-09-07T07:50:43.6378944Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6413679Z Entering 'third_party/mimalloc' 2025-09-07T07:50:43.6438574Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6474798Z Entering 'third_party/nlohmann' 2025-09-07T07:50:43.6508801Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6543135Z Entering 'third_party/onnx' 2025-09-07T07:50:43.6570205Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6625446Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:43.6652970Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6688575Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:43.6715036Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6749777Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:43.6775296Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6809129Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:43.6835945Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6867696Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:43.6893795Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6926699Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:43.6952464Z http.https://github.com/.extraheader 2025-09-07T07:50:43.6988054Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:43.7013828Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7047335Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:43.7072391Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7103908Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:43.7129401Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7165474Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:43.7190509Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7224984Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:43.7250746Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7286863Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:43.7312409Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7367036Z Entering 'third_party/pocketfft' 2025-09-07T07:50:43.7393410Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7427300Z Entering 'third_party/protobuf' 2025-09-07T07:50:43.7455744Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7493773Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:43.7518028Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7550299Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:43.7575845Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7610543Z Entering 'third_party/psimd' 2025-09-07T07:50:43.7638160Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7670947Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:43.7697058Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7730415Z Entering 'third_party/pybind11' 2025-09-07T07:50:43.7755739Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7790197Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:43.7816325Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7850895Z Entering 'third_party/sleef' 2025-09-07T07:50:43.7879109Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7911537Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:43.7939251Z http.https://github.com/.extraheader 2025-09-07T07:50:43.7971385Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:43.7995610Z http.https://github.com/.extraheader 2025-09-07T07:50:43.8027488Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:43.8056012Z http.https://github.com/.extraheader 2025-09-07T07:50:43.8088336Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:43.8113884Z http.https://github.com/.extraheader 2025-09-07T07:50:43.8145733Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:43.8171073Z http.https://github.com/.extraheader 2025-09-07T07:50:43.8204290Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:43.8227939Z http.https://github.com/.extraheader 2025-09-07T07:50:43.8288069Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:50:43.8712145Z ##[endgroup] 2025-09-07T07:50:43.8712576Z ##[group]Fetching the repository 2025-09-07T07:50:43.8727434Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:50:44.3730326Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:50:44.3756910Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:44.3761530Z ##[endgroup] 2025-09-07T07:50:44.3761946Z ##[group]Determining the checkout info 2025-09-07T07:50:44.3762756Z ##[endgroup] 2025-09-07T07:50:44.3766890Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:50:44.3984978Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:50:44.4017251Z ##[group]Checking out the ref 2025-09-07T07:50:44.4022880Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:44.4479683Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:50:44.4486256Z ##[endgroup] 2025-09-07T07:50:44.4486698Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:50:44.4491600Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:50:44.4531174Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:50:44.4560757Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:50:44.4592146Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:50:44.4618983Z ##[endgroup] 2025-09-07T07:50:44.4619446Z ##[group]Fetching submodules 2025-09-07T07:50:44.4624237Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:50:44.4878244Z Synchronizing submodule url for 'android/libs/fbjni' 2025-09-07T07:50:44.4901815Z Synchronizing submodule url for 'third_party/FP16' 2025-09-07T07:50:44.4925225Z Synchronizing submodule url for 'third_party/FXdiv' 2025-09-07T07:50:44.4948755Z Synchronizing submodule url for 'third_party/NNPACK' 2025-09-07T07:50:44.4973339Z Synchronizing submodule url for 'third_party/NVTX' 2025-09-07T07:50:44.4999617Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:44.5020013Z Synchronizing submodule url for 'third_party/XNNPACK' 2025-09-07T07:50:44.5060528Z Synchronizing submodule url for 'third_party/aiter' 2025-09-07T07:50:44.5084346Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:44.5117292Z Synchronizing submodule url for 'third_party/benchmark' 2025-09-07T07:50:44.5140794Z Synchronizing submodule url for 'third_party/composable_kernel' 2025-09-07T07:50:44.5175058Z Synchronizing submodule url for 'third_party/cpp-httplib' 2025-09-07T07:50:44.5198134Z Synchronizing submodule url for 'third_party/cpuinfo' 2025-09-07T07:50:44.5222814Z Synchronizing submodule url for 'third_party/cudnn_frontend' 2025-09-07T07:50:44.5246456Z Synchronizing submodule url for 'third_party/cutlass' 2025-09-07T07:50:44.5280357Z Synchronizing submodule url for 'third_party/fbgemm' 2025-09-07T07:50:44.5303949Z Synchronizing submodule url for 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:44.5324049Z Synchronizing submodule url for 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:44.5352323Z Synchronizing submodule url for 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:44.5374351Z Synchronizing submodule url for 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:44.5404099Z Synchronizing submodule url for 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:44.5427754Z Synchronizing submodule url for 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:44.5448687Z Synchronizing submodule url for 'third_party/fbgemm/external/json' 2025-09-07T07:50:44.5475197Z Synchronizing submodule url for 'third_party/flash-attention' 2025-09-07T07:50:44.5497374Z Synchronizing submodule url for 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:44.5523224Z Synchronizing submodule url for 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:44.5557738Z Synchronizing submodule url for 'third_party/flatbuffers' 2025-09-07T07:50:44.5584580Z Synchronizing submodule url for 'third_party/fmt' 2025-09-07T07:50:44.5607505Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:44.5632172Z Synchronizing submodule url for 'third_party/gloo' 2025-09-07T07:50:44.5655718Z Synchronizing submodule url for 'third_party/googletest' 2025-09-07T07:50:44.5681030Z Synchronizing submodule url for 'third_party/ideep' 2025-09-07T07:50:44.5699877Z Synchronizing submodule url for 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:44.5730846Z Synchronizing submodule url for 'third_party/ittapi' 2025-09-07T07:50:44.5754409Z Synchronizing submodule url for 'third_party/kineto' 2025-09-07T07:50:44.5775726Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:44.5795846Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:44.5818872Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:44.5839715Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:44.5862645Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:44.5884300Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:44.5906988Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:44.5928318Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:44.5949029Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:44.5972163Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:44.5997102Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:44.6019493Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:44.6043654Z Synchronizing submodule url for 'third_party/kleidiai' 2025-09-07T07:50:44.6068557Z Synchronizing submodule url for 'third_party/mimalloc' 2025-09-07T07:50:44.6091659Z Synchronizing submodule url for 'third_party/nlohmann' 2025-09-07T07:50:44.6117342Z Synchronizing submodule url for 'third_party/onnx' 2025-09-07T07:50:44.6159505Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:44.6185846Z Synchronizing submodule url for 'third_party/opentelemetry-cpp' 2025-09-07T07:50:44.6210336Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:44.6231402Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:44.6253480Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:44.6274352Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:44.6297581Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:44.6319770Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:44.6340387Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:44.6361648Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:44.6384333Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:44.6407538Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:44.6452074Z Synchronizing submodule url for 'third_party/pocketfft' 2025-09-07T07:50:44.6475250Z Synchronizing submodule url for 'third_party/protobuf' 2025-09-07T07:50:44.6505151Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:44.6525116Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:44.6549904Z Synchronizing submodule url for 'third_party/psimd' 2025-09-07T07:50:44.6572946Z Synchronizing submodule url for 'third_party/pthreadpool' 2025-09-07T07:50:44.6595521Z Synchronizing submodule url for 'third_party/pybind11' 2025-09-07T07:50:44.6619132Z Synchronizing submodule url for 'third_party/python-peachpy' 2025-09-07T07:50:44.6644317Z Synchronizing submodule url for 'third_party/sleef' 2025-09-07T07:50:44.6667338Z Synchronizing submodule url for 'third_party/tensorpipe' 2025-09-07T07:50:44.6692812Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:44.6712286Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:44.6733793Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:44.6756594Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:44.6777494Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:44.6812632Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:50:44.7207850Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:50:44.7343036Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:50:44.7438127Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:50:44.7680332Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:50:44.8660255Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:50:44.9056688Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:50:46.0326532Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:50:46.2997424Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:50:46.6215365Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:50:46.6430304Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:50:47.0111372Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:50:47.1270042Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:50:47.2735537Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:50:47.3701987Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:50:47.7779263Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:50:47.9252789Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:50:48.0006491Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:50:48.3123542Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:50:48.5122697Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:50:49.1564910Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:50:49.2004259Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:50:49.2146480Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:50:49.3312347Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:50:49.4184965Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:50:49.6896187Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:50:50.5557795Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:50:50.8084094Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:50:50.8406356Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:50:50.8867402Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:50:50.9115301Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:50:50.9518548Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:50:50.9671552Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:50:51.7160246Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:50:51.7395895Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:50:51.8596635Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:50:52.0644402Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:50:52.3055542Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:50:52.3215674Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:50:52.3566344Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:50:52.3725964Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:50:52.3829717Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:50:52.4000835Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:50:52.4400424Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:50:52.5424360Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:50:52.5683735Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:50:52.6021473Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:50:52.6511373Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:50:52.7125156Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:50:52.7965569Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:50:52.9303972Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:50:53.0900050Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:50:53.1067786Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:50:53.1851331Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:50:53.2046488Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:50:53.2440623Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:50:53.2585497Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:50:53.4003700Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:50:53.4176602Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:50:53.4332026Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:50:53.4491269Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:50:53.7908763Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T07:50:53.8463205Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T07:50:54.3050771Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T07:50:54.3267705Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T07:50:54.6357210Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T07:50:54.6624254Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T07:50:54.7200250Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T07:50:54.7393264Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900' 2025-09-07T07:50:54.7708836Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8' 2025-09-07T07:50:54.8218943Z Submodule path 'third_party/pybind11': checked out 'f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8' 2025-09-07T07:50:54.8907564Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67' 2025-09-07T07:50:55.2042467Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68' 2025-09-07T07:50:55.2795088Z Submodule path 'third_party/tensorpipe': checked out 'af0118d13e52f5a08841464a768e01a0bf3e3075' 2025-09-07T07:50:55.3813555Z Submodule path 'third_party/tensorpipe/third_party/googletest': checked out 'aee0f9d9b5b87796ee8a0ab26b7587ec30e8858e' 2025-09-07T07:50:55.4227681Z Submodule path 'third_party/tensorpipe/third_party/libnop': checked out '910b55815be16109f04f4180e9adee14fb4ce281' 2025-09-07T07:50:55.5995696Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '5152db2cbfeb5582e9c27c5ea1dba2cd9e10759b' 2025-09-07T07:50:55.7770046Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef' 2025-09-07T07:50:55.8506592Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5' 2025-09-07T07:50:55.8552768Z [command]/usr/bin/git submodule foreach --recursive git config --local gc.auto 0 2025-09-07T07:50:55.8806379Z Entering 'android/libs/fbjni' 2025-09-07T07:50:55.8967982Z Entering 'third_party/FP16' 2025-09-07T07:50:55.9079573Z Entering 'third_party/FXdiv' 2025-09-07T07:50:55.9442244Z Entering 'third_party/NNPACK' 2025-09-07T07:50:55.9529937Z Entering 'third_party/NVTX' 2025-09-07T07:50:55.9807604Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:56.0440086Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:56.1011007Z Entering 'third_party/aiter' 2025-09-07T07:50:56.1676975Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:56.1865736Z Entering 'third_party/benchmark' 2025-09-07T07:50:56.2302688Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:56.3621047Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:56.4158834Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:56.4326071Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:56.4614013Z Entering 'third_party/cutlass' 2025-09-07T07:50:56.5139140Z Entering 'third_party/fbgemm' 2025-09-07T07:50:56.5288797Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:56.5594215Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:56.6075093Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:56.6242137Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:56.6776066Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:56.6976539Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:56.7153525Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:56.7256888Z Entering 'third_party/flash-attention' 2025-09-07T07:50:56.7440581Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:56.7994040Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:56.8303687Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:56.8657540Z Entering 'third_party/fmt' 2025-09-07T07:50:56.8851958Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:56.9355937Z Entering 'third_party/gloo' 2025-09-07T07:50:57.0930005Z Entering 'third_party/googletest' 2025-09-07T07:50:57.2553214Z Entering 'third_party/ideep' 2025-09-07T07:50:57.2655739Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:57.2821213Z Entering 'third_party/ittapi' 2025-09-07T07:50:57.4560795Z Entering 'third_party/kineto' 2025-09-07T07:50:57.5355474Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:57.5434263Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:57.5971487Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:57.7200307Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:57.7912188Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:57.9643755Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:58.0050234Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:58.0257017Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:58.0332052Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:58.1615898Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:58.1742693Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:58.1855539Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:58.1980877Z Entering 'third_party/kleidiai' 2025-09-07T07:50:58.3702280Z Entering 'third_party/mimalloc' 2025-09-07T07:50:58.3905737Z Entering 'third_party/nlohmann' 2025-09-07T07:50:58.4035185Z Entering 'third_party/onnx' 2025-09-07T07:50:58.5069302Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:58.5734407Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:58.5829421Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:58.5895925Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:58.5978799Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:58.6100850Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:58.6191871Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:58.6246393Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:58.6316164Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:58.6469281Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:58.6534858Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:58.6651550Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:58.6764971Z Entering 'third_party/pocketfft' 2025-09-07T07:50:58.6873214Z Entering 'third_party/protobuf' 2025-09-07T07:50:58.6964241Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:58.7050112Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:58.7100099Z Entering 'third_party/psimd' 2025-09-07T07:50:58.7234560Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:58.7303783Z Entering 'third_party/pybind11' 2025-09-07T07:50:58.7399896Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:58.7489121Z Entering 'third_party/sleef' 2025-09-07T07:50:58.7639335Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:58.7698560Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:58.7840590Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:58.7912224Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:58.8058731Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:58.8102159Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:58.8216197Z ##[endgroup] 2025-09-07T07:50:58.8216670Z ##[group]Persisting credentials for submodules 2025-09-07T07:50:58.8225361Z [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' || :" 2025-09-07T07:50:58.8499302Z Entering 'android/libs/fbjni' 2025-09-07T07:50:58.8528442Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8528865Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8634149Z Entering 'third_party/FP16' 2025-09-07T07:50:58.8663477Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8663899Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8718530Z Entering 'third_party/FXdiv' 2025-09-07T07:50:58.8748997Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8749404Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8873334Z Entering 'third_party/NNPACK' 2025-09-07T07:50:58.8904553Z url.https://github.com/.insteadof 2025-09-07T07:50:58.8905096Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9002346Z Entering 'third_party/NVTX' 2025-09-07T07:50:58.9030082Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9030819Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9149573Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:58.9176954Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9177353Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9300257Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:58.9329268Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9329720Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9459648Z Entering 'third_party/aiter' 2025-09-07T07:50:58.9494608Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9494987Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9633750Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:58.9663543Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9663966Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9738577Z Entering 'third_party/benchmark' 2025-09-07T07:50:58.9771214Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9771598Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9925116Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:58.9951999Z url.https://github.com/.insteadof 2025-09-07T07:50:58.9952381Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0026161Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:59.0057295Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0057767Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0142851Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:59.0176179Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0176561Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0284674Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:59.0315994Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0316341Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0373329Z Entering 'third_party/cutlass' 2025-09-07T07:50:59.0405802Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0406180Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0513708Z Entering 'third_party/fbgemm' 2025-09-07T07:50:59.0543580Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0543954Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0595652Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:59.0624000Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0624367Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0708033Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:59.0735807Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0736170Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0848564Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:59.0878530Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0878867Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0940026Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:59.0969980Z url.https://github.com/.insteadof 2025-09-07T07:50:59.0970357Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1023213Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:59.1051996Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1052350Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1116399Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:59.1144612Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1145067Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1203701Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:59.1233499Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1233851Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1346369Z Entering 'third_party/flash-attention' 2025-09-07T07:50:59.1376590Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1376966Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1554010Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:59.1580133Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1580494Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1714750Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:59.1743864Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1744301Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1815375Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:59.1841322Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1841674Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1900955Z Entering 'third_party/fmt' 2025-09-07T07:50:59.1931132Z url.https://github.com/.insteadof 2025-09-07T07:50:59.1931538Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2009152Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:59.2037623Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2037969Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2125179Z Entering 'third_party/gloo' 2025-09-07T07:50:59.2154403Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2154836Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2222044Z Entering 'third_party/googletest' 2025-09-07T07:50:59.2251369Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2251796Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2304802Z Entering 'third_party/ideep' 2025-09-07T07:50:59.2337195Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2337698Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2409989Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:59.2443814Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2444196Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2544783Z Entering 'third_party/ittapi' 2025-09-07T07:50:59.2574112Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2574500Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2650933Z Entering 'third_party/kineto' 2025-09-07T07:50:59.2677239Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2677596Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2734278Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:59.2764175Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2764529Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2857529Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:59.2884560Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2884926Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2956433Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:59.2987782Z url.https://github.com/.insteadof 2025-09-07T07:50:59.2988136Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3053252Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:59.3080042Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3080677Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3138183Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:59.3169186Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3169578Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3266806Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:59.3293749Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3294124Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3448686Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:59.3474662Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3475014Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3671276Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:59.3698375Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3698752Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3834416Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:59.3863381Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3863749Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3949262Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:59.3975512Z url.https://github.com/.insteadof 2025-09-07T07:50:59.3975872Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4139638Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:59.4166613Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4166981Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4259823Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:59.4289361Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4289716Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4386972Z Entering 'third_party/kleidiai' 2025-09-07T07:50:59.4414577Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4414910Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4581614Z Entering 'third_party/mimalloc' 2025-09-07T07:50:59.4608544Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4608891Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4711815Z Entering 'third_party/nlohmann' 2025-09-07T07:50:59.4737927Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4738282Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4880332Z Entering 'third_party/onnx' 2025-09-07T07:50:59.4905372Z url.https://github.com/.insteadof 2025-09-07T07:50:59.4905704Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5101338Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:59.5129996Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5130361Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5318372Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:59.5347492Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5347855Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5514163Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:59.5539172Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5539557Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5752781Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:59.5777818Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5778207Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5942668Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:59.5968205Z url.https://github.com/.insteadof 2025-09-07T07:50:59.5968576Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6074815Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:59.6100047Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6100384Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6239773Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:59.6264932Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6265283Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6409686Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:59.6435016Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6435399Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6546626Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:59.6572207Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6572578Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6745144Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:59.6771172Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6771522Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6904393Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:59.6930232Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6930587Z url.https://github.com/.insteadof 2025-09-07T07:50:59.6980284Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:59.7005248Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7005602Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7195956Z Entering 'third_party/pocketfft' 2025-09-07T07:50:59.7222164Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7222542Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7331306Z Entering 'third_party/protobuf' 2025-09-07T07:50:59.7357788Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7358151Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7463406Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:59.7487396Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7487742Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7664212Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:59.7689016Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7689363Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7820003Z Entering 'third_party/psimd' 2025-09-07T07:50:59.7846877Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7847239Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7971273Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:59.7997265Z url.https://github.com/.insteadof 2025-09-07T07:50:59.7997622Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8130613Z Entering 'third_party/pybind11' 2025-09-07T07:50:59.8158351Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8158725Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8289168Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:59.8315417Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8315807Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8428870Z Entering 'third_party/sleef' 2025-09-07T07:50:59.8454776Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8455131Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8521042Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:59.8548675Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8549196Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8602220Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:59.8628140Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8631489Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8685674Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:59.8711241Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8711617Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8774946Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:59.8803798Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8804156Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8843790Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:59.8868354Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8868708Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8903646Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:59.8938012Z url.https://github.com/.insteadof 2025-09-07T07:50:59.8938391Z url.https://github.com/.insteadof 2025-09-07T07:50:59.9032050Z [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" 2025-09-07T07:50:59.9282355Z Entering 'android/libs/fbjni' 2025-09-07T07:50:59.9355453Z file:/home/frank/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:50:59.9374522Z Entering 'third_party/FP16' 2025-09-07T07:50:59.9449779Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:50:59.9468082Z Entering 'third_party/FXdiv' 2025-09-07T07:50:59.9573537Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:50:59.9593671Z Entering 'third_party/NNPACK' 2025-09-07T07:50:59.9649805Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:50:59.9668784Z Entering 'third_party/NVTX' 2025-09-07T07:50:59.9789307Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:50:59.9811044Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:59.9891585Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:50:59.9910044Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:59.9961113Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:51:00.0000704Z Entering 'third_party/aiter' 2025-09-07T07:51:00.0052120Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:51:00.0069917Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:00.0151364Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:51:00.0179412Z Entering 'third_party/benchmark' 2025-09-07T07:51:00.0221931Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:00.0240262Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:00.2984542Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T07:51:00.3019818Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:00.3113763Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T07:51:00.3138809Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:00.3352024Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T07:51:00.3380058Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:00.3586770Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T07:51:00.3611419Z Entering 'third_party/cutlass' 2025-09-07T07:51:00.3776603Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config remote.origin.url 2025-09-07T07:51:00.3815273Z Entering 'third_party/fbgemm' 2025-09-07T07:51:00.3987343Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T07:51:00.4012034Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:00.4137856Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T07:51:00.4160494Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:00.4211437Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T07:51:00.4239799Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:00.4323658Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T07:51:00.4343162Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:00.4409697Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T07:51:00.4440096Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:00.4488522Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T07:51:00.4508186Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:00.4556613Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T07:51:00.4582984Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:00.4636637Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T07:51:00.4660571Z Entering 'third_party/flash-attention' 2025-09-07T07:51:00.4706084Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:51:00.4725211Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:00.4814057Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:51:00.4839204Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:00.4927141Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:51:00.4957131Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:00.5081965Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:51:00.5103892Z Entering 'third_party/fmt' 2025-09-07T07:51:00.5195302Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:51:00.5213369Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:00.5281228Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T07:51:00.5299533Z Entering 'third_party/gloo' 2025-09-07T07:51:00.5368353Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T07:51:00.5387904Z Entering 'third_party/googletest' 2025-09-07T07:51:00.5481880Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:00.5502716Z Entering 'third_party/ideep' 2025-09-07T07:51:00.5614893Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T07:51:00.5633203Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:00.5716187Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T07:51:00.5743655Z Entering 'third_party/ittapi' 2025-09-07T07:51:00.5904806Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:51:00.5925045Z Entering 'third_party/kineto' 2025-09-07T07:51:00.6018565Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:51:00.6037497Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:00.6095499Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:51:00.6112882Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:00.6199303Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:51:00.6221532Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:00.6293055Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T07:51:00.6310716Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:00.6406127Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:51:00.6426397Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:00.6511885Z file:/home/frank/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T07:51:00.6528342Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:00.6575465Z 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'third_party/psimd' 2025-09-07T07:51:02.6340474Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:02.6410441Z Entering 'third_party/pybind11' 2025-09-07T07:51:02.6540270Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:02.6597484Z Entering 'third_party/sleef' 2025-09-07T07:51:02.6681072Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:02.6761253Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:02.6863444Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:02.6913502Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:02.7009139Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:02.7087203Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:02.7207037Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-09-07T07:51:02.7466889Z Entering 'android/libs/fbjni' 2025-09-07T07:51:02.7576117Z Entering 'third_party/FP16' 2025-09-07T07:51:02.7638013Z Entering 'third_party/FXdiv' 2025-09-07T07:51:02.7718513Z Entering 'third_party/NNPACK' 2025-09-07T07:51:02.7804962Z Entering 'third_party/NVTX' 2025-09-07T07:51:02.7876337Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:02.7964459Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:02.8061320Z Entering 'third_party/aiter' 2025-09-07T07:51:02.8115451Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:02.8186612Z Entering 'third_party/benchmark' 2025-09-07T07:51:02.8236206Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:02.8326641Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:02.8380949Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:02.8464896Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:02.8558125Z Entering 'third_party/cutlass' 2025-09-07T07:51:02.8641334Z Entering 'third_party/fbgemm' 2025-09-07T07:51:02.8707778Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:02.8779528Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:03.0213406Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:03.0260056Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:03.0338312Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:03.0586408Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:03.0911986Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:03.1213913Z Entering 'third_party/flash-attention' 2025-09-07T07:51:03.1691181Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:03.1777174Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:03.1837481Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:03.1910609Z Entering 'third_party/fmt' 2025-09-07T07:51:03.2189108Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:03.2827354Z Entering 'third_party/gloo' 2025-09-07T07:51:03.2900965Z Entering 'third_party/googletest' 2025-09-07T07:51:03.2962037Z Entering 'third_party/ideep' 2025-09-07T07:51:03.3013801Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:03.3297805Z Entering 'third_party/ittapi' 2025-09-07T07:51:03.3536195Z Entering 'third_party/kineto' 2025-09-07T07:51:03.3868074Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:03.4007226Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:03.4410614Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:03.4592405Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:03.4911920Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:03.4998796Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:03.5068482Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:03.5134782Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:03.5458468Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:03.5593980Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:03.5687222Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:03.5772630Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:03.5826816Z Entering 'third_party/kleidiai' 2025-09-07T07:51:03.7147649Z Entering 'third_party/mimalloc' 2025-09-07T07:51:03.7632400Z Entering 'third_party/nlohmann' 2025-09-07T07:51:03.7738414Z Entering 'third_party/onnx' 2025-09-07T07:51:03.7858310Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:03.7965428Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:03.8124535Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:03.9507234Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:03.9689746Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:04.0520252Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:04.1332891Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:04.1444144Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:04.1532006Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:04.1647325Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:04.1740261Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:04.1871777Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:04.3221444Z Entering 'third_party/pocketfft' 2025-09-07T07:51:04.4442797Z Entering 'third_party/protobuf' 2025-09-07T07:51:04.4547550Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:04.4602069Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:04.4722714Z Entering 'third_party/psimd' 2025-09-07T07:51:04.4838098Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:04.6375517Z Entering 'third_party/pybind11' 2025-09-07T07:51:04.6516585Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:04.6612242Z Entering 'third_party/sleef' 2025-09-07T07:51:04.6706999Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:04.6806137Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:04.7415457Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:04.8238918Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:04.8285509Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:04.8321377Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:04.8381011Z ##[endgroup] 2025-09-07T07:51:04.8434703Z [command]/usr/bin/git log -1 --format=%H 2025-09-07T07:51:04.8461510Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:04.9433124Z Prepare all required actions 2025-09-07T07:51:04.9433803Z Getting action download info 2025-09-07T07:51:05.2575391Z ##[group]Run ./.github/actions/setup-linux 2025-09-07T07:51:05.2575737Z env: 2025-09-07T07:51:05.2575959Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:05.2576210Z ##[endgroup] 2025-09-07T07:51:05.2937957Z ##[group]Run set -euo pipefail 2025-09-07T07:51:05.2938364Z set -euo pipefail 2025-09-07T07:51:05.2938654Z function get_ec2_metadata() { 2025-09-07T07:51:05.2939044Z  # Pulled from instance metadata endpoint for EC2 2025-09-07T07:51:05.2939707Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-09-07T07:51:05.2940288Z  category=$1 2025-09-07T07:51:05.2940650Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-09-07T07:51:05.2941156Z  runner_name_str=i-03028b1668c838483-1006 2025-09-07T07:51:05.2941585Z  if [[ -f /.inarc ]]; then 2025-09-07T07:51:05.2941980Z  echo "ARC Runner, no info on ec2 metadata" 2025-09-07T07:51:05.2942369Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-09-07T07:51:05.2942854Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-09-07T07:51:05.2943633Z  else 2025-09-07T07:51:05.2944527Z  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}" 2025-09-07T07:51:05.2945474Z  fi 2025-09-07T07:51:05.2945683Z } 2025-09-07T07:51:05.2945951Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-09-07T07:51:05.2946386Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-09-07T07:51:05.2946875Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-09-07T07:51:05.2947292Z echo "system info $(uname -a)" 2025-09-07T07:51:05.2961227Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:05.2961628Z env: 2025-09-07T07:51:05.2961858Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:05.2962124Z ##[endgroup] 2025-09-07T07:51:05.3052703Z ami-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:05.3058200Z instance-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:05.3063606Z instance-type: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:05.3075128Z system info Linux 4325a60d1947 6.5.0-1024-aws #24~22.04.1-Ubuntu SMP Thu Jul 18 10:43:12 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux 2025-09-07T07:51:05.3219782Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:51:05.3220787Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:51:05.3235795Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:05.3236203Z env: 2025-09-07T07:51:05.3236429Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:05.3236695Z ##[endgroup] 2025-09-07T07:51:05.4753149Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T07:51:05.4753467Z with: 2025-09-07T07:51:05.4753690Z shell: bash 2025-09-07T07:51:05.4753951Z timeout_minutes: 5 2025-09-07T07:51:05.4754204Z max_attempts: 3 2025-09-07T07:51:05.4754438Z retry_wait_seconds: 30 2025-09-07T07:51:05.4757156Z command: AWS_ACCOUNT_ID=$(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 2025-09-07T07:51:05.4759645Z polling_interval_seconds: 1 2025-09-07T07:51:05.4759994Z warning_on_retry: true 2025-09-07T07:51:05.4760254Z continue_on_error: false 2025-09-07T07:51:05.4760519Z env: 2025-09-07T07:51:05.4760736Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:05.4761021Z AWS_RETRY_MODE: standard 2025-09-07T07:51:05.4761275Z AWS_MAX_ATTEMPTS: 5 2025-09-07T07:51:05.4761580Z AWS_DEFAULT_REGION: us-east-1 2025-09-07T07:51:05.4761884Z ##[endgroup] 2025-09-07T07:51:07.3348679Z 2025-09-07T07:51:07.3349355Z WARNING! Your credentials are stored unencrypted in '/home/frank/.docker/config.json'. 2025-09-07T07:51:07.3350209Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:07.3350792Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:07.3351221Z 2025-09-07T07:51:07.3351667Z Login Succeeded 2025-09-07T07:51:07.5588925Z Command completed after 1 attempt(s). 2025-09-07T07:51:07.6193456Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:07.6194035Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:07.6194510Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:07.6214303Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:07.6215473Z env: 2025-09-07T07:51:07.6215863Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:07.6216139Z ##[endgroup] 2025-09-07T07:51:07.7108604Z ##[group]Run set +e 2025-09-07T07:51:07.7108953Z set +e 2025-09-07T07:51:07.7109338Z set -x 2025-09-07T07:51:07.7109746Z  2025-09-07T07:51:07.7110168Z PT_DOMAIN=download.pytorch.org 2025-09-07T07:51:07.7111247Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-09-07T07:51:07.7112596Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-09-07T07:51:07.7113648Z # one is returned at random 2025-09-07T07:51:07.7114385Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-09-07T07:51:07.7114883Z  2025-09-07T07:51:07.7115240Z if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:51:07.7115904Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-09-07T07:51:07.7116784Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-09-07T07:51:07.7117443Z  2025-09-07T07:51:07.7117863Z  if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:51:07.7118562Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-09-07T07:51:07.7119232Z  exit 1 2025-09-07T07:51:07.7119649Z  fi 2025-09-07T07:51:07.7120033Z fi 2025-09-07T07:51:07.7120384Z  2025-09-07T07:51:07.7120836Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-09-07T07:51:07.7121503Z  # Clean up any old records first 2025-09-07T07:51:07.7122165Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-09-07T07:51:07.7122760Z fi 2025-09-07T07:51:07.7123487Z  2025-09-07T07:51:07.7124041Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-09-07T07:51:07.7124774Z cat /etc/hosts 2025-09-07T07:51:07.7143489Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:07.7144182Z env: 2025-09-07T07:51:07.7144563Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:07.7145036Z ##[endgroup] 2025-09-07T07:51:07.7190337Z + PT_DOMAIN=download.pytorch.org 2025-09-07T07:51:07.7197236Z ++ dig -4 +short download.pytorch.org 2025-09-07T07:51:07.7198452Z ++ tail -n1 2025-09-07T07:51:07.7417275Z + RESOLVED_IP=18.160.10.76 2025-09-07T07:51:07.7628604Z + '[' -z 18.160.10.76 ']' 2025-09-07T07:51:07.7629196Z + grep -r download.pytorch.org /etc/hosts 2025-09-07T07:51:07.7646277Z + echo '18.160.10.76 download.pytorch.org' 2025-09-07T07:51:07.7650484Z + sudo tee -a /etc/hosts 2025-09-07T07:51:07.8039079Z 18.160.10.76 download.pytorch.org 2025-09-07T07:51:07.8039981Z + cat /etc/hosts 2025-09-07T07:51:07.8040331Z 127.0.0.1 localhost 2025-09-07T07:51:07.8050686Z ::1 localhost ip6-localhost ip6-loopback 2025-09-07T07:51:07.8051348Z fe00:: ip6-localnet 2025-09-07T07:51:07.8051605Z ff00:: ip6-mcastprefix 2025-09-07T07:51:07.8051881Z ff02::1 ip6-allnodes 2025-09-07T07:51:07.8052116Z ff02::2 ip6-allrouters 2025-09-07T07:51:07.8052360Z 172.17.0.2 4325a60d1947 2025-09-07T07:51:07.8052625Z 18.160.10.76 download.pytorch.org 2025-09-07T07:51:07.8115287Z ##[group]Run set +x 2025-09-07T07:51:07.8115776Z set +x 2025-09-07T07:51:07.8116155Z  2025-09-07T07:51:07.8116497Z max_attempts=30 2025-09-07T07:51:07.8116968Z delay=10 2025-09-07T07:51:07.8117347Z attempt=1 2025-09-07T07:51:07.8117728Z  2025-09-07T07:51:07.8118174Z for attempt in $(seq 1 $max_attempts); do 2025-09-07T07:51:07.8119145Z  echo "Attempt $attempt of $max_attempts: Checking if Docker daemon is running..." 2025-09-07T07:51:07.8120068Z  if docker info > /dev/null 2>&1; then 2025-09-07T07:51:07.8120834Z  echo "Docker is running. Proceeding with the next steps" 2025-09-07T07:51:07.8121417Z  exit 0 2025-09-07T07:51:07.8121680Z  else 2025-09-07T07:51:07.8122241Z  echo "Docker is not running yet." 2025-09-07T07:51:07.8123145Z  echo "Retrying in $delay seconds..." 2025-09-07T07:51:07.8123521Z  sleep $delay 2025-09-07T07:51:07.8123911Z  fi 2025-09-07T07:51:07.8124137Z done 2025-09-07T07:51:07.8124491Z echo "Reached maximum attempts to connect to Docker. Exiting." 2025-09-07T07:51:07.8124926Z exit 1 2025-09-07T07:51:07.8142649Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:07.8143308Z env: 2025-09-07T07:51:07.8143692Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:07.8144167Z ##[endgroup] 2025-09-07T07:51:07.8224171Z Attempt 1 of 30: Checking if Docker daemon is running... 2025-09-07T07:51:07.8666501Z Docker is running. Proceeding with the next steps 2025-09-07T07:51:08.0215694Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-09-07T07:51:08.0216274Z with: 2025-09-07T07:51:08.0217394Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:08.0218517Z use-custom-docker-registry: true 2025-09-07T07:51:08.0218827Z docker-build-dir: .ci/docker 2025-09-07T07:51:08.0219131Z docker-build-script: ./build.sh 2025-09-07T07:51:08.0219433Z working-directory: . 2025-09-07T07:51:08.0219786Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:08.0220182Z force-push: false 2025-09-07T07:51:08.0220585Z env: 2025-09-07T07:51:08.0220931Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:08.0222609Z ##[endgroup] 2025-09-07T07:51:08.0327423Z ##[group]Run set -ex 2025-09-07T07:51:08.0327981Z set -ex 2025-09-07T07:51:08.0328361Z  2025-09-07T07:51:08.0329062Z # If the docker build directory or the build script doesn't exist, the action will 2025-09-07T07:51:08.0329892Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-09-07T07:51:08.0330560Z # job could then download the pre-built image as usual 2025-09-07T07:51:08.0331480Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-09-07T07:51:08.0332653Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0333239Z else 2025-09-07T07:51:08.0333702Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0334457Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0335425Z  2025-09-07T07:51:08.0337996Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-09-07T07:51:08.0340405Z  exit 0 2025-09-07T07:51:08.0340801Z fi 2025-09-07T07:51:08.0341177Z  2025-09-07T07:51:08.0341817Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-09-07T07:51:08.0342931Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-09-07T07:51:08.0343893Z  # use it as it is, but first let's extract the tag 2025-09-07T07:51:08.0344762Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-09-07T07:51:08.0345673Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0346605Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0347225Z else 2025-09-07T07:51:08.0347633Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-09-07T07:51:08.0348032Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-09-07T07:51:08.0348595Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-09-07T07:51:08.0349169Z  fi 2025-09-07T07:51:08.0350012Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-09-07T07:51:08.0354081Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0356045Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0359396Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0359935Z fi 2025-09-07T07:51:08.0379351Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:08.0380063Z env: 2025-09-07T07:51:08.0380836Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:08.0381332Z REPO_NAME: pytorch 2025-09-07T07:51:08.0385747Z 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 2025-09-07T07:51:08.0388724Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:51:08.0389046Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-09-07T07:51:08.0389698Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:08.0390875Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-09-07T07:51:08.0391414Z CUSTOM_TAG_PREFIX: 2025-09-07T07:51:08.0391753Z ##[endgroup] 2025-09-07T07:51:08.0488837Z + [[ -d .ci/docker ]] 2025-09-07T07:51:08.0489332Z + [[ -f .ci/docker/./build.sh ]] 2025-09-07T07:51:08.0489721Z + [[ true == \t\r\u\e ]] 2025-09-07T07:51:08.0489984Z + echo skip=false 2025-09-07T07:51:08.0495643Z + [[ 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* ]] 2025-09-07T07:51:08.0501245Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:08.0502955Z ++ awk -F '[:,]' '{print $2}' 2025-09-07T07:51:08.0515573Z + DOCKER_TAG=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:08.0516921Z + echo docker-tag=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:08.0520598Z + 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 2025-09-07T07:51:08.0586284Z ##[group]Run set +e 2025-09-07T07:51:08.0586757Z set +e 2025-09-07T07:51:08.0588972Z set -x 2025-09-07T07:51:08.0589859Z  2025-09-07T07:51:08.0590216Z login() { 2025-09-07T07:51:08.0591075Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:51:08.0592004Z } 2025-09-07T07:51:08.0592366Z  2025-09-07T07:51:08.0592742Z retry () { 2025-09-07T07:51:08.0593186Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:51:08.0593772Z } 2025-09-07T07:51:08.0594132Z  2025-09-07T07:51:08.0594535Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:51:08.0595081Z  2025-09-07T07:51:08.0595453Z START_TIME=$(date +%s) 2025-09-07T07:51:08.0595986Z # Wait up to 120 minutes 2025-09-07T07:51:08.0596492Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-09-07T07:51:08.0596986Z  # Check if image already exists, if it does then skip building it 2025-09-07T07:51:08.0597553Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-09-07T07:51:08.0598109Z  exit 0 2025-09-07T07:51:08.0598505Z  fi 2025-09-07T07:51:08.0598886Z  2025-09-07T07:51:08.0599579Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-09-07T07:51:08.0601737Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-09-07T07:51:08.0603401Z  # latter, it will wait for the Docker images to become available before continuing 2025-09-07T07:51:08.0604361Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-09-07T07:51:08.0604806Z  # It's a Docker build job, let's build the image 2025-09-07T07:51:08.0605172Z  break 2025-09-07T07:51:08.0605411Z  else 2025-09-07T07:51:08.0605760Z  # It's a regular build job, wait for the image to become available 2025-09-07T07:51:08.0606170Z  sleep 300 2025-09-07T07:51:08.0606419Z  fi 2025-09-07T07:51:08.0606704Z done 2025-09-07T07:51:08.0606920Z  2025-09-07T07:51:08.0607922Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-09-07T07:51:08.0609071Z # be empty. The default action would be to continue rebuild the image 2025-09-07T07:51:08.0611549Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-09-07T07:51:08.0612121Z  # if we're on the base branch then use the parent commit 2025-09-07T07:51:08.0612600Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-09-07T07:51:08.0612914Z else 2025-09-07T07:51:08.0613371Z  # otherwise we're on a PR, so use the most recent base commit 2025-09-07T07:51:08.0614269Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-09-07T07:51:08.0614839Z fi 2025-09-07T07:51:08.0615037Z  2025-09-07T07:51:08.0615403Z if [[ -z "${MERGE_BASE}" ]]; then 2025-09-07T07:51:08.0615842Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0616243Z  2025-09-07T07:51:08.0617428Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-09-07T07:51:08.0618433Z  exit 0 2025-09-07T07:51:08.0619040Z fi 2025-09-07T07:51:08.0619674Z  2025-09-07T07:51:08.0620294Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-09-07T07:51:08.0621729Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-09-07T07:51:08.0622458Z  exit 1 2025-09-07T07:51:08.0622866Z fi 2025-09-07T07:51:08.0623106Z  2025-09-07T07:51:08.0623682Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-09-07T07:51:08.0624626Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-09-07T07:51:08.0625351Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-09-07T07:51:08.0626643Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-09-07T07:51:08.0627722Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-09-07T07:51:08.0628268Z fi 2025-09-07T07:51:08.0628552Z  2025-09-07T07:51:08.0628991Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:08.0815671Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:08.0817518Z env: 2025-09-07T07:51:08.0818029Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:08.0818920Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:51:08.0819722Z BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:08.0822198Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:08.0824232Z DOCKER_TAG: pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:08.0825668Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:08.0826701Z DOCKER_PUSH: 2025-09-07T07:51:08.0827102Z ##[endgroup] 2025-09-07T07:51:08.1426132Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:08.1427128Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:08.1428181Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:51:08.1431421Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:09.1438568Z 2025-09-07T07:51:09.1439220Z WARNING! Your credentials are stored unencrypted in '/home/frank/.docker/config.json'. 2025-09-07T07:51:09.1439854Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:09.1440304Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:09.1440569Z 2025-09-07T07:51:09.1440663Z Login Succeeded 2025-09-07T07:51:09.1544414Z ++ date +%s 2025-09-07T07:51:09.1545013Z + START_TIME=1757231469 2025-09-07T07:51:09.1545657Z ++ date +%s 2025-09-07T07:51:09.1545879Z + [[ 1757224269 -lt 1757231469 ]] 2025-09-07T07:51:09.1546984Z + 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 2025-09-07T07:51:09.3729621Z { 2025-09-07T07:51:09.3729894Z "schemaVersion": 2, 2025-09-07T07:51:09.3730338Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-09-07T07:51:09.3730788Z "config": { 2025-09-07T07:51:09.3731116Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-09-07T07:51:09.3731530Z "size": 31375, 2025-09-07T07:51:09.3731945Z "digest": "sha256:29d1d8a31b215537637bab7c99e18c255840b899cf7023e4e3cb5efa3270aef8" 2025-09-07T07:51:09.3732435Z }, 2025-09-07T07:51:09.3732730Z "layers": [ 2025-09-07T07:51:09.3732934Z { 2025-09-07T07:51:09.3733299Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.3733728Z "size": 30448359, 2025-09-07T07:51:09.3734156Z "digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46" 2025-09-07T07:51:09.3734635Z }, 2025-09-07T07:51:09.3734831Z { 2025-09-07T07:51:09.3735153Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.3735573Z "size": 1554, 2025-09-07T07:51:09.3735972Z "digest": "sha256:171dcef20c49de4bc9268f60e02f111b72c638b0f24c3c5636c5013029db6d30" 2025-09-07T07:51:09.3736451Z }, 2025-09-07T07:51:09.3736644Z { 2025-09-07T07:51:09.3736968Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.3737472Z "size": 313297922, 2025-09-07T07:51:09.3737909Z "digest": "sha256:4c92b3f72f1df31fe9f487fc1c27fcf1ba475ffb43abd69056306d1247786e40" 2025-09-07T07:51:09.3738394Z }, 2025-09-07T07:51:09.3738589Z { 2025-09-07T07:51:09.3738907Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.3739327Z "size": 792, 2025-09-07T07:51:09.3739735Z "digest": "sha256:744f9ba90a6582eb601b3c20409bb10d6dad635dd118c3975f79721f4c82747c" 2025-09-07T07:51:09.3740222Z }, 2025-09-07T07:51:09.3740397Z { 2025-09-07T07:51:09.3740718Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.3741135Z "size": 106, 2025-09-07T07:51:09.3741532Z "digest": "sha256:d3c08322a3326e45849dd80264a047c4f42ba4a2419d35c919542e2890e23934" 2025-09-07T07:51:09.3741986Z }, 2025-09-07T07:51:09.3742176Z { 2025-09-07T07:51:09.3742497Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.3742915Z "size": 704, 2025-09-07T07:51:09.3743311Z "digest": 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"sha256:1e93be219e89e7733b91ba7e3af1a44d985e84959f732ecd5f5ca61bd13b5d41" 2025-09-07T07:51:09.4557514Z }, 2025-09-07T07:51:09.4557704Z { 2025-09-07T07:51:09.4558027Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4558442Z "size": 32, 2025-09-07T07:51:09.4558835Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:09.4559316Z }, 2025-09-07T07:51:09.4559503Z { 2025-09-07T07:51:09.4559863Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4560338Z "size": 158, 2025-09-07T07:51:09.4560743Z "digest": "sha256:136825afebb533ee295f0d2523595281086c6410c60d5f712b84cefd24cb31d5" 2025-09-07T07:51:09.4561484Z }, 2025-09-07T07:51:09.4561826Z { 2025-09-07T07:51:09.4562324Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4563084Z "size": 1368, 2025-09-07T07:51:09.4563656Z "digest": "sha256:22b39805302d877e4c1ba433ebc36520438ea29a9ba8bc059efbcd9106f3a82d" 2025-09-07T07:51:09.4564317Z }, 2025-09-07T07:51:09.4564839Z { 2025-09-07T07:51:09.4565260Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4565679Z "size": 32, 2025-09-07T07:51:09.4566168Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:09.4566636Z }, 2025-09-07T07:51:09.4566825Z { 2025-09-07T07:51:09.4567145Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4567638Z "size": 136, 2025-09-07T07:51:09.4568038Z "digest": "sha256:d12add675e3505e74eb9880eeef540ea0801282ca1ae01c3c221157cec91f5ae" 2025-09-07T07:51:09.4568527Z }, 2025-09-07T07:51:09.4568756Z { 2025-09-07T07:51:09.4569079Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4569479Z "size": 380, 2025-09-07T07:51:09.4570079Z "digest": "sha256:bc127046d33a7a98563698411b54ece8a167d520922879d7b69e8ca73a12d034" 2025-09-07T07:51:09.4570703Z }, 2025-09-07T07:51:09.4570894Z { 2025-09-07T07:51:09.4571203Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4571821Z "size": 32, 2025-09-07T07:51:09.4572500Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:09.4573152Z }, 2025-09-07T07:51:09.4573331Z { 2025-09-07T07:51:09.4573696Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4574114Z "size": 104, 2025-09-07T07:51:09.4574523Z "digest": "sha256:951e8ce838415c4257680a9d60d216f3750cbb18d243d9a21e2008cce7e589cf" 2025-09-07T07:51:09.4575089Z }, 2025-09-07T07:51:09.4575281Z { 2025-09-07T07:51:09.4575605Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4576021Z "size": 408, 2025-09-07T07:51:09.4576427Z "digest": "sha256:32340b97ae50ba7b2918ab40d6f4a8db875afee69318f484e4deb0a1e2ec4beb" 2025-09-07T07:51:09.4577009Z }, 2025-09-07T07:51:09.4577218Z { 2025-09-07T07:51:09.4577710Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4578131Z "size": 32, 2025-09-07T07:51:09.4578545Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:09.4579024Z }, 2025-09-07T07:51:09.4579216Z { 2025-09-07T07:51:09.4579528Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4579985Z "size": 109, 2025-09-07T07:51:09.4580483Z "digest": "sha256:5bbb04cd6b57ae13d7cf05ab9e9b4ed9752833ee2dba4eeaac47bde6022c4725" 2025-09-07T07:51:09.4580978Z }, 2025-09-07T07:51:09.4581153Z { 2025-09-07T07:51:09.4581476Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4581892Z "size": 1897, 2025-09-07T07:51:09.4582312Z "digest": "sha256:d8c4b845cfc7ca7cc0604f472bf6da8b1f1d4e98dff3c76e1985a7013a5b9e3f" 2025-09-07T07:51:09.4582788Z }, 2025-09-07T07:51:09.4582977Z { 2025-09-07T07:51:09.4583340Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4583989Z "size": 243440375, 2025-09-07T07:51:09.4584663Z "digest": "sha256:b35c180f4d8ddc2396eac4a6b893f438481a8163ceb0b88f203488bc5f2a8ba4" 2025-09-07T07:51:09.4585261Z }, 2025-09-07T07:51:09.4585503Z { 2025-09-07T07:51:09.4585826Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4586238Z "size": 106, 2025-09-07T07:51:09.4586639Z "digest": "sha256:5f967b3c303a99e609441551f7c8988cca4fd464c0c3127506bff8509583091b" 2025-09-07T07:51:09.4587108Z }, 2025-09-07T07:51:09.4587300Z { 2025-09-07T07:51:09.4587610Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4588029Z "size": 166, 2025-09-07T07:51:09.4588436Z "digest": "sha256:04770904f012e5584f1c19a0bc92d9863baaebf08bf75b4a9981f2b7795c8953" 2025-09-07T07:51:09.4588911Z }, 2025-09-07T07:51:09.4589097Z { 2025-09-07T07:51:09.4589501Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4589923Z "size": 7943, 2025-09-07T07:51:09.4590715Z "digest": "sha256:73373941fb321b4cb4a171b1423a68a4c7fedada3a1498868d7efe93cb03170e" 2025-09-07T07:51:09.4591211Z }, 2025-09-07T07:51:09.4591458Z { 2025-09-07T07:51:09.4591819Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4592239Z "size": 8072, 2025-09-07T07:51:09.4592636Z "digest": "sha256:9572e6cd907bfa4888456dbccc6e22146a0044374585f3fa0a8ced19b831ed62" 2025-09-07T07:51:09.4593109Z }, 2025-09-07T07:51:09.4593299Z { 2025-09-07T07:51:09.4593628Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4594035Z "size": 304, 2025-09-07T07:51:09.4594512Z "digest": "sha256:64a544aba233551e38898f138dd6ba3161ccdb9554e0ffb5b9d8f0f7fe4a7fa8" 2025-09-07T07:51:09.4594988Z }, 2025-09-07T07:51:09.4595262Z { 2025-09-07T07:51:09.4595992Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4596695Z "size": 13362696, 2025-09-07T07:51:09.4597222Z "digest": "sha256:7e35418a24997de5428763c93826679486760a1a9563209ae64de66ba45f99c1" 2025-09-07T07:51:09.4597718Z }, 2025-09-07T07:51:09.4597920Z { 2025-09-07T07:51:09.4598263Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4598725Z "size": 108, 2025-09-07T07:51:09.4599131Z "digest": "sha256:2ed8e82748d4a1131f41d9e41322f47a6ffef67a5a2b7bf5392237db5c035c61" 2025-09-07T07:51:09.4599594Z }, 2025-09-07T07:51:09.4599782Z { 2025-09-07T07:51:09.4600104Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4600525Z "size": 54145663, 2025-09-07T07:51:09.4600933Z "digest": "sha256:c988fbcccd708fb158a81c429d32e1060a7e40924fc3c987c629fa69d9484717" 2025-09-07T07:51:09.4601411Z }, 2025-09-07T07:51:09.4601601Z { 2025-09-07T07:51:09.4601986Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:09.4602435Z "size": 32, 2025-09-07T07:51:09.4603158Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:09.4603842Z } 2025-09-07T07:51:09.4604101Z ] 2025-09-07T07:51:09.4604344Z } 2025-09-07T07:51:09.4604634Z + exit 0 2025-09-07T07:51:09.5218353Z ##[group]Run set -eux 2025-09-07T07:51:09.5218659Z set -eux 2025-09-07T07:51:09.5219096Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-09-07T07:51:09.5220292Z 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 2025-09-07T07:51:09.5234487Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:09.5234897Z env: 2025-09-07T07:51:09.5235124Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:09.5235390Z ##[endgroup] 2025-09-07T07:51:09.5383098Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-09-07T07:51:09.5383977Z + jq --raw-output .SecretString 2025-09-07T07:51:09.5386642Z + jq -r .docker_hub_readonly_token 2025-09-07T07:51:09.5388634Z + docker login --username pytorchbot --password-stdin 2025-09-07T07:51:10.4333791Z 2025-09-07T07:51:10.4334201Z Login Succeeded 2025-09-07T07:51:10.4334784Z WARNING! Your credentials are stored unencrypted in '/home/frank/.docker/config.json'. 2025-09-07T07:51:10.4335388Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:10.4335881Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:10.4336184Z 2025-09-07T07:51:10.4479788Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:51:10.4480422Z tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:51:10.4482789Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-09-07T07:51:10.4501747Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:10.4502148Z env: 2025-09-07T07:51:10.4502377Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:10.4503585Z 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 2025-09-07T07:51:10.4504985Z ##[endgroup] 2025-09-07T07:51:10.4641443Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:10.6624203Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-09-07T07:51:10.6624948Z with: 2025-09-07T07:51:10.6625982Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:10.6627200Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:10.6627638Z env: 2025-09-07T07:51:10.6627861Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:10.6628131Z ##[endgroup] 2025-09-07T07:51:10.6648458Z ##[group]Run set -x 2025-09-07T07:51:10.6648755Z set -x 2025-09-07T07:51:10.6649021Z set +e 2025-09-07T07:51:10.6649245Z  2025-09-07T07:51:10.6649445Z login() { 2025-09-07T07:51:10.6650102Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:51:10.6650637Z } 2025-09-07T07:51:10.6650845Z  2025-09-07T07:51:10.6651106Z retry () { 2025-09-07T07:51:10.6651381Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:51:10.6652002Z } 2025-09-07T07:51:10.6652272Z  2025-09-07T07:51:10.6652646Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:51:10.6652961Z  2025-09-07T07:51:10.6653451Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-09-07T07:51:10.6654132Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-09-07T07:51:10.6654512Z  2025-09-07T07:51:10.6654719Z set -e 2025-09-07T07:51:10.6655061Z # ignore output since only exit code is used for conditional 2025-09-07T07:51:10.6655561Z # only pull docker image if it's not available locally 2025-09-07T07:51:10.6656121Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-09-07T07:51:10.6656650Z  retry docker pull "${DOCKER_IMAGE}" 2025-09-07T07:51:10.6657023Z fi 2025-09-07T07:51:10.6673148Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:10.6673561Z env: 2025-09-07T07:51:10.6673828Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:10.6675136Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:10.6676288Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:10.6676705Z ##[endgroup] 2025-09-07T07:51:10.6825132Z + set +e 2025-09-07T07:51:10.6825482Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:10.6826250Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:10.6829150Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:51:10.6830794Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:11.4822901Z 2025-09-07T07:51:11.4823821Z WARNING! Your credentials are stored unencrypted in '/home/frank/.docker/config.json'. 2025-09-07T07:51:11.4824697Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:11.4825155Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:11.4825421Z 2025-09-07T07:51:11.4825518Z Login Succeeded 2025-09-07T07:51:11.4850005Z ++ 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 2025-09-07T07:51:11.4851244Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-09-07T07:51:11.7667606Z + IMAGE_SIZE=36183.606596946716 2025-09-07T07:51:11.7668022Z + echo 'Compressed size of image in MB: 36183.606596946716' 2025-09-07T07:51:11.7668410Z + set -e 2025-09-07T07:51:11.8658451Z + 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 2025-09-07T07:51:11.8660059Z Compressed size of image in MB: 36183.606596946716 2025-09-07T07:51:11.8661926Z + 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 2025-09-07T07:51:11.8664898Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:12.6692690Z pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image 2025-09-07T07:51:12.8444523Z e6fdc8487bfe: Pulling fs layer 2025-09-07T07:51:12.8445009Z 171dcef20c49: Pulling fs layer 2025-09-07T07:51:12.8445475Z 4c92b3f72f1d: Pulling fs layer 2025-09-07T07:51:12.8445905Z 744f9ba90a65: Pulling fs layer 2025-09-07T07:51:12.8446241Z d3c08322a332: Pulling fs layer 2025-09-07T07:51:12.8446673Z ffd43b71f3cc: Pulling fs layer 2025-09-07T07:51:12.8447025Z 830692b57f6e: Pulling fs layer 2025-09-07T07:51:12.8447431Z d3c08322a332: Waiting 2025-09-07T07:51:12.8447865Z ffd43b71f3cc: Waiting 2025-09-07T07:51:12.8448254Z 744f9ba90a65: Waiting 2025-09-07T07:51:12.8448524Z 5bad36d18468: Pulling fs layer 2025-09-07T07:51:12.8448915Z 830692b57f6e: Waiting 2025-09-07T07:51:12.8449200Z 0e34fdd9ac5c: Pulling fs layer 2025-09-07T07:51:12.8449533Z 0e34fdd9ac5c: Waiting 2025-09-07T07:51:12.8449858Z 3c868a62868e: Pulling fs layer 2025-09-07T07:51:12.8450132Z 5bad36d18468: Waiting 2025-09-07T07:51:12.8450488Z 3c868a62868e: Waiting 2025-09-07T07:51:12.8450776Z 62170a22dd57: Pulling fs layer 2025-09-07T07:51:12.8451127Z 553c1d23b6c4: Pulling fs layer 2025-09-07T07:51:12.8451493Z 9408d557a804: Pulling fs layer 2025-09-07T07:51:12.8451880Z df607cfc7c07: Pulling fs layer 2025-09-07T07:51:12.8452223Z 62170a22dd57: Waiting 2025-09-07T07:51:12.8452471Z 553c1d23b6c4: Waiting 2025-09-07T07:51:12.8452860Z 4f4fb700ef54: Pulling fs layer 2025-09-07T07:51:12.8453240Z 9408d557a804: Waiting 2025-09-07T07:51:12.8453633Z 40a8e39faeda: Pulling fs layer 2025-09-07T07:51:12.8453913Z d895771c9fac: Pulling fs layer 2025-09-07T07:51:12.8454313Z c4ee04f39d49: Pulling fs layer 2025-09-07T07:51:12.8454618Z 3690c9826e48: Pulling fs layer 2025-09-07T07:51:12.8454951Z 4f4fb700ef54: Waiting 2025-09-07T07:51:12.8455251Z 40a8e39faeda: Waiting 2025-09-07T07:51:12.8455501Z 57cbc5013733: Pulling fs layer 2025-09-07T07:51:12.8455899Z d895771c9fac: Waiting 2025-09-07T07:51:12.8456153Z c4ee04f39d49: Waiting 2025-09-07T07:51:12.8456437Z f5f4b06b58bb: Pulling fs layer 2025-09-07T07:51:12.8456799Z 3690c9826e48: Waiting 2025-09-07T07:51:12.8457053Z 57cbc5013733: Waiting 2025-09-07T07:51:12.8457449Z f59713ce4bf4: Pulling fs layer 2025-09-07T07:51:12.8457719Z f5f4b06b58bb: Waiting 2025-09-07T07:51:12.8458042Z fe0486521517: Pulling fs layer 2025-09-07T07:51:12.8458338Z 8c21cc3715a2: Pulling fs layer 2025-09-07T07:51:12.8458638Z d37c58456a6a: Pulling fs layer 2025-09-07T07:51:12.8458977Z d042f63abc13: Pulling fs layer 2025-09-07T07:51:12.8459256Z f59713ce4bf4: Waiting 2025-09-07T07:51:12.8459566Z 621284a9c05a: Pulling fs layer 2025-09-07T07:51:12.8459846Z fe0486521517: Waiting 2025-09-07T07:51:12.8460070Z 8c21cc3715a2: Waiting 2025-09-07T07:51:12.8460367Z d37c58456a6a: Waiting 2025-09-07T07:51:12.8460608Z d042f63abc13: Waiting 2025-09-07T07:51:12.8460906Z 85f605d2dd3a: Pulling fs layer 2025-09-07T07:51:12.8461230Z 621284a9c05a: Waiting 2025-09-07T07:51:12.8461479Z 381b5539e598: Pulling fs layer 2025-09-07T07:51:12.8461806Z a487c0c80029: Pulling fs layer 2025-09-07T07:51:12.8462112Z 48bcb81e2566: Pulling fs layer 2025-09-07T07:51:12.9142349Z 381b5539e598: Waiting 2025-09-07T07:51:12.9142607Z 85f605d2dd3a: Waiting 2025-09-07T07:51:12.9142907Z a487c0c80029: Waiting 2025-09-07T07:51:12.9143147Z 48bcb81e2566: Waiting 2025-09-07T07:51:12.9143383Z e261928c0043: Pulling fs layer 2025-09-07T07:51:12.9143723Z 0fea55428091: Pulling fs layer 2025-09-07T07:51:12.9144224Z e261928c0043: Waiting 2025-09-07T07:51:12.9144528Z 0fea55428091: Waiting 2025-09-07T07:51:12.9144769Z b4291bccbb84: Pulling fs layer 2025-09-07T07:51:12.9145068Z ddc91b09189a: Pulling fs layer 2025-09-07T07:51:12.9145390Z b4291bccbb84: Waiting 2025-09-07T07:51:12.9145639Z 7540c7428627: Pulling fs layer 2025-09-07T07:51:12.9145954Z ddc91b09189a: Waiting 2025-09-07T07:51:12.9146193Z 7540c7428627: Waiting 2025-09-07T07:51:12.9146439Z 003c4e2598fb: Pulling fs layer 2025-09-07T07:51:12.9146772Z 5687149362ae: Pulling fs layer 2025-09-07T07:51:12.9161172Z cdd2cf54eb2a: Pulling fs layer 2025-09-07T07:51:12.9161513Z d3ad4df1ba3a: Pulling fs layer 2025-09-07T07:51:12.9161883Z 3c9055753b4c: Pulling fs layer 2025-09-07T07:51:12.9162176Z 31cf8d0bd21c: Pulling fs layer 2025-09-07T07:51:12.9162511Z 003c4e2598fb: Waiting 2025-09-07T07:51:12.9162759Z 5687149362ae: Waiting 2025-09-07T07:51:12.9163302Z cdd2cf54eb2a: Waiting 2025-09-07T07:51:12.9163555Z d3ad4df1ba3a: Waiting 2025-09-07T07:51:12.9163872Z 3c9055753b4c: Waiting 2025-09-07T07:51:12.9164109Z 6623ea814971: Pulling fs layer 2025-09-07T07:51:12.9164394Z 11696c3aa380: Pulling fs layer 2025-09-07T07:51:12.9164746Z ef4d544e35ca: Pulling fs layer 2025-09-07T07:51:12.9165024Z 31cf8d0bd21c: Waiting 2025-09-07T07:51:12.9165314Z ef4d544e35ca: Waiting 2025-09-07T07:51:12.9165559Z 6623ea814971: Waiting 2025-09-07T07:51:12.9165797Z 11696c3aa380: Waiting 2025-09-07T07:51:12.9166100Z 5c5108865e5e: Pulling fs layer 2025-09-07T07:51:12.9166512Z 9e97578e9edf: Pulling fs layer 2025-09-07T07:51:12.9166848Z da5a91b54cb5: Pulling fs layer 2025-09-07T07:51:12.9167130Z 5c5108865e5e: Waiting 2025-09-07T07:51:12.9167382Z 1e93be219e89: Pulling fs layer 2025-09-07T07:51:12.9167731Z 9e97578e9edf: Waiting 2025-09-07T07:51:12.9167960Z da5a91b54cb5: Waiting 2025-09-07T07:51:12.9168262Z 1e93be219e89: Waiting 2025-09-07T07:51:12.9168565Z 136825afebb5: Pulling fs layer 2025-09-07T07:51:12.9168850Z 22b39805302d: Pulling fs layer 2025-09-07T07:51:12.9169184Z d12add675e35: Pulling fs layer 2025-09-07T07:51:12.9169473Z bc127046d33a: Pulling fs layer 2025-09-07T07:51:12.9169746Z d12add675e35: Waiting 2025-09-07T07:51:12.9170045Z 136825afebb5: Waiting 2025-09-07T07:51:12.9170276Z 22b39805302d: Waiting 2025-09-07T07:51:12.9170514Z bc127046d33a: Waiting 2025-09-07T07:51:12.9170824Z 951e8ce83841: Pulling fs layer 2025-09-07T07:51:12.9171114Z 32340b97ae50: Pulling fs layer 2025-09-07T07:51:12.9171427Z 951e8ce83841: Waiting 2025-09-07T07:51:12.9171672Z 32340b97ae50: Waiting 2025-09-07T07:51:12.9171927Z 5bbb04cd6b57: Pulling fs layer 2025-09-07T07:51:12.9172262Z 5bbb04cd6b57: Waiting 2025-09-07T07:51:12.9172500Z d8c4b845cfc7: Pulling fs layer 2025-09-07T07:51:12.9172795Z b35c180f4d8d: Pulling fs layer 2025-09-07T07:51:12.9173149Z 5f967b3c303a: Pulling fs layer 2025-09-07T07:51:12.9173427Z d8c4b845cfc7: Waiting 2025-09-07T07:51:12.9173703Z b35c180f4d8d: Waiting 2025-09-07T07:51:12.9173956Z 5f967b3c303a: Waiting 2025-09-07T07:51:12.9174203Z 04770904f012: Pulling fs layer 2025-09-07T07:51:12.9174616Z 73373941fb32: Pulling fs layer 2025-09-07T07:51:12.9174908Z 9572e6cd907b: Pulling fs layer 2025-09-07T07:51:12.9175236Z 64a544aba233: Pulling fs layer 2025-09-07T07:51:12.9175531Z 04770904f012: Waiting 2025-09-07T07:51:12.9175752Z 73373941fb32: Waiting 2025-09-07T07:51:12.9176050Z 9572e6cd907b: Waiting 2025-09-07T07:51:12.9176289Z 64a544aba233: Waiting 2025-09-07T07:51:12.9176541Z 7e35418a2499: Pulling fs layer 2025-09-07T07:51:12.9176871Z 2ed8e82748d4: Pulling fs layer 2025-09-07T07:51:12.9177148Z 7e35418a2499: Waiting 2025-09-07T07:51:12.9177566Z c988fbcccd70: Pulling fs layer 2025-09-07T07:51:12.9177851Z c988fbcccd70: Waiting 2025-09-07T07:51:12.9178137Z 2ed8e82748d4: Waiting 2025-09-07T07:51:12.9225964Z 171dcef20c49: Verifying Checksum 2025-09-07T07:51:12.9226353Z 171dcef20c49: Download complete 2025-09-07T07:51:13.1245542Z 744f9ba90a65: Download complete 2025-09-07T07:51:13.2080582Z d3c08322a332: Download complete 2025-09-07T07:51:13.2890572Z ffd43b71f3cc: Verifying Checksum 2025-09-07T07:51:13.2891682Z ffd43b71f3cc: Download complete 2025-09-07T07:51:13.2916714Z e6fdc8487bfe: Verifying Checksum 2025-09-07T07:51:13.2917207Z e6fdc8487bfe: Download complete 2025-09-07T07:51:13.3673191Z 830692b57f6e: Verifying Checksum 2025-09-07T07:51:13.3673776Z 830692b57f6e: Download complete 2025-09-07T07:51:13.3896729Z 5bad36d18468: Verifying Checksum 2025-09-07T07:51:13.3897228Z 5bad36d18468: Download complete 2025-09-07T07:51:13.4730529Z 3c868a62868e: Verifying Checksum 2025-09-07T07:51:13.4730905Z 3c868a62868e: Download complete 2025-09-07T07:51:13.5315866Z 62170a22dd57: Verifying Checksum 2025-09-07T07:51:13.5316262Z 62170a22dd57: Download complete 2025-09-07T07:51:13.6106951Z 553c1d23b6c4: Download complete 2025-09-07T07:51:13.7938870Z 9408d557a804: Verifying Checksum 2025-09-07T07:51:13.7939470Z 9408d557a804: Download complete 2025-09-07T07:51:16.5645930Z 0e34fdd9ac5c: Verifying Checksum 2025-09-07T07:51:16.5646333Z 0e34fdd9ac5c: Download complete 2025-09-07T07:51:16.5776247Z 4f4fb700ef54: Verifying Checksum 2025-09-07T07:51:16.5776734Z 4f4fb700ef54: Download complete 2025-09-07T07:51:16.8144560Z 40a8e39faeda: Verifying Checksum 2025-09-07T07:51:16.8144972Z 40a8e39faeda: Download complete 2025-09-07T07:51:18.6329423Z d895771c9fac: Verifying Checksum 2025-09-07T07:51:18.6330038Z d895771c9fac: Download complete 2025-09-07T07:51:18.7960097Z c4ee04f39d49: Verifying Checksum 2025-09-07T07:51:18.7960494Z c4ee04f39d49: Download complete 2025-09-07T07:51:19.0524654Z 3690c9826e48: Verifying Checksum 2025-09-07T07:51:19.0525349Z 3690c9826e48: Download complete 2025-09-07T07:51:19.2048568Z 57cbc5013733: Verifying Checksum 2025-09-07T07:51:19.2048972Z 57cbc5013733: Download complete 2025-09-07T07:51:19.3182785Z f5f4b06b58bb: Verifying Checksum 2025-09-07T07:51:19.3183161Z f5f4b06b58bb: Download complete 2025-09-07T07:51:19.4022428Z f59713ce4bf4: Verifying Checksum 2025-09-07T07:51:19.4023086Z f59713ce4bf4: Download complete 2025-09-07T07:51:19.5614745Z fe0486521517: Verifying Checksum 2025-09-07T07:51:19.5615372Z fe0486521517: Download complete 2025-09-07T07:51:20.0479471Z e6fdc8487bfe: Pull complete 2025-09-07T07:51:20.3838155Z 4c92b3f72f1d: Verifying Checksum 2025-09-07T07:51:20.3838806Z 4c92b3f72f1d: Download complete 2025-09-07T07:51:20.5361042Z d37c58456a6a: Verifying Checksum 2025-09-07T07:51:20.5361447Z d37c58456a6a: Download complete 2025-09-07T07:51:21.8070277Z 171dcef20c49: Pull complete 2025-09-07T07:51:21.8505753Z d042f63abc13: Verifying Checksum 2025-09-07T07:51:21.8506132Z d042f63abc13: Download complete 2025-09-07T07:51:21.9494085Z 621284a9c05a: Verifying Checksum 2025-09-07T07:51:21.9494470Z 621284a9c05a: Download complete 2025-09-07T07:51:22.0584360Z 85f605d2dd3a: Verifying Checksum 2025-09-07T07:51:22.0585056Z 85f605d2dd3a: Download complete 2025-09-07T07:51:29.3936134Z 381b5539e598: Verifying Checksum 2025-09-07T07:51:29.3936633Z 381b5539e598: Download complete 2025-09-07T07:51:29.4764233Z a487c0c80029: Verifying Checksum 2025-09-07T07:51:29.4764640Z a487c0c80029: Download complete 2025-09-07T07:51:29.5616247Z 48bcb81e2566: Verifying Checksum 2025-09-07T07:51:29.5616643Z 48bcb81e2566: Download complete 2025-09-07T07:51:29.6441566Z e261928c0043: Verifying Checksum 2025-09-07T07:51:29.6442183Z e261928c0043: Download complete 2025-09-07T07:51:29.7186916Z 0fea55428091: Verifying Checksum 2025-09-07T07:51:29.7187257Z 0fea55428091: Download complete 2025-09-07T07:51:29.9934754Z b4291bccbb84: Verifying Checksum 2025-09-07T07:51:29.9935228Z b4291bccbb84: Download complete 2025-09-07T07:51:30.1010404Z ddc91b09189a: Verifying Checksum 2025-09-07T07:51:30.1010987Z ddc91b09189a: Download complete 2025-09-07T07:51:30.1877962Z 7540c7428627: Verifying Checksum 2025-09-07T07:51:30.1878750Z 7540c7428627: Download complete 2025-09-07T07:51:30.2642341Z 003c4e2598fb: Verifying Checksum 2025-09-07T07:51:30.2642735Z 003c4e2598fb: Download complete 2025-09-07T07:51:30.3493421Z 5687149362ae: Download complete 2025-09-07T07:51:30.4251452Z cdd2cf54eb2a: Verifying Checksum 2025-09-07T07:51:30.4251880Z cdd2cf54eb2a: Download complete 2025-09-07T07:51:44.7659132Z 4c92b3f72f1d: Pull complete 2025-09-07T07:51:46.0007339Z 744f9ba90a65: Pull complete 2025-09-07T07:51:47.1311480Z d3c08322a332: Pull complete 2025-09-07T07:51:48.1201134Z ffd43b71f3cc: Pull complete 2025-09-07T07:51:48.6689155Z 830692b57f6e: Pull complete 2025-09-07T07:51:50.1614806Z 5bad36d18468: Pull complete 2025-09-07T07:51:58.1486992Z 0e34fdd9ac5c: Pull complete 2025-09-07T07:52:00.5141023Z 3c868a62868e: Pull complete 2025-09-07T07:52:02.0258077Z 62170a22dd57: Pull complete 2025-09-07T07:52:03.5275273Z 553c1d23b6c4: Pull complete 2025-09-07T07:52:04.8349056Z 9408d557a804: Pull complete 2025-09-07T07:52:05.4137415Z df607cfc7c07: Verifying Checksum 2025-09-07T07:52:05.4137859Z df607cfc7c07: Download complete 2025-09-07T07:52:05.5394470Z 3c9055753b4c: Verifying Checksum 2025-09-07T07:52:05.5394925Z 3c9055753b4c: Download complete 2025-09-07T07:52:09.4808474Z 31cf8d0bd21c: Verifying Checksum 2025-09-07T07:52:09.4809133Z 31cf8d0bd21c: Download complete 2025-09-07T07:53:28.0935631Z 8c21cc3715a2: Verifying Checksum 2025-09-07T07:53:28.0936077Z 8c21cc3715a2: Download complete 2025-09-07T07:53:28.1707623Z 11696c3aa380: Verifying Checksum 2025-09-07T07:53:28.1707996Z 11696c3aa380: Download complete 2025-09-07T07:53:28.2491648Z ef4d544e35ca: Verifying Checksum 2025-09-07T07:53:28.2491996Z ef4d544e35ca: Download complete 2025-09-07T07:53:28.3351351Z 5c5108865e5e: Verifying Checksum 2025-09-07T07:53:28.3351695Z 5c5108865e5e: Download complete 2025-09-07T07:53:28.4157092Z 9e97578e9edf: Verifying Checksum 2025-09-07T07:53:28.4157438Z 9e97578e9edf: Download complete 2025-09-07T07:53:28.4967944Z da5a91b54cb5: Verifying Checksum 2025-09-07T07:53:28.4968301Z da5a91b54cb5: Download complete 2025-09-07T07:53:28.5721704Z 1e93be219e89: Verifying Checksum 2025-09-07T07:53:28.5722057Z 1e93be219e89: Download complete 2025-09-07T07:53:28.6446027Z 136825afebb5: Verifying Checksum 2025-09-07T07:53:28.6446361Z 136825afebb5: Download complete 2025-09-07T07:53:28.6965711Z 22b39805302d: Verifying Checksum 2025-09-07T07:53:28.6966090Z 22b39805302d: Download complete 2025-09-07T07:53:28.7715630Z d12add675e35: Verifying Checksum 2025-09-07T07:53:28.7715980Z d12add675e35: Download complete 2025-09-07T07:53:28.8406049Z bc127046d33a: Verifying Checksum 2025-09-07T07:53:28.8406394Z bc127046d33a: Download complete 2025-09-07T07:53:28.9070215Z 951e8ce83841: Verifying Checksum 2025-09-07T07:53:28.9070560Z 951e8ce83841: Download complete 2025-09-07T07:53:28.9836351Z 32340b97ae50: Verifying Checksum 2025-09-07T07:53:28.9836684Z 32340b97ae50: Download complete 2025-09-07T07:53:29.0553192Z 5bbb04cd6b57: Verifying Checksum 2025-09-07T07:53:29.0553552Z 5bbb04cd6b57: Download complete 2025-09-07T07:53:29.1318293Z d8c4b845cfc7: Verifying Checksum 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2025-09-07T08:47:21.5514610Z 04770904f012: Pull complete 2025-09-07T08:47:23.9860794Z 73373941fb32: Pull complete 2025-09-07T08:47:26.8558775Z 9572e6cd907b: Pull complete 2025-09-07T08:47:29.6762932Z 64a544aba233: Pull complete 2025-09-07T08:47:32.7223266Z 7e35418a2499: Pull complete 2025-09-07T08:47:34.8396268Z 2ed8e82748d4: Pull complete 2025-09-07T08:47:40.0811517Z c988fbcccd70: Pull complete 2025-09-07T08:47:43.7542395Z Digest: sha256:f30843ff9ea9e117a2c8e6d207e85c9e77dfe682f1dfcdfea5b94178d1bf00b3 2025-09-07T08:47:44.1629846Z 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 2025-09-07T08:47:44.2729396Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:47:44.2906526Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:47:44.2907740Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:47:44.2920849Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:47:44.2921250Z env: 2025-09-07T08:47:44.2921462Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:47:44.2921730Z ##[endgroup] 2025-09-07T08:47:44.4005970Z ##[group]Run echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:47:44.4006873Z echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:47:44.4020533Z shell: /usr/bin/bash -e {0} 2025-09-07T08:47:44.4020940Z env: 2025-09-07T08:47:44.4021162Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:47:44.4021424Z ##[endgroup] 2025-09-07T08:47:44.5053592Z ##[group]Run echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:47:44.5054469Z echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:47:44.5066378Z shell: /usr/bin/bash -e {0} 2025-09-07T08:47:44.5066667Z env: 2025-09-07T08:47:44.5066889Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:47:44.5067228Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:47:44.5067581Z ##[endgroup] 2025-09-07T08:47:44.5607437Z Prepare all required actions 2025-09-07T08:47:44.6104029Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-09-07T08:47:44.6104388Z with: 2025-09-07T08:47:44.6104814Z github-token: *** 2025-09-07T08:47:44.6105035Z env: 2025-09-07T08:47:44.6105251Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:47:44.6105588Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:47:44.6106059Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:47:44.6106440Z ##[endgroup] 2025-09-07T08:47:44.6672525Z ##[group]Run set -eux 2025-09-07T08:47:44.6672799Z set -eux 2025-09-07T08:47:44.6673250Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T08:47:44.6685186Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:47:44.6685565Z env: 2025-09-07T08:47:44.6685788Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:47:44.6686126Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:47:44.6686627Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:47:44.6687226Z GITHUB_TOKEN: *** 2025-09-07T08:47:44.6687468Z ##[endgroup] 2025-09-07T08:47:44.7202748Z + python3 .github/scripts/get_workflow_job_id.py 17525309334 i-03028b1668c838483-1006 2025-09-07T08:47:45.5055348Z Setting output job-id=49775768420 2025-09-07T08:47:45.5055958Z Setting output job-name=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T08:47:45.5381240Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:47:45.5382005Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:47:45.5383007Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-09-07T08:47:45.5383889Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-09-07T08:47:45.5396775Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:47:45.5397170Z env: 2025-09-07T08:47:45.5397397Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:47:45.5397735Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:47:45.5398199Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:47:45.5398590Z JOB_ID: 49775768420 2025-09-07T08:47:45.5399088Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T08:47:45.5399633Z WORKFLOW_NAME: inductor-A100-perf-nightly 2025-09-07T08:47:45.5399963Z WORKFLOW_RUN_ID: 17525309334 2025-09-07T08:47:45.5400450Z MONITOR_LOG_INTERVAL: 15 2025-09-07T08:47:45.5400735Z MONITOR_DATA_COLLECT_INTERVAL: 4 2025-09-07T08:47:45.5401032Z ##[endgroup] 2025-09-07T08:47:45.9107184Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:47:46.3950762Z Collecting psutil==5.9.8 2025-09-07T08:47:46.4640355Z 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) 2025-09-07T08:47:46.8194673Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 KB 788.2 kB/s eta 0:00:00 2025-09-07T08:47:47.0981552Z Collecting dataclasses_json==0.6.7 2025-09-07T08:47:47.1075554Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-09-07T08:47:47.7215473Z Collecting nvidia-ml-py==11.525.84 2025-09-07T08:47:47.7307214Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-09-07T08:47:48.4437299Z Collecting marshmallow<4.0.0,>=3.18.0 2025-09-07T08:47:48.4530996Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-09-07T08:47:48.6383888Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 50.9/50.9 KB 222.0 kB/s eta 0:00:00 2025-09-07T08:47:48.8145375Z Collecting typing-inspect<1,>=0.4.0 2025-09-07T08:47:48.8236226Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-09-07T08:47:49.2668835Z Collecting packaging>=17.0 2025-09-07T08:47:49.2760176Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-09-07T08:47:49.5353425Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 66.5/66.5 KB 218.6 kB/s eta 0:00:00 2025-09-07T08:47:49.7304532Z Collecting mypy-extensions>=0.3.0 2025-09-07T08:47:49.7394750Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-09-07T08:47:50.3119339Z Collecting typing-extensions>=3.7.4 2025-09-07T08:47:50.3211316Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-09-07T08:47:50.5438177Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.6/44.6 KB 156.1 kB/s eta 0:00:00 2025-09-07T08:47:50.6265928Z Installing collected packages: nvidia-ml-py, typing-extensions, psutil, packaging, mypy-extensions, typing-inspect, marshmallow, dataclasses_json 2025-09-07T08:47:54.0909080Z 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 2025-09-07T08:47:54.1627217Z Prepare all required actions 2025-09-07T08:47:54.1627600Z Getting action download info 2025-09-07T08:47:54.2954655Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-09-07T08:47:57.0697046Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-09-07T08:48:05.9265287Z ##[group]Run ./.github/actions/download-build-artifacts 2025-09-07T08:48:05.9265669Z with: 2025-09-07T08:48:05.9265921Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:48:05.9266252Z s3-bucket: gha-artifacts 2025-09-07T08:48:05.9266516Z env: 2025-09-07T08:48:05.9266752Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:05.9267083Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:05.9267535Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:05.9267926Z ##[endgroup] 2025-09-07T08:48:05.9774817Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:48:05.9775179Z with: 2025-09-07T08:48:05.9775423Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:48:05.9775771Z s3-bucket: gha-artifacts 2025-09-07T08:48:05.9776040Z region: us-east-1 2025-09-07T08:48:05.9776258Z env: 2025-09-07T08:48:05.9776473Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:05.9776807Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:05.9777367Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:05.9777764Z ##[endgroup] 2025-09-07T08:48:06.4405561Z (node:9492) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:48:06.4406420Z 2025-09-07T08:48:06.4406626Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:48:06.4407163Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:48:06.4407750Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:48:06.5413442Z Found 1 objects with prefix pytorch/pytorch/17525309334/linux-jammy-cuda12.8-py3.10-gcc9-sm80/ 2025-09-07T08:48:06.5414161Z Starting download (1/1): /home/frank/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:48:17.4755452Z Finished download (1/1): /home/frank/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:48:17.4764246Z Artifact download has finished successfully 2025-09-07T08:48:17.5529605Z ##[group]Run unzip -o artifacts.zip 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build/bin/test_jit 2025-09-07T08:48:29.8328764Z inflating: build/bin/ProcessGroupGlooTest 2025-09-07T08:48:29.8390797Z inflating: build/bin/ProcessGroupGlooAsyncTest 2025-09-07T08:48:29.8745507Z inflating: build/bin/test_lazy 2025-09-07T08:48:29.8749297Z inflating: build/bin/torch_shm_manager 2025-09-07T08:48:29.8749644Z creating: .additional_ci_files/ 2025-09-07T08:48:29.8839089Z inflating: .additional_ci_files/test-times.json 2025-09-07T08:48:29.9179222Z inflating: .additional_ci_files/test-class-times.json 2025-09-07T08:48:29.9605280Z ##[group]Run rm artifacts.zip 2025-09-07T08:48:29.9605591Z rm artifacts.zip 2025-09-07T08:48:29.9618489Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:29.9618888Z env: 2025-09-07T08:48:29.9619117Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:29.9619445Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:29.9619921Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:29.9620323Z ##[endgroup] 2025-09-07T08:48:30.1185910Z ##[group]Run df -H 2025-09-07T08:48:30.1186151Z df -H 2025-09-07T08:48:30.1197965Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:30.1198356Z env: 2025-09-07T08:48:30.1198573Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:30.1198897Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:30.1199356Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:30.1199750Z ##[endgroup] 2025-09-07T08:48:30.1731264Z Filesystem Size Used Avail Use% Mounted on 2025-09-07T08:48:30.1731649Z overlay 5.3T 529G 4.7T 11% / 2025-09-07T08:48:30.1732174Z tmpfs 68M 0 68M 0% /dev 2025-09-07T08:48:30.1732507Z shm 68M 0 68M 0% /dev/shm 2025-09-07T08:48:30.1732877Z /dev/root 5.3T 529G 4.7T 11% /home/frank/_work 2025-09-07T08:48:30.1733403Z tmpfs 121G 111k 121G 1% /run/docker.sock 2025-09-07T08:48:30.1733794Z tmpfs 603G 13k 603G 1% /proc/driver/nvidia 2025-09-07T08:48:30.1734252Z tmpfs 241G 1.7M 241G 1% /run/.ro3529841866/nvidia-persistenced/socket 2025-09-07T08:48:30.1734709Z tmpfs 603G 0 603G 0% /proc/acpi 2025-09-07T08:48:30.1735063Z tmpfs 603G 0 603G 0% /proc/scsi 2025-09-07T08:48:30.1735412Z tmpfs 603G 0 603G 0% /sys/firmware 2025-09-07T08:48:30.1768058Z Prepare all required actions 2025-09-07T08:48:30.1768705Z Getting action download info 2025-09-07T08:48:30.3195886Z ##[group]Run ./.github/actions/download-td-artifacts 2025-09-07T08:48:30.3196248Z with: 2025-09-07T08:48:30.3196466Z env: 2025-09-07T08:48:30.3196682Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:30.3197005Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:30.3197465Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:30.3197858Z ##[endgroup] 2025-09-07T08:48:30.3720422Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:48:30.3720759Z with: 2025-09-07T08:48:30.3720975Z name: td_results 2025-09-07T08:48:30.3721225Z s3-bucket: gha-artifacts 2025-09-07T08:48:30.3721498Z region: us-east-1 2025-09-07T08:48:30.3721717Z env: 2025-09-07T08:48:30.3721934Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:30.3722270Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:30.3722988Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:30.3723391Z ##[endgroup] 2025-09-07T08:48:30.8281821Z (node:9513) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:48:30.8282364Z 2025-09-07T08:48:30.8282553Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:48:30.8283214Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:48:30.8283790Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:48:30.9177869Z Found 0 objects with prefix pytorch/pytorch/17525309334/td_results/ 2025-09-07T08:48:30.9183907Z Artifact download has finished successfully 2025-09-07T08:48:30.9518900Z ##[group]Run mkdir -p .additional_ci_files 2025-09-07T08:48:30.9519286Z mkdir -p .additional_ci_files 2025-09-07T08:48:30.9519728Z mv td_results.json .additional_ci_files/td_results.json || true 2025-09-07T08:48:30.9532626Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:30.9533010Z env: 2025-09-07T08:48:30.9533233Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:30.9533571Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:30.9534033Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:30.9534428Z ##[endgroup] 2025-09-07T08:48:31.0021465Z mv: cannot stat 'td_results.json': No such file or directory 2025-09-07T08:48:31.0438255Z ##[group]Run .github/scripts/parse_ref.py 2025-09-07T08:48:31.0438623Z .github/scripts/parse_ref.py 2025-09-07T08:48:31.0450824Z shell: /usr/bin/bash -e {0} 2025-09-07T08:48:31.0451118Z env: 2025-09-07T08:48:31.0451343Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:31.0451670Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:31.0452138Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:31.0452531Z ##[endgroup] 2025-09-07T08:48:31.1104346Z Setting output branch=main 2025-09-07T08:48:31.1244028Z Prepare all required actions 2025-09-07T08:48:31.1244423Z Getting action download info 2025-09-07T08:48:31.2497793Z ##[group]Run ./.github/actions/filter-test-configs 2025-09-07T08:48:31.2498186Z with: 2025-09-07T08:48:31.2498578Z github-token: *** 2025-09-07T08:48:31.2504587Z test-matrix: {"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]} 2025-09-07T08:48:31.2510707Z job-name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T08:48:31.2511210Z env: 2025-09-07T08:48:31.2511432Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:31.2511757Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:31.2512207Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:31.2512596Z ##[endgroup] 2025-09-07T08:48:31.3004139Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T08:48:31.3004445Z with: 2025-09-07T08:48:31.3004631Z shell: bash 2025-09-07T08:48:31.3004849Z timeout_minutes: 10 2025-09-07T08:48:31.3005084Z max_attempts: 5 2025-09-07T08:48:31.3005322Z retry_wait_seconds: 30 2025-09-07T08:48:31.3006128Z 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 2025-09-07T08:48:31.3006970Z polling_interval_seconds: 1 2025-09-07T08:48:31.3007250Z warning_on_retry: true 2025-09-07T08:48:31.3007507Z continue_on_error: false 2025-09-07T08:48:31.3007754Z env: 2025-09-07T08:48:31.3007947Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:31.3008278Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:31.3008734Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:31.3009278Z GITHUB_TOKEN: *** 2025-09-07T08:48:31.3009497Z ##[endgroup] 2025-09-07T08:48:31.3770398Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:48:31.6813505Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:48:32.0724658Z Collecting requests==2.27.1 2025-09-07T08:48:32.1393152Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-09-07T08:48:32.4246957Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 187.2 kB/s eta 0:00:00 2025-09-07T08:48:32.8098987Z Collecting pyyaml==6.0.2 2025-09-07T08:48:32.8183674Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-09-07T08:48:33.1683160Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 2.1 MB/s eta 0:00:00 2025-09-07T08:48:33.5372200Z Collecting charset-normalizer~=2.0.0 2025-09-07T08:48:33.5456690Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-09-07T08:48:33.7242007Z Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.27.1) (2020.6.20) 2025-09-07T08:48:33.7247830Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.27.1) (1.26.5) 2025-09-07T08:48:33.7259803Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.27.1) (3.3) 2025-09-07T08:48:33.8023921Z Installing collected packages: pyyaml, charset-normalizer, requests 2025-09-07T08:48:34.1456875Z WARNING: The script normalizer is installed in '/home/frank/.local/bin' which is not on PATH. 2025-09-07T08:48:34.1457799Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T08:48:35.1251745Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-09-07T08:48:35.3760917Z Command completed after 1 attempt(s). 2025-09-07T08:48:35.4120147Z ##[group]Run set -x 2025-09-07T08:48:35.4120421Z set -x 2025-09-07T08:48:35.4120655Z  2025-09-07T08:48:35.4121040Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:48:35.4121541Z # in runner workspace 2025-09-07T08:48:35.4121939Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-09-07T08:48:35.4135766Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:35.4136170Z env: 2025-09-07T08:48:35.4136395Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:35.4136757Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:35.4137322Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:35.4137719Z ##[endgroup] 2025-09-07T08:48:35.4584745Z + python3 /home/frank/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-09-07T08:48:35.4735330Z Setting output branch=main 2025-09-07T08:48:35.5079674Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:48:35.5080110Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:48:35.5080453Z echo "Job name: ${JOB_NAME}" 2025-09-07T08:48:35.5080754Z  2025-09-07T08:48:35.5081140Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:48:35.5081620Z # in runner workspace 2025-09-07T08:48:35.5082055Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-09-07T08:48:35.5082549Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-09-07T08:48:35.5083186Z  --job-name "${JOB_NAME}" \ 2025-09-07T08:48:35.5089156Z  --test-matrix "{"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]}" \ 2025-09-07T08:48:35.5095372Z  --selected-test-configs "" \ 2025-09-07T08:48:35.5095719Z  --pr-number "${PR_NUMBER}" \ 2025-09-07T08:48:35.5096033Z  --tag "${TAG}" \ 2025-09-07T08:48:35.5096331Z  --event-name "${EVENT_NAME}" \ 2025-09-07T08:48:35.5096662Z  --schedule "${SCHEDULE}" \ 2025-09-07T08:48:35.5096982Z  --branch "${HEAD_BRANCH}" 2025-09-07T08:48:35.5109048Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:35.5109432Z env: 2025-09-07T08:48:35.5109658Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:35.5109993Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:35.5110456Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:35.5111037Z GITHUB_TOKEN: *** 2025-09-07T08:48:35.5111466Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T08:48:35.5111972Z PR_NUMBER: 2025-09-07T08:48:35.5112193Z TAG: 2025-09-07T08:48:35.5112407Z EVENT_NAME: schedule 2025-09-07T08:48:35.5112642Z SCHEDULE: 0 7 * * 0 2025-09-07T08:48:35.5112889Z HEAD_BRANCH: main 2025-09-07T08:48:35.5113137Z ##[endgroup] 2025-09-07T08:48:35.5586179Z Workflow: inductor-A100-perf-nightly 2025-09-07T08:48:35.5586721Z Job name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T08:48:35.7099528Z Setting output keep-going=True 2025-09-07T08:48:35.7099897Z Setting output ci-verbose-test-logs=False 2025-09-07T08:48:35.7100252Z Setting output ci-test-showlocals=False 2025-09-07T08:48:35.7100599Z Setting output ci-no-test-timeout=False 2025-09-07T08:48:35.7100915Z Setting output ci-no-td=False 2025-09-07T08:48:35.7101224Z Setting output ci-td-distributed=False 2025-09-07T08:48:35.7101554Z Setting output is-unstable=False 2025-09-07T08:48:35.7101865Z Setting output reenabled-issues= 2025-09-07T08:48:35.7107970Z Setting output test-matrix={"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]} 2025-09-07T08:48:35.7114230Z Setting output is-test-matrix-empty=False 2025-09-07T08:48:35.7547982Z ##[group]Run echo "Filtered matrix:" 2025-09-07T08:48:35.7548344Z echo "Filtered matrix:" 2025-09-07T08:48:35.7554156Z echo "{"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]}" 2025-09-07T08:48:35.7560119Z  2025-09-07T08:48:35.7560322Z echo 2025-09-07T08:48:35.7560600Z echo "Is the current job unstable? False" 2025-09-07T08:48:35.7560938Z  2025-09-07T08:48:35.7561127Z echo 2025-09-07T08:48:35.7561384Z echo "Is keep-going label set? True" 2025-09-07T08:48:35.7561704Z  2025-09-07T08:48:35.7561910Z echo 2025-09-07T08:48:35.7562131Z echo "Reenabled issues? " 2025-09-07T08:48:35.7574617Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:35.7575016Z env: 2025-09-07T08:48:35.7575241Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:35.7575581Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:35.7576039Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:35.7576429Z ##[endgroup] 2025-09-07T08:48:35.8053387Z Filtered matrix: 2025-09-07T08:48:35.8060263Z {include: [{config: inductor_huggingface_perf, shard: 1, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 2, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 3, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 4, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 5, num_shards: 5, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 1, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 2, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 3, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 4, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 5, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 6, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 1, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 2, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 3, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 4, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 5, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 6, num_shards: 6, runner: linux.aws.a100}, {config: cachebench, shard: 1, num_shards: 2, runner: linux.aws.a100}, {config: cachebench, shard: 2, num_shards: 2, runner: linux.aws.a100}]} 2025-09-07T08:48:35.8066145Z 2025-09-07T08:48:35.8066267Z Is the current job unstable? False 2025-09-07T08:48:35.8066472Z 2025-09-07T08:48:35.8066578Z Is keep-going label set? True 2025-09-07T08:48:35.8066775Z 2025-09-07T08:48:35.8066869Z Reenabled issues? 2025-09-07T08:48:35.8486436Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:48:35.8486977Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:48:35.8498602Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:35.8499001Z env: 2025-09-07T08:48:35.8499226Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:35.8499570Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:35.8500037Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:35.8500424Z JOB_TIMEOUT: 1440 2025-09-07T08:48:35.8500662Z ##[endgroup] 2025-09-07T08:48:35.9472787Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:48:35.9473347Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:48:35.9473808Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:48:35.9485602Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:48:35.9486012Z env: 2025-09-07T08:48:35.9486239Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:35.9486580Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:35.9487028Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:35.9487419Z ##[endgroup] 2025-09-07T08:48:36.0450759Z ##[group]Run set -x 2025-09-07T08:48:36.0451109Z set -x 2025-09-07T08:48:36.0451335Z  2025-09-07T08:48:36.0451581Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-09-07T08:48:36.0451983Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-09-07T08:48:36.0452398Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-09-07T08:48:36.0452771Z  TEST_COMMAND=.ci/onnx/test.sh 2025-09-07T08:48:36.0453071Z else 2025-09-07T08:48:36.0453331Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:48:36.0453649Z fi 2025-09-07T08:48:36.0453860Z  2025-09-07T08:48:36.0454113Z # Leaving 1GB for the runner and other things 2025-09-07T08:48:36.0454721Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-09-07T08:48:36.0455626Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-09-07T08:48:36.0456361Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-09-07T08:48:36.0456899Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-09-07T08:48:36.0457438Z  2025-09-07T08:48:36.0457716Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:48:36.0458079Z  SHM_OPTS= 2025-09-07T08:48:36.0458327Z  JENKINS_USER= 2025-09-07T08:48:36.0458693Z  # ensure that docker container cleanly exits in 12 hours 2025-09-07T08:48:36.0459190Z  # if for some reason cleanup action doesn't stop container 2025-09-07T08:48:36.0459607Z  # when job is cancelled 2025-09-07T08:48:36.0460130Z  DOCKER_SHELL_CMD="sleep 12h" 2025-09-07T08:48:36.0460430Z else 2025-09-07T08:48:36.0460690Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-09-07T08:48:36.0461042Z  JENKINS_USER="--user jenkins" 2025-09-07T08:48:36.0461374Z  DOCKER_SHELL_CMD= 2025-09-07T08:48:36.0461627Z fi 2025-09-07T08:48:36.0474738Z  2025-09-07T08:48:36.0475110Z # detached container should get cleaned up by teardown_ec2_linux 2025-09-07T08:48:36.0475660Z # TODO: Stop building test binaries as part of the build phase 2025-09-07T08:48:36.0476270Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-09-07T08:48:36.0476820Z # shellcheck disable=SC2086,SC2090 2025-09-07T08:48:36.0477162Z container_name=$(docker run \ 2025-09-07T08:48:36.0477469Z  ${GPU_FLAG:-} \ 2025-09-07T08:48:36.0477765Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-09-07T08:48:36.0478120Z  -e BUILD_ENVIRONMENT \ 2025-09-07T08:48:36.0478416Z  -e PR_NUMBER \ 2025-09-07T08:48:36.0478686Z  -e GITHUB_ACTIONS \ 2025-09-07T08:48:36.0478965Z  -e GITHUB_REPOSITORY \ 2025-09-07T08:48:36.0479267Z  -e GITHUB_WORKFLOW \ 2025-09-07T08:48:36.0479551Z  -e GITHUB_JOB \ 2025-09-07T08:48:36.0479816Z  -e GITHUB_RUN_ID \ 2025-09-07T08:48:36.0480080Z  -e GITHUB_RUN_NUMBER \ 2025-09-07T08:48:36.0480378Z  -e GITHUB_RUN_ATTEMPT \ 2025-09-07T08:48:36.0480668Z  -e JOB_ID \ 2025-09-07T08:48:36.0480915Z  -e JOB_NAME \ 2025-09-07T08:48:36.0481175Z  -e BASE_SHA \ 2025-09-07T08:48:36.0481415Z  -e BRANCH \ 2025-09-07T08:48:36.0481666Z  -e SHA1 \ 2025-09-07T08:48:36.0481909Z  -e AWS_DEFAULT_REGION \ 2025-09-07T08:48:36.0482202Z  -e IN_WHEEL_TEST \ 2025-09-07T08:48:36.0482470Z  -e SHARD_NUMBER \ 2025-09-07T08:48:36.0482754Z  -e TEST_CONFIG \ 2025-09-07T08:48:36.0483286Z  -e NUM_TEST_SHARDS \ 2025-09-07T08:48:36.0483586Z  -e REENABLED_ISSUES \ 2025-09-07T08:48:36.0483884Z  -e CONTINUE_THROUGH_ERROR \ 2025-09-07T08:48:36.0484466Z  -e VERBOSE_TEST_LOGS \ 2025-09-07T08:48:36.0484778Z  -e TEST_SHOWLOCALS \ 2025-09-07T08:48:36.0485075Z  -e NO_TEST_TIMEOUT \ 2025-09-07T08:48:36.0485348Z  -e NO_TD \ 2025-09-07T08:48:36.0485615Z  -e TD_DISTRIBUTED \ 2025-09-07T08:48:36.0485906Z  -e PR_LABELS \ 2025-09-07T08:48:36.0486213Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-09-07T08:48:36.0486543Z  -e SCCACHE_BUCKET \ 2025-09-07T08:48:36.0486832Z  -e SCCACHE_REGION \ 2025-09-07T08:48:36.0487114Z  -e XLA_CUDA \ 2025-09-07T08:48:36.0487411Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-09-07T08:48:36.0487770Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-09-07T08:48:36.0488160Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-09-07T08:48:36.0488543Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-09-07T08:48:36.0488896Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-09-07T08:48:36.0489229Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-09-07T08:48:36.0489584Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-09-07T08:48:36.0489914Z  -e DASHBOARD_TAG \ 2025-09-07T08:48:36.0490209Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-09-07T08:48:36.0490585Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-09-07T08:48:36.0490998Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-09-07T08:48:36.0491422Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-09-07T08:48:36.0491830Z  --security-opt seccomp=unconfined \ 2025-09-07T08:48:36.0492184Z  --cap-add=SYS_PTRACE \ 2025-09-07T08:48:36.0492471Z  --ipc=host \ 2025-09-07T08:48:36.0492732Z  ${SHM_OPTS} \ 2025-09-07T08:48:36.0493128Z  --tty \ 2025-09-07T08:48:36.0493374Z  --detach \ 2025-09-07T08:48:36.0493633Z  --name="${container_name}" \ 2025-09-07T08:48:36.0493959Z  ${JENKINS_USER} \ 2025-09-07T08:48:36.0494327Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-09-07T08:48:36.0494744Z  -w /var/lib/jenkins/workspace \ 2025-09-07T08:48:36.0495077Z  "${DOCKER_IMAGE}" \ 2025-09-07T08:48:36.0495350Z  ${DOCKER_SHELL_CMD} 2025-09-07T08:48:36.0495626Z ) 2025-09-07T08:48:36.0495924Z # Propagate download.pytorch.org IP to container 2025-09-07T08:48:36.0496614Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-09-07T08:48:36.0497442Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-09-07T08:48:36.0497867Z  2025-09-07T08:48:36.0498145Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:48:36.0498752Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-09-07T08:48:36.0499291Z fi 2025-09-07T08:48:36.0499495Z  2025-09-07T08:48:36.0500007Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-09-07T08:48:36.0511660Z shell: /usr/bin/bash -e {0} 2025-09-07T08:48:36.0511950Z env: 2025-09-07T08:48:36.0512161Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:48:36.0512501Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:48:36.0512964Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T08:48:36.0513451Z BUILD_ENVIRONMENT: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:48:36.0513833Z PR_NUMBER: 2025-09-07T08:48:36.0514069Z GITHUB_REPOSITORY: pytorch/pytorch 2025-09-07T08:48:36.0514408Z GITHUB_WORKFLOW: inductor-A100-perf-nightly 2025-09-07T08:48:36.0514746Z GITHUB_JOB: test 2025-09-07T08:48:36.0514988Z GITHUB_RUN_ID: 17525309334 2025-09-07T08:48:36.0515253Z GITHUB_RUN_NUMBER: 5418 2025-09-07T08:48:36.0515520Z GITHUB_RUN_ATTEMPT: 1 2025-09-07T08:48:36.0515770Z JOB_ID: 49775768420 2025-09-07T08:48:36.0516377Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T08:48:36.0516875Z BRANCH: main 2025-09-07T08:48:36.0517139Z SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:48:36.0517526Z BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:48:36.0517901Z TEST_CONFIG: inductor_torchbench_perf 2025-09-07T08:48:36.0518207Z SHARD_NUMBER: 3 2025-09-07T08:48:36.0518444Z NUM_TEST_SHARDS: 6 2025-09-07T08:48:36.0518691Z REENABLED_ISSUES: 2025-09-07T08:48:36.0518952Z CONTINUE_THROUGH_ERROR: True 2025-09-07T08:48:36.0519226Z VERBOSE_TEST_LOGS: False 2025-09-07T08:48:36.0519497Z TEST_SHOWLOCALS: False 2025-09-07T08:48:36.0519765Z NO_TEST_TIMEOUT: False 2025-09-07T08:48:36.0520027Z NO_TD: False 2025-09-07T08:48:36.0520247Z TD_DISTRIBUTED: False 2025-09-07T08:48:36.0520561Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-09-07T08:48:36.0520930Z SCCACHE_REGION: us-east-1 2025-09-07T08:48:36.0521199Z SHM_SIZE: 2g 2025-09-07T08:48:36.0522129Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:48:36.0523268Z XLA_CUDA: 2025-09-07T08:48:36.0523636Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:48:36.0524295Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-09-07T08:48:36.0524624Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-09-07T08:48:36.0526096Z 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 2025-09-07T08:48:36.0527983Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-09-07T08:48:36.0528472Z HUGGING_FACE_HUB_TOKEN: *** 2025-09-07T08:48:36.0528890Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-09-07T08:48:36.0529385Z ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T08:48:36.0529878Z ##[endgroup] 2025-09-07T08:48:36.0885279Z + [[ inductor_torchbench_perf == \m\u\l\t\i\g\p\u ]] 2025-09-07T08:48:36.0885749Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *onnx* ]] 2025-09-07T08:48:36.0888417Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:48:36.0888833Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-09-07T08:48:36.0896755Z + TOTAL_AVAILABLE_MEMORY_IN_GB='1120.797 ' 2025-09-07T08:48:36.0897112Z + TOTAL_MEMORY_WITH_SWAP=1123 2025-09-07T08:48:36.0897580Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *\s\3\9\0\x* ]] 2025-09-07T08:48:36.0897980Z + SHM_OPTS=--shm-size=2g 2025-09-07T08:48:36.0898259Z + JENKINS_USER='--user jenkins' 2025-09-07T08:48:36.0898541Z + DOCKER_SHELL_CMD= 2025-09-07T08:48:36.0905502Z +++ nproc --ignore=2 2025-09-07T08:48:36.0918853Z ++ docker run --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all -e SCCACHE_SERVER_PORT=5232 -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=10 -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=1120g --memory-swap=1123g --env-file=/tmp/github_env_17525309334 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=2g --tty --detach --name= --user jenkins -v /home/frank/_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 2025-09-07T09:11:32.9371196Z + container_name=733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T09:11:32.9373840Z + grep download.pytorch.org /etc/hosts 2025-09-07T09:11:32.9375580Z + docker exec -i 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 sudo bash -c '/bin/cat >> /etc/hosts' 2025-09-07T09:11:33.0212120Z + echo DOCKER_CONTAINER_ID=733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T09:11:33.0213637Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *\s\3\9\0\x* ]] 2025-09-07T09:11:33.0215989Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T09:11:33.0218376Z + docker exec -t 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-09-07T09:11:33.4220185Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d) 2025-09-07T09:11:34.2406074Z 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) 2025-09-07T09:11:34.2409624Z 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) 2025-09-07T09:11:34.2414219Z 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) 2025-09-07T09:11:34.2421988Z 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) 2025-09-07T09:11:34.2423327Z 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) 2025-09-07T09:11:34.2427432Z 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) 2025-09-07T09:11:34.2440825Z 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) 2025-09-07T09:11:34.2801591Z 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) 2025-09-07T09:11:34.2821374Z 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) 2025-09-07T09:11:34.2857092Z 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) 2025-09-07T09:11:35.1864926Z Installing collected packages: torch 2025-09-07T09:11:46.6077463Z 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. 2025-09-07T09:11:46.6078482Z dall-e 0.1 requires torchvision, which is not installed. 2025-09-07T09:11:46.6078961Z effdet 0.4.1 requires torchvision, which is not installed. 2025-09-07T09:11:46.6079487Z python-doctr 1.0.0 requires torchvision>=0.15.0, which is not installed. 2025-09-07T09:11:46.6080123Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed. 2025-09-07T09:11:46.6080937Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed. 2025-09-07T09:11:46.6081693Z timm 1.0.14 requires torchvision, which is not installed. 2025-09-07T09:11:46.6082578Z Successfully installed torch-2.9.0a0+git93fb23d 2025-09-07T09:11:46.9060501Z + export TERM=vt100 2025-09-07T09:11:46.9060803Z + TERM=vt100 2025-09-07T09:11:46.9062725Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:11:46.9070978Z + source .ci/pytorch/common.sh 2025-09-07T09:11:46.9076010Z +++ dirname .ci/pytorch/common.sh 2025-09-07T09:11:46.9082634Z ++ source .ci/pytorch/common_utils.sh 2025-09-07T09:11:46.9084191Z +++ declare -f -t trap_add 2025-09-07T09:11:46.9088713Z ++ set -ex -o pipefail 2025-09-07T09:11:46.9089029Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:11:46.9089409Z ++ BUILD_TEST_LIBTORCH=0 2025-09-07T09:11:46.9092232Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:11:46.9099355Z + source .ci/pytorch/common-build.sh 2025-09-07T09:11:46.9100672Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *win-* ]] 2025-09-07T09:11:46.9106882Z ++++ dirname .ci/pytorch/common-build.sh 2025-09-07T09:11:46.9113996Z +++ cd .ci/pytorch 2025-09-07T09:11:46.9114297Z +++ pwd -P 2025-09-07T09:11:46.9116434Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-09-07T09:11:46.9116905Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-pch* ]] 2025-09-07T09:11:46.9117272Z ++ which sccache 2025-09-07T09:11:46.9128198Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-09-07T09:11:46.9128575Z ++ sccache --stop-server 2025-09-07T09:11:46.9152601Z ++ true 2025-09-07T09:11:46.9152857Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-09-07T09:11:46.9162222Z ++ trap_add sccache_epilogue EXIT 2025-09-07T09:11:46.9162562Z ++ trap_add_cmd=sccache_epilogue 2025-09-07T09:11:46.9162938Z ++ shift 2025-09-07T09:11:46.9163167Z ++ for trap_add_name in "$@" 2025-09-07T09:11:46.9169226Z ++++ trap -p EXIT 2025-09-07T09:11:46.9171865Z +++ eval 'extract_trap_cmd ' 2025-09-07T09:11:46.9172541Z ++++ extract_trap_cmd 2025-09-07T09:11:46.9172797Z ++++ printf '%s\n' '' 2025-09-07T09:11:46.9173066Z +++ printf '%s\n' sccache_epilogue 2025-09-07T09:11:46.9173728Z ++ trap -- ' 2025-09-07T09:11:46.9173965Z sccache_epilogue' EXIT 2025-09-07T09:11:46.9174228Z ++ [[ -n 1 ]] 2025-09-07T09:11:46.9174623Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-09-07T09:11:46.9175246Z Skipping sccache server initialization, setting environment variables 2025-09-07T09:11:46.9175700Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:11:46.9175980Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:11:46.9176330Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:11:46.9176783Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:11:46.9177306Z ++ export RUST_LOG=sccache::server=error 2025-09-07T09:11:46.9177630Z ++ RUST_LOG=sccache::server=error 2025-09-07T09:11:46.9177930Z ++ sccache --zero-stats 2025-09-07T09:11:47.7284954Z Statistics zeroed. 2025-09-07T09:11:47.7289264Z ++ which ccache 2025-09-07T09:11:47.7303065Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *rocm* ]] 2025-09-07T09:11:47.7303548Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *s390x* ]] 2025-09-07T09:11:47.7304006Z + [[ -d /var/lib/jenkins/workspace ]] 2025-09-07T09:11:47.7307429Z ++ stat -c %u /var/lib/jenkins/workspace 2025-09-07T09:11:47.7319880Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-09-07T09:11:47.7320277Z + trap_add cleanup_workspace EXIT 2025-09-07T09:11:47.7320622Z + trap_add_cmd=cleanup_workspace 2025-09-07T09:11:47.7320925Z + shift 2025-09-07T09:11:47.7321171Z + for trap_add_name in "$@" 2025-09-07T09:11:47.7329070Z +++ trap -p EXIT 2025-09-07T09:11:47.7332896Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-09-07T09:11:47.7333308Z sccache_epilogue'\'' EXIT' 2025-09-07T09:11:47.7333625Z +++ extract_trap_cmd trap -- ' 2025-09-07T09:11:47.7333940Z sccache_epilogue' EXIT 2025-09-07T09:11:47.7334204Z +++ printf '%s\n' ' 2025-09-07T09:11:47.7334503Z sccache_epilogue' 2025-09-07T09:11:47.7334782Z ++ printf '%s\n' cleanup_workspace 2025-09-07T09:11:47.7335348Z + trap -- ' 2025-09-07T09:11:47.7335576Z sccache_epilogue 2025-09-07T09:11:47.7335847Z cleanup_workspace' EXIT 2025-09-07T09:11:47.7336671Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-09-07T09:12:05.3640449Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-09-07T09:12:05.3658418Z + echo 'Environment variables:' 2025-09-07T09:12:05.3658758Z Environment variables: 2025-09-07T09:12:05.3658996Z + env 2025-09-07T09:12:05.3667953Z GITHUB_WORKSPACE=/home/frank/_work/pytorch/pytorch 2025-09-07T09:12:05.3668422Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:12:05.3668791Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T09:12:05.3674622Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:12:05.3675001Z HOSTNAME=733d4ba3112f 2025-09-07T09:12:05.3675499Z GITHUB_PATH=/home/frank/_work/_temp/_runner_file_commands/add_path_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.3676097Z GITHUB_ACTION=__run_2 2025-09-07T09:12:05.3676367Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:12:05.3676671Z GITHUB_RUN_NUMBER=5418 2025-09-07T09:12:05.3676933Z TEST_CONFIG=inductor_torchbench_perf 2025-09-07T09:12:05.3677271Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:12:05.3677600Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:12:05.3677924Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:12:05.3678326Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:12:05.3678612Z GITHUB_TRIGGERING_ACTOR=desertfire 2025-09-07T09:12:05.3678909Z GITHUB_REF_TYPE=branch 2025-09-07T09:12:05.3679204Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.3679537Z XLA_CUDA= 2025-09-07T09:12:05.3679751Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:12:05.3680156Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:12:05.3680554Z *** 2025-09-07T09:12:05.3680771Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:12:05.3681040Z GITHUB_ACTIONS=true 2025-09-07T09:12:05.3681297Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:12:05.3689608Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:12:05.3690010Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.3690376Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.3691024Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly.yml@refs/heads/main 2025-09-07T09:12:05.3691613Z UCC_HOME=/usr 2025-09-07T09:12:05.3691844Z VERBOSE_TEST_LOGS=False 2025-09-07T09:12:05.3692108Z GITHUB_REF=refs/heads/main 2025-09-07T09:12:05.3692360Z SHARD_NUMBER=3 2025-09-07T09:12:05.3692594Z GITHUB_REF_PROTECTED=true 2025-09-07T09:12:05.3692857Z HOME=/var/lib/jenkins 2025-09-07T09:12:05.3693097Z SCCACHE_SERVER_PORT=5232 2025-09-07T09:12:05.3693396Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:12:05.3693729Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:12:05.3694080Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:12:05.3694415Z USE_SYSTEM_NCCL=1 2025-09-07T09:12:05.3694656Z NUM_TEST_SHARDS=6 2025-09-07T09:12:05.3694885Z UCX_HOME=/usr 2025-09-07T09:12:05.3695372Z GITHUB_STATE=/home/frank/_work/_temp/_runner_file_commands/save_state_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.3696137Z JOB_NAME=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T09:12:05.3696864Z GITHUB_ENV=/home/frank/_work/_temp/_runner_file_commands/set_env_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.3697637Z GITHUB_EVENT_PATH=/home/frank/_work/_temp/_github_workflow/event.json 2025-09-07T09:12:05.3698081Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:12:05.3699379Z 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 2025-09-07T09:12:05.3700706Z GITHUB_RUN_ID=17525309334 2025-09-07T09:12:05.3700957Z INSTALLED_OPENBLAS= 2025-09-07T09:12:05.3701506Z GITHUB_STEP_SUMMARY=/home/frank/_work/_temp/_runner_file_commands/step_summary_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.3702127Z GITHUB_ACTOR=desertfire 2025-09-07T09:12:05.3702379Z PR_NUMBER= 2025-09-07T09:12:05.3702580Z DESIRED_CUDA=12.8.1 2025-09-07T09:12:05.3702818Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:12:05.3703321Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:12:05.3703668Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:12:05.3704008Z TERM=vt100 2025-09-07T09:12:05.3704226Z INSTALLED_VISION=yes 2025-09-07T09:12:05.3704469Z BRANCH=main 2025-09-07T09:12:05.3704676Z SCCACHE_REGION=us-east-1 2025-09-07T09:12:05.3704966Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:12:05.3705253Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:12:05.3705697Z GITHUB_ACTION_PATH=/home/frank/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:12:05.3706210Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:12:05.3706567Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:12:05.3706906Z REENABLED_ISSUES= 2025-09-07T09:12:05.3707138Z DOCS= 2025-09-07T09:12:05.3707341Z SHLVL=1 2025-09-07T09:12:05.3707529Z MAX_JOBS=10 2025-09-07T09:12:05.3707752Z GITHUB_ACTOR_ID=3659962 2025-09-07T09:12:05.3708096Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.3708487Z GITHUB_REF_NAME=main 2025-09-07T09:12:05.3708858Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:12:05.3709299Z GITHUB_JOB=test 2025-09-07T09:12:05.3709533Z NO_TEST_TIMEOUT=False 2025-09-07T09:12:05.3709791Z TD_DISTRIBUTED=False 2025-09-07T09:12:05.3710048Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:12:05.3710355Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:12:05.3710624Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:12:05.3710895Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:12:05.3711697Z 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 2025-09-07T09:12:05.3712528Z GITHUB_BASE_REF= 2025-09-07T09:12:05.3712920Z INSTALLED_ACL= 2025-09-07T09:12:05.3713337Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T09:12:05.3713821Z CI=true 2025-09-07T09:12:05.3714030Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:12:05.3714367Z RUST_LOG=sccache::server=error 2025-09-07T09:12:05.3714638Z JOB_ID=49775768420 2025-09-07T09:12:05.3714852Z GITHUB_HEAD_REF= 2025-09-07T09:12:05.3715084Z GITHUB_ACTION_REF= 2025-09-07T09:12:05.3715370Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:12:05.3715725Z TEST_SHOWLOCALS=False 2025-09-07T09:12:05.3716003Z GITHUB_WORKFLOW=inductor-A100-perf-nightly 2025-09-07T09:12:05.3716342Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:12:05.3716890Z GITHUB_OUTPUT=/home/frank/_work/_temp/_runner_file_commands/set_output_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.3717460Z NO_TD=False 2025-09-07T09:12:05.3717693Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:12:05.3717988Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:12:05.3718308Z _=/usr/bin/env 2025-09-07T09:12:05.3718642Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-09-07T09:12:05.3960303Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-09-07T09:12:05.3960982Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-09-07T09:12:05.3961585Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-09-07T09:12:05.3962183Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-09-07T09:12:05.3962647Z + BUILD_DIR=build 2025-09-07T09:12:05.3963028Z + BUILD_RENAMED_DIR=build_renamed 2025-09-07T09:12:05.3963336Z + BUILD_BIN_DIR=build/bin 2025-09-07T09:12:05.3963587Z + SHARD_NUMBER=3 2025-09-07T09:12:05.3963823Z + NUM_TEST_SHARDS=6 2025-09-07T09:12:05.3964087Z + export TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:12:05.3964408Z + TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:12:05.3964677Z + export VALGRIND=ON 2025-09-07T09:12:05.3964931Z + VALGRIND=ON 2025-09-07T09:12:05.3965229Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *clang9* ]] 2025-09-07T09:12:05.3965657Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *xpu* ]] 2025-09-07T09:12:05.3965995Z + detect_cuda_arch 2025-09-07T09:12:05.6356705Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:12:05.6357270Z + command -v nvidia-smi 2025-09-07T09:12:05.6357583Z /usr/bin/nvidia-smi 2025-09-07T09:12:05.6357950Z ++ nvidia-smi --query-gpu=compute_cap --format=csv 2025-09-07T09:12:05.6358295Z ++ tail -n 1 2025-09-07T09:12:05.6569303Z + TORCH_CUDA_ARCH_LIST=8.0 2025-09-07T09:12:05.6569620Z + export TORCH_CUDA_ARCH_LIST 2025-09-07T09:12:05.6569977Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *s390x* ]] 2025-09-07T09:12:05.6570319Z + [[ 0 == \1 ]] 2025-09-07T09:12:05.6570543Z + [[ True == \1 ]] 2025-09-07T09:12:05.6570838Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *bazel* ]] 2025-09-07T09:12:05.6574423Z ++ realpath build/custom_test_artifacts 2025-09-07T09:12:05.6583761Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-09-07T09:12:05.6584280Z + [[ -n '' ]] 2025-09-07T09:12:05.6584516Z + echo 'Environment variables' 2025-09-07T09:12:05.6584802Z Environment variables 2025-09-07T09:12:05.6585041Z + env 2025-09-07T09:12:05.6592068Z GITHUB_WORKSPACE=/home/frank/_work/pytorch/pytorch 2025-09-07T09:12:05.6592488Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:12:05.6592850Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T09:12:05.6593451Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:12:05.6593747Z HOSTNAME=733d4ba3112f 2025-09-07T09:12:05.6594239Z GITHUB_PATH=/home/frank/_work/_temp/_runner_file_commands/add_path_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.6594802Z GITHUB_ACTION=__run_2 2025-09-07T09:12:05.6595094Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:12:05.6605969Z GITHUB_RUN_NUMBER=5418 2025-09-07T09:12:05.6606266Z TEST_CONFIG=inductor_torchbench_perf 2025-09-07T09:12:05.6606604Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:12:05.6607269Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:12:05.6607602Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:12:05.6608056Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:12:05.6608366Z GITHUB_TRIGGERING_ACTOR=desertfire 2025-09-07T09:12:05.6608684Z GITHUB_REF_TYPE=branch 2025-09-07T09:12:05.6608947Z TORCH_CUDA_ARCH_LIST=8.0 2025-09-07T09:12:05.6609242Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.6609583Z XLA_CUDA= 2025-09-07T09:12:05.6609816Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:12:05.6610233Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:12:05.6610571Z *** 2025-09-07T09:12:05.6610777Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:12:05.6611058Z GITHUB_ACTIONS=true 2025-09-07T09:12:05.6611312Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:12:05.6611660Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:12:05.6612040Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.6612417Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.6613058Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly.yml@refs/heads/main 2025-09-07T09:12:05.6613649Z UCC_HOME=/usr 2025-09-07T09:12:05.6613872Z TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:12:05.6614158Z VERBOSE_TEST_LOGS=False 2025-09-07T09:12:05.6614422Z GITHUB_REF=refs/heads/main 2025-09-07T09:12:05.6614688Z SHARD_NUMBER=3 2025-09-07T09:12:05.6614911Z GITHUB_REF_PROTECTED=true 2025-09-07T09:12:05.6615179Z HOME=/var/lib/jenkins 2025-09-07T09:12:05.6615438Z SCCACHE_SERVER_PORT=5232 2025-09-07T09:12:05.6615739Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:12:05.6616064Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:12:05.6616414Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:12:05.6616763Z USE_SYSTEM_NCCL=1 2025-09-07T09:12:05.6616999Z NUM_TEST_SHARDS=6 2025-09-07T09:12:05.6617329Z UCX_HOME=/usr 2025-09-07T09:12:05.6617827Z GITHUB_STATE=/home/frank/_work/_temp/_runner_file_commands/save_state_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.6618602Z JOB_NAME=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T09:12:05.6619348Z GITHUB_ENV=/home/frank/_work/_temp/_runner_file_commands/set_env_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.6620238Z GITHUB_EVENT_PATH=/home/frank/_work/_temp/_github_workflow/event.json 2025-09-07T09:12:05.6620669Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:12:05.6621962Z 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 2025-09-07T09:12:05.6623287Z GITHUB_RUN_ID=17525309334 2025-09-07T09:12:05.6623562Z INSTALLED_OPENBLAS= 2025-09-07T09:12:05.6624094Z GITHUB_STEP_SUMMARY=/home/frank/_work/_temp/_runner_file_commands/step_summary_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.6624713Z GITHUB_ACTOR=desertfire 2025-09-07T09:12:05.6624966Z PR_NUMBER= 2025-09-07T09:12:05.6625190Z DESIRED_CUDA=12.8.1 2025-09-07T09:12:05.6625417Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:12:05.6625660Z VALGRIND=ON 2025-09-07T09:12:05.6625893Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:12:05.6626235Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:12:05.6626579Z TERM=vt100 2025-09-07T09:12:05.6626800Z INSTALLED_VISION=yes 2025-09-07T09:12:05.6627045Z BRANCH=main 2025-09-07T09:12:05.6627271Z SCCACHE_REGION=us-east-1 2025-09-07T09:12:05.6627533Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:12:05.6627822Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:12:05.6628267Z GITHUB_ACTION_PATH=/home/frank/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:12:05.6628781Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:12:05.6629129Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:12:05.6629482Z REENABLED_ISSUES= 2025-09-07T09:12:05.6629710Z DOCS= 2025-09-07T09:12:05.6629911Z SHLVL=1 2025-09-07T09:12:05.6630100Z MAX_JOBS=10 2025-09-07T09:12:05.6630482Z GITHUB_ACTOR_ID=3659962 2025-09-07T09:12:05.6630825Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:12:05.6631213Z GITHUB_REF_NAME=main 2025-09-07T09:12:05.6631583Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:12:05.6632026Z GITHUB_JOB=test 2025-09-07T09:12:05.6632260Z NO_TEST_TIMEOUT=False 2025-09-07T09:12:05.6632511Z TD_DISTRIBUTED=False 2025-09-07T09:12:05.6632767Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:12:05.6633077Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:12:05.6633348Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:12:05.6633620Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:12:05.6634416Z 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 2025-09-07T09:12:05.6635248Z GITHUB_BASE_REF= 2025-09-07T09:12:05.6635480Z INSTALLED_ACL= 2025-09-07T09:12:05.6635903Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T09:12:05.6636382Z CI=true 2025-09-07T09:12:05.6636611Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:12:05.6636946Z RUST_LOG=sccache::server=error 2025-09-07T09:12:05.6637227Z JOB_ID=49775768420 2025-09-07T09:12:05.6637445Z GITHUB_HEAD_REF= 2025-09-07T09:12:05.6637682Z GITHUB_ACTION_REF= 2025-09-07T09:12:05.6637980Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:12:05.6638338Z TEST_SHOWLOCALS=False 2025-09-07T09:12:05.6638613Z GITHUB_WORKFLOW=inductor-A100-perf-nightly 2025-09-07T09:12:05.6638958Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:12:05.6639512Z GITHUB_OUTPUT=/home/frank/_work/_temp/_runner_file_commands/set_output_577d58ba-cc00-4171-b41e-112dfa7503ec 2025-09-07T09:12:05.6640084Z NO_TD=False 2025-09-07T09:12:05.6640306Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:12:05.6640620Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:12:05.6640936Z _=/usr/bin/env 2025-09-07T09:12:05.6641170Z + echo 'Testing pytorch' 2025-09-07T09:12:05.6641416Z Testing pytorch 2025-09-07T09:12:05.6641670Z + export LANG=C.UTF-8 2025-09-07T09:12:05.6641920Z + LANG=C.UTF-8 2025-09-07T09:12:05.6642162Z + PR_NUMBER= 2025-09-07T09:12:05.6642419Z + [[ inductor_torchbench_perf == \d\e\f\a\u\l\t ]] 2025-09-07T09:12:05.6643181Z + [[ inductor_torchbench_perf == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-09-07T09:12:05.6643588Z + [[ inductor_torchbench_perf == \s\l\o\w ]] 2025-09-07T09:12:05.6644018Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *slow-gradcheck* ]] 2025-09-07T09:12:05.6644474Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:12:05.6644872Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:12:05.6645231Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:12:05.6645576Z + [[ inductor_torchbench_perf == *crossref* ]] 2025-09-07T09:12:05.6645968Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:12:05.6646369Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *xpu* ]] 2025-09-07T09:12:05.6646796Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *-bazel-* ]] 2025-09-07T09:12:05.6647187Z + pip_install ninja==1.10.2 2025-09-07T09:12:05.6647559Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:12:05.6648019Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-09-07T09:12:06.3441236Z Collecting ninja==1.10.2 2025-09-07T09:12:06.3641789Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-09-07T09:12:06.4094608Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-09-07T09:12:07.6833283Z Installing collected packages: ninja 2025-09-07T09:12:07.6833683Z Attempting uninstall: ninja 2025-09-07T09:12:07.6844475Z Found existing installation: ninja 1.11.1.3 2025-09-07T09:12:07.6865597Z Uninstalling ninja-1.11.1.3: 2025-09-07T09:12:07.9183707Z Successfully uninstalled ninja-1.11.1.3 2025-09-07T09:12:08.3491090Z Successfully installed ninja-1.10.2 2025-09-07T09:12:08.4499603Z + 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 2025-09-07T09:12:08.4721877Z + 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 2025-09-07T09:12:08.4723159Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *aarch64* ]] 2025-09-07T09:12:08.4723630Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *asan* ]] 2025-09-07T09:12:08.4724063Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-debug* ]] 2025-09-07T09:12:08.4724492Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *-bazel-* ]] 2025-09-07T09:12:08.4725107Z + echo 'We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm80. Expect the assertion to pass' 2025-09-07T09:12:08.4725862Z We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm80. Expect the assertion to pass 2025-09-07T09:12:08.4726372Z + cd test 2025-09-07T09:12:08.4726722Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-09-07T09:12:09.0623627Z /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. 2025-09-07T09:12:09.0625123Z import pynvml # type: ignore[import] 2025-09-07T09:12:10.2552854Z + [[ inductor_torchbench_perf == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-09-07T09:12:10.2553363Z + [[ inductor_torchbench_perf == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-09-07T09:12:10.2553866Z + [[ inductor_torchbench_perf == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-09-07T09:12:10.2557816Z + DYNAMO_BENCHMARK_FLAGS=() 2025-09-07T09:12:10.2558158Z + [[ inductor_torchbench_perf == *pr_time_benchmarks* ]] 2025-09-07T09:12:10.2558555Z + [[ inductor_torchbench_perf == *dynamo_eager* ]] 2025-09-07T09:12:10.2558973Z + [[ inductor_torchbench_perf == *aot_eager* ]] 2025-09-07T09:12:10.2559352Z + [[ inductor_torchbench_perf == *aot_inductor* ]] 2025-09-07T09:12:10.2559770Z + [[ inductor_torchbench_perf == *max_autotune_inductor* ]] 2025-09-07T09:12:10.2560481Z + [[ inductor_torchbench_perf == *inductor* ]] 2025-09-07T09:12:10.2560850Z + [[ inductor_torchbench_perf != *perf* ]] 2025-09-07T09:12:10.2561203Z + [[ inductor_torchbench_perf == *dynamic* ]] 2025-09-07T09:12:10.2561562Z + [[ inductor_torchbench_perf == *cpu* ]] 2025-09-07T09:12:10.2561906Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-09-07T09:12:10.2580773Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *libtorch* ]] 2025-09-07T09:12:10.2581274Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-bazel-* ]] 2025-09-07T09:12:10.2584035Z + cd test 2025-09-07T09:12:10.2584783Z + python -c 'import torch; print(torch.__config__.show())' 2025-09-07T09:12:10.8654084Z /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. 2025-09-07T09:12:10.8655519Z import pynvml # type: ignore[import] 2025-09-07T09:12:13.3093574Z PyTorch built with: 2025-09-07T09:12:13.3093902Z - GCC 9.5 2025-09-07T09:12:13.3094125Z - C++ Version: 201703 2025-09-07T09:12:13.3094703Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:12:13.3095431Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:12:13.3095885Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:12:13.3096234Z - LAPACK is enabled (usually provided by MKL) 2025-09-07T09:12:13.3096573Z - NNPACK is enabled 2025-09-07T09:12:13.3096827Z - CPU capability usage: AVX512 2025-09-07T09:12:13.3097114Z - CUDA Runtime 12.8 2025-09-07T09:12:13.3097551Z - NVCC architecture flags: -gencode;arch=compute_80,code=sm_80 2025-09-07T09:12:13.3098307Z - CuDNN 90.8 2025-09-07T09:12:13.3103128Z - 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, 2025-09-07T09:12:13.3108086Z 2025-09-07T09:12:14.4755124Z + cd test 2025-09-07T09:12:14.4755535Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-09-07T09:12:15.1138196Z /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. 2025-09-07T09:12:15.1139579Z import pynvml # type: ignore[import] 2025-09-07T09:12:15.9337664Z ATen/Parallel: 2025-09-07T09:12:15.9338001Z at::get_num_threads() : 12 2025-09-07T09:12:15.9338306Z at::get_num_interop_threads() : 48 2025-09-07T09:12:15.9338626Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:12:15.9338958Z omp_get_max_threads() : 12 2025-09-07T09:12:15.9339547Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:12:15.9340150Z mkl_get_max_threads() : 12 2025-09-07T09:12:15.9340956Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:12:15.9341429Z std::thread::hardware_concurrency() : 96 2025-09-07T09:12:15.9341763Z Environment variables: 2025-09-07T09:12:15.9342022Z OMP_NUM_THREADS : [not set] 2025-09-07T09:12:15.9342306Z MKL_NUM_THREADS : [not set] 2025-09-07T09:12:15.9342596Z ATen parallel backend: OpenMP 2025-09-07T09:12:15.9342786Z 2025-09-07T09:12:16.2589573Z + [[ inductor_torchbench_perf == *numpy_2* ]] 2025-09-07T09:12:16.2590045Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *aarch64* ]] 2025-09-07T09:12:16.2590449Z + [[ inductor_torchbench_perf == *backward* ]] 2025-09-07T09:12:16.2590803Z + [[ inductor_torchbench_perf == *xla* ]] 2025-09-07T09:12:16.2591175Z + [[ inductor_torchbench_perf == *vllm* ]] 2025-09-07T09:12:16.2591534Z + [[ inductor_torchbench_perf == *executorch* ]] 2025-09-07T09:12:16.2591912Z + [[ inductor_torchbench_perf == \j\i\t\_\l\e\g\a\c\y ]] 2025-09-07T09:12:16.2592358Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *libtorch* ]] 2025-09-07T09:12:16.2592766Z + [[ inductor_torchbench_perf == distributed ]] 2025-09-07T09:12:16.2593159Z + [[ inductor_torchbench_perf == *operator_benchmark* ]] 2025-09-07T09:12:16.2593575Z + [[ inductor_torchbench_perf == *inductor_distributed* ]] 2025-09-07T09:12:16.2593998Z + [[ inductor_torchbench_perf == *inductor-halide* ]] 2025-09-07T09:12:16.2594421Z + [[ inductor_torchbench_perf == *inductor-triton-cpu* ]] 2025-09-07T09:12:16.2594878Z + [[ inductor_torchbench_perf == *inductor-micro-benchmark* ]] 2025-09-07T09:12:16.2595312Z + [[ inductor_torchbench_perf == *huggingface* ]] 2025-09-07T09:12:16.2595666Z + [[ inductor_torchbench_perf == *timm* ]] 2025-09-07T09:12:16.2596014Z + [[ inductor_torchbench_perf == cachebench ]] 2025-09-07T09:12:16.2596809Z + [[ inductor_torchbench_perf == verify_cachebench ]] 2025-09-07T09:12:16.2597198Z + [[ inductor_torchbench_perf == *torchbench* ]] 2025-09-07T09:12:16.2597525Z + install_torchaudio 2025-09-07T09:12:16.2597789Z + local commit 2025-09-07T09:12:16.2598022Z ++ get_pinned_commit audio 2025-09-07T09:12:16.2598310Z ++ cat .github/ci_commit_pins/audio.txt 2025-09-07T09:12:16.2606764Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:12:16.2607471Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio 2025-09-07T09:12:16.2608349Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:12:16.2608923Z + local wheel_dir=dist/audio 2025-09-07T09:12:16.2609197Z + local found_whl=0 2025-09-07T09:12:16.2609437Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:16.2609887Z + [[ -f dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:12:16.2610340Z + found_whl=1 2025-09-07T09:12:16.2610555Z + break 2025-09-07T09:12:16.2610742Z + '[' 1 == 0 ']' 2025-09-07T09:12:16.2610982Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:16.2611475Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:16.2612122Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:12:16.2612558Z + local args 2025-09-07T09:12:16.2612947Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:12:16.2613429Z + for path in "${args[@]}" 2025-09-07T09:12:16.2613890Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:12:16.2614561Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:16.2615319Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:16.6526254Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:16.6604361Z Installing collected packages: torchaudio 2025-09-07T09:12:17.4644909Z Successfully installed torchaudio-2.8.0a0+2e30055 2025-09-07T09:12:17.5046332Z + install_torchvision 2025-09-07T09:12:17.5046618Z + local orig_preload 2025-09-07T09:12:17.5046863Z + local commit 2025-09-07T09:12:17.5049703Z ++ get_pinned_commit vision 2025-09-07T09:12:17.5050346Z ++ cat .github/ci_commit_pins/vision.txt 2025-09-07T09:12:17.5064007Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:12:17.5064386Z + orig_preload= 2025-09-07T09:12:17.5064627Z + '[' -n '' ']' 2025-09-07T09:12:17.5064923Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:12:17.5065280Z + export FORCE_CUDA=1 2025-09-07T09:12:17.5065528Z + FORCE_CUDA=1 2025-09-07T09:12:17.5065754Z + export WITH_CUDA=1 2025-09-07T09:12:17.5065998Z + WITH_CUDA=1 2025-09-07T09:12:17.5066567Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-09-07T09:12:17.5067501Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:12:17.5068089Z + local wheel_dir=dist/vision 2025-09-07T09:12:17.5068379Z + local found_whl=0 2025-09-07T09:12:17.5068629Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:17.5069080Z + [[ -f dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:12:17.5069550Z + found_whl=1 2025-09-07T09:12:17.5069765Z + break 2025-09-07T09:12:17.5069964Z + '[' 1 == 0 ']' 2025-09-07T09:12:17.5070190Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:17.5070688Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:17.5071376Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:12:17.5071840Z + local args 2025-09-07T09:12:17.5072232Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:12:17.5073017Z + for path in "${args[@]}" 2025-09-07T09:12:17.5073493Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:12:17.5074203Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:17.5075000Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:17.8654876Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:17.9447114Z Installing collected packages: torchvision 2025-09-07T09:12:18.9674687Z Successfully installed torchvision-0.22.0a0+966da7e 2025-09-07T09:12:19.0154139Z + '[' -n '' ']' 2025-09-07T09:12:19.0154392Z + id=2 2025-09-07T09:12:19.0154634Z + pip_install opencv-python==4.8.0.74 2025-09-07T09:12:19.0155048Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:12:19.0155545Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74 2025-09-07T09:12:19.6978109Z Collecting opencv-python==4.8.0.74 2025-09-07T09:12:19.7145932Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB) 2025-09-07T09:12:19.8357408Z 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) 2025-09-07T09:12:19.8412811Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB) 2025-09-07T09:12:23.8765308Z Installing collected packages: opencv-python 2025-09-07T09:12:23.8765721Z Attempting uninstall: opencv-python 2025-09-07T09:12:23.8778751Z Found existing installation: opencv-python 4.11.0.86 2025-09-07T09:12:23.8853410Z Uninstalling opencv-python-4.11.0.86: 2025-09-07T09:12:24.0551914Z Successfully uninstalled opencv-python-4.11.0.86 2025-09-07T09:12:25.9527257Z Successfully installed opencv-python-4.8.0.74 2025-09-07T09:12:26.0656774Z + [[ inductor_torchbench_perf == *inductor_torchbench_smoketest_perf* ]] 2025-09-07T09:12:26.0657475Z + [[ inductor_torchbench_perf == *inductor_torchbench_cpu_smoketest_perf* ]] 2025-09-07T09:12:26.0658876Z + [[ inductor_torchbench_perf == *torchbench_gcp_smoketest* ]] 2025-09-07T09:12:26.0659673Z + [[ inductor_torchbench_perf != *cpu* ]] 2025-09-07T09:12:26.0660293Z + install_torchrec_and_fbgemm 2025-09-07T09:12:26.0660810Z + local torchrec_commit 2025-09-07T09:12:26.0661970Z ++ get_pinned_commit torchrec 2025-09-07T09:12:26.0662530Z ++ cat .github/ci_commit_pins/torchrec.txt 2025-09-07T09:12:26.0674535Z + torchrec_commit=6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:12:26.0675236Z + local fbgemm_commit 2025-09-07T09:12:26.0678990Z ++ get_pinned_commit fbgemm 2025-09-07T09:12:26.0679444Z ++ cat .github/ci_commit_pins/fbgemm.txt 2025-09-07T09:12:26.0690635Z + fbgemm_commit=de731af65b4f04696e85c729e3282450b51b95fd 2025-09-07T09:12:26.0691432Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:12:26.0692173Z + pip_uninstall torchrec-nightly 2025-09-07T09:12:26.0692760Z + pip3 uninstall -y torchrec-nightly 2025-09-07T09:12:26.5066299Z WARNING: Skipping torchrec-nightly as it is not installed. 2025-09-07T09:12:26.5470323Z + pip_uninstall fbgemm-gpu-nightly 2025-09-07T09:12:26.5470762Z + pip3 uninstall -y fbgemm-gpu-nightly 2025-09-07T09:12:26.9076430Z WARNING: Skipping fbgemm-gpu-nightly as it is not installed. 2025-09-07T09:12:26.9451526Z + pip_install setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:12:26.9452099Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:12:26.9452745Z + python3 -m pip install --progress-bar off setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:12:27.2999235Z Requirement already satisfied: setuptools-git-versioning in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (2.1.0) 2025-09-07T09:12:27.3001331Z Requirement already satisfied: scikit-build in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.18.1) 2025-09-07T09:12:27.3004429Z Requirement already satisfied: pyre-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.0.32) 2025-09-07T09:12:27.3017045Z Requirement already satisfied: packaging in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (25.0) 2025-09-07T09:12:27.3020790Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (80.9.0) 2025-09-07T09:12:27.3027799Z 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) 2025-09-07T09:12:27.3072748Z Requirement already satisfied: distro in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (1.9.0) 2025-09-07T09:12:27.3081383Z 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) 2025-09-07T09:12:27.3090256Z Requirement already satisfied: typing-inspect in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (0.9.0) 2025-09-07T09:12:27.3093870Z Requirement already satisfied: typing-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (4.15.0) 2025-09-07T09:12:27.3175617Z 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) 2025-09-07T09:12:28.4100372Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:12:28.4101182Z + pip_build_and_install git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 dist/torchrec 2025-09-07T09:12:28.4102137Z + local build_target=git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:12:28.4102730Z + local wheel_dir=dist/torchrec 2025-09-07T09:12:28.4103018Z + local found_whl=0 2025-09-07T09:12:28.6374318Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:28.6374786Z + [[ -f dist/torchrec/torchrec-0.3.2-py3-none-any.whl ]] 2025-09-07T09:12:28.6375159Z + found_whl=1 2025-09-07T09:12:28.6375364Z + break 2025-09-07T09:12:28.6375568Z + '[' 1 == 0 ']' 2025-09-07T09:12:28.6376254Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:28.6376664Z + pip_install_whl dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:12:28.6377181Z + args=('dist/torchrec/torchrec-0.3.2-py3-none-any.whl') 2025-09-07T09:12:28.6377562Z + local args 2025-09-07T09:12:28.6377874Z + [[ dist/torchrec/torchrec-0.3.2-py3-none-any.whl == *\ * ]] 2025-09-07T09:12:28.6378286Z + for path in "${args[@]}" 2025-09-07T09:12:28.6378652Z + echo 'Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl' 2025-09-07T09:12:28.6379146Z Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:12:28.6379724Z + python3 -mpip install --no-index --no-deps dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:12:28.9923834Z Processing ./dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:12:29.0543176Z Installing collected packages: torchrec 2025-09-07T09:12:30.7109628Z Successfully installed torchrec-0.3.2 2025-09-07T09:12:30.7514039Z + pip_build_and_install git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu dist/fbgemm_gpu 2025-09-07T09:12:30.7515235Z + local build_target=git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu 2025-09-07T09:12:30.7515944Z + local wheel_dir=dist/fbgemm_gpu 2025-09-07T09:12:30.7516242Z + local found_whl=0 2025-09-07T09:12:30.7516499Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:30.7516940Z + [[ -f dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:12:30.7517396Z + found_whl=1 2025-09-07T09:12:30.7517616Z + break 2025-09-07T09:12:30.7517822Z + '[' 1 == 0 ']' 2025-09-07T09:12:30.7518049Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:12:30.7518898Z + pip_install_whl dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:30.7519561Z + args=('dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:12:30.7520022Z + local args 2025-09-07T09:12:30.7520406Z + [[ dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:12:30.7520899Z + for path in "${args[@]}" 2025-09-07T09:12:30.7521371Z + echo 'Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:12:30.7522051Z Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:30.7523103Z + python3 -mpip install --no-index --no-deps dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:31.1124983Z Processing ./dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:12:31.3944832Z Installing collected packages: fbgemm-gpu 2025-09-07T09:12:34.4700733Z Successfully installed fbgemm-gpu-0.4.1.post421 2025-09-07T09:12:34.5077939Z + PYTHONPATH=/torchbench 2025-09-07T09:12:34.5078234Z + test_dynamo_benchmark torchbench 2 2025-09-07T09:12:34.5082928Z ++ pwd 2025-09-07T09:12:34.5084660Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:12:34.5085126Z + local suite=torchbench 2025-09-07T09:12:34.5085382Z + shift 2025-09-07T09:12:34.5085591Z + local shard_id=2 2025-09-07T09:12:34.5085823Z + shift 2025-09-07T09:12:34.5086082Z + [[ inductor_torchbench_perf == *perf_compare* ]] 2025-09-07T09:12:34.5086454Z + [[ inductor_torchbench_perf == *perf* ]] 2025-09-07T09:12:34.5086793Z + [[ inductor_torchbench_perf == *b200* ]] 2025-09-07T09:12:34.5087174Z + test_single_dynamo_benchmark dashboard torchbench 2 2025-09-07T09:12:34.5088752Z ++ pwd 2025-09-07T09:12:34.5090565Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:12:34.5091026Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:12:34.5107959Z + local name=dashboard 2025-09-07T09:12:34.5108246Z + shift 2025-09-07T09:12:34.5108461Z + local suite=torchbench 2025-09-07T09:12:34.5108704Z + shift 2025-09-07T09:12:34.5108909Z + local shard_id=2 2025-09-07T09:12:34.5109147Z + shift 2025-09-07T09:12:34.5109357Z + partition_flags=() 2025-09-07T09:12:34.5115959Z + local partition_flags 2025-09-07T09:12:34.5116353Z + [[ -n 6 ]] 2025-09-07T09:12:34.5116572Z + [[ -n 2 ]] 2025-09-07T09:12:34.5116988Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id") 2025-09-07T09:12:34.5117526Z + [[ inductor_torchbench_perf == *perf_compare* ]] 2025-09-07T09:12:34.5117898Z + [[ inductor_torchbench_perf == *perf* ]] 2025-09-07T09:12:34.5118426Z + test_perf_for_dashboard torchbench --device cuda --total-partitions 6 --partition-id 2 2025-09-07T09:12:34.5118925Z ++ pwd 2025-09-07T09:12:34.5119222Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:12:34.5119694Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:12:34.5128348Z + local suite=torchbench 2025-09-07T09:12:34.5128626Z + shift 2025-09-07T09:12:34.5128829Z + local backend=inductor 2025-09-07T09:12:34.5129095Z + modes=() 2025-09-07T09:12:34.5129305Z + local modes 2025-09-07T09:12:34.5130602Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *training-true* ]] 2025-09-07T09:12:34.5131985Z + modes+=(training) 2025-09-07T09:12:34.5133266Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *inference-true* ]] 2025-09-07T09:12:34.5134635Z + modes+=(inference) 2025-09-07T09:12:34.5134904Z + targets=('accuracy' 'performance') 2025-09-07T09:12:34.5135206Z + local targets 2025-09-07T09:12:34.5135420Z + local device=cuda 2025-09-07T09:12:34.5135693Z + [[ inductor_torchbench_perf == *cpu* ]] 2025-09-07T09:12:34.5136274Z + [[ inductor_torchbench_perf == *cuda_a10g* ]] 2025-09-07T09:12:34.5136631Z + [[ inductor_torchbench_perf == *h100* ]] 2025-09-07T09:12:34.5136968Z + [[ inductor_torchbench_perf == *b200* ]] 2025-09-07T09:12:34.5137412Z + [[ inductor_torchbench_perf == *rocm* ]] 2025-09-07T09:12:34.5137734Z + for mode in "${modes[@]}" 2025-09-07T09:12:34.5138018Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:12:34.5138330Z + [[ training == \t\r\a\i\n\i\n\g ]] 2025-09-07T09:12:34.5138604Z + dtype=amp 2025-09-07T09:12:34.5138832Z + for target in "${targets[@]}" 2025-09-07T09:12:34.5139128Z + target_flag=('--accuracy') 2025-09-07T09:12:34.5139404Z + local target_flag 2025-09-07T09:12:34.5139648Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:12:34.5139966Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T09:12:34.5140296Z + target_flag+=(--no-translation-validation) 2025-09-07T09:12:34.5141682Z + [[ 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* ]] 2025-09-07T09:12:34.5144092Z + [[ 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* ]] 2025-09-07T09:12:34.5146624Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:12:35.1307131Z /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. 2025-09-07T09:12:35.1308559Z import pynvml # type: ignore[import] 2025-09-07T09:12:39.0561932Z /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. 2025-09-07T09:12:39.0563602Z import pynvml # type: ignore[import] 2025-09-07T09:12:41.9801593Z 2025-09-07T09:12:43.0189708Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:12:43.0190136Z 2025-09-07T09:12:43.0190658Z config.json: 0.00B [00:00, ?B/s] 2025-09-07T09:12:43.0191188Z config.json: 1.72kB [00:00, 11.0MB/s] 2025-09-07T09:12:48.1044420Z 2025-09-07T09:12:48.1044873Z loading model: 0it [00:06, ?it/s] 2025-09-07T09:12:48.1045273Z cuda train hf_Bart 2025-09-07T09:13:24.6557387Z W0907 09:13:24.654000 204 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:14:04.1697869Z pass 2025-09-07T09:14:09.5135132Z /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. 2025-09-07T09:14:09.5137803Z import pynvml # type: ignore[import] 2025-09-07T09:14:12.1949624Z 2025-09-07T09:14:16.4179073Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:14:16.4180584Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:14:16.4180965Z cuda train hf_Bert 2025-09-07T09:14:45.7936046Z W0907 09:14:45.792000 1036 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:15:16.9659196Z pass 2025-09-07T09:15:22.0061020Z /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. 2025-09-07T09:15:22.0063671Z import pynvml # type: ignore[import] 2025-09-07T09:15:24.9704202Z 2025-09-07T09:15:31.2746927Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:31.2747312Z loading model: 0it [00:06, ?it/s] 2025-09-07T09:15:31.2747641Z cuda train hf_Bert_large 2025-09-07T09:16:21.3338532Z W0907 09:16:21.332000 1749 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:17:29.8904363Z pass 2025-09-07T09:17:36.3390064Z /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. 2025-09-07T09:17:36.3391648Z import pynvml # type: ignore[import] 2025-09-07T09:17:39.1224607Z 2025-09-07T09:17:40.8962446Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T09:17:40.8965112Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T09:17:40.8966665Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T09:17:40.8967925Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T09:17:40.8974016Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T09:17:40.8976505Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T09:17:40.8978177Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T09:17:40.8979440Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T09:17:44.0986344Z 2025-09-07T09:17:44.0986926Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:17:44.0987441Z cuda train hf_BigBird 2025-09-07T09:18:32.1423100Z W0907 09:18:32.141000 2402 site-packages/torch/_inductor/utils.py:2298] [2/0_1] DeviceCopy in input program 2025-09-07T09:19:36.8285304Z W0907 09:19:36.827000 2402 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:20:07.9750984Z pass 2025-09-07T09:20:14.2451003Z /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. 2025-09-07T09:20:14.2457225Z import pynvml # type: ignore[import] 2025-09-07T09:20:17.0994194Z 2025-09-07T09:20:17.9907481Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:20:17.9908025Z 2025-09-07T09:20:17.9908594Z config.json: 0% 0.00/483 [00:00 will be ignored 2025-09-07T09:20:54.2020312Z pass 2025-09-07T09:20:58.5698803Z /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. 2025-09-07T09:20:58.5700339Z import pynvml # type: ignore[import] 2025-09-07T09:21:01.6268914Z 2025-09-07T09:21:02.5203600Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:21:02.5204143Z 2025-09-07T09:21:02.5204685Z config.json: 0% 0.00/665 [00:00 will be ignored 2025-09-07T09:21:58.6235091Z pass 2025-09-07T09:22:03.6359679Z /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. 2025-09-07T09:22:03.6361459Z import pynvml # type: ignore[import] 2025-09-07T09:22:06.5602381Z 2025-09-07T09:22:07.5324769Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:22:07.5325126Z 2025-09-07T09:22:07.5325871Z config.json: 0% 0.00/666 [00:00 will be ignored 2025-09-07T09:24:20.1548388Z pass 2025-09-07T09:24:25.6080273Z /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. 2025-09-07T09:24:25.6081774Z import pynvml # type: ignore[import] 2025-09-07T09:24:28.3751063Z 2025-09-07T09:24:30.6171178Z loading model: 0it [00:00, ?it/s]Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T09:24:30.6173534Z WARNING:transformers.models.reformer.modeling_reformer:Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T09:24:31.4278428Z 2025-09-07T09:24:31.4278897Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:24:31.4279381Z cuda train hf_Reformer 2025-09-07T09:24:58.4727394Z W0907 09:24:58.471000 5995 site-packages/torch/_logging/_internal.py:1199] [35/0] Profiler function will be ignored 2025-09-07T09:25:11.1622019Z pass 2025-09-07T09:25:14.8905548Z /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. 2025-09-07T09:25:14.8907066Z import pynvml # type: ignore[import] 2025-09-07T09:25:17.7080399Z 2025-09-07T09:25:18.5897176Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:25:18.5897602Z 2025-09-07T09:25:18.5898062Z config.json: 0% 0.00/615 [00:00 will be ignored 2025-09-07T09:26:25.1890261Z pass 2025-09-07T09:26:30.4475707Z /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. 2025-09-07T09:26:30.4478523Z import pynvml # type: ignore[import] 2025-09-07T09:26:33.2409833Z 2025-09-07T09:26:34.1276774Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:26:34.1277157Z 2025-09-07T09:26:34.1277758Z config.json: 0% 0.00/1.21k [00:00 will be ignored 2025-09-07T09:29:25.5973874Z pass 2025-09-07T09:29:31.2430681Z /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. 2025-09-07T09:29:31.2432192Z import pynvml # type: ignore[import] 2025-09-07T09:29:34.1828169Z 2025-09-07T09:29:35.1019403Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:35.1019717Z 2025-09-07T09:29:35.1020268Z config.json: 0% 0.00/1.21k [00:00 will be ignored 2025-09-07T09:30:26.6030902Z pass 2025-09-07T09:30:30.6088115Z /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. 2025-09-07T09:30:30.6089546Z import pynvml # type: ignore[import] 2025-09-07T09:30:34.1814972Z 2025-09-07T09:30:34.9558597Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:30:34.9559232Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:30:34.9559765Z cuda train hf_distil_whisper 2025-09-07T09:30:34.9565062Z Traceback (most recent call last): 2025-09-07T09:30:34.9565713Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:30:34.9566355Z ) = runner.load_model( 2025-09-07T09:30:34.9566909Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 325, in load_model 2025-09-07T09:30:34.9567533Z benchmark = benchmark_cls( 2025-09-07T09:30:34.9568395Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T09:30:34.9568950Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T09:30:34.9569584Z File "/torchbench/torchbenchmark/models/hf_distil_whisper/__init__.py", line 13, in __init__ 2025-09-07T09:30:34.9570259Z raise NotImplementedError("Training is not implemented.") 2025-09-07T09:30:34.9570795Z NotImplementedError: Training is not implemented. 2025-09-07T09:30:34.9571087Z 2025-09-07T09:30:34.9571245Z model_fail_to_load 2025-09-07T09:30:36.2442556Z accuracy pass_rate=80.00% 2025-09-07T09:30:36.2453429Z calls_captured gmean=0.00x mean=1442.400x 2025-09-07T09:30:36.2460817Z unique_graphs gmean=0.00x mean=3.867x 2025-09-07T09:30:36.2467149Z graph_breaks gmean=0.00x mean=6.400x 2025-09-07T09:30:36.2474007Z unique_graph_breaks gmean=0.00x mean=4.467x 2025-09-07T09:30:36.2480593Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:30:36.2487254Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:30:36.2493615Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:30:36.2495368Z compilation_latency mean=56.681 seconds 2025-09-07T09:30:37.6502545Z + [[ 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* ]] 2025-09-07T09:30:37.6506806Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:30:38.4392375Z /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. 2025-09-07T09:30:38.4395136Z import pynvml # type: ignore[import] 2025-09-07T09:30:42.7048738Z /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. 2025-09-07T09:30:42.7050243Z import pynvml # type: ignore[import] 2025-09-07T09:30:45.4966155Z 2025-09-07T09:30:51.1765779Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:30:51.1766215Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:30:51.1766639Z cuda train hf_Bart 2025-09-07T09:31:26.6108585Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:31:26.6109980Z pred = mod(**cloned_inputs) 2025-09-07T09:31:26.6110664Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1471, in forward 2025-09-07T09:31:26.6111354Z outputs = self.model( 2025-09-07T09:31:26.6112007Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1288, in forward 2025-09-07T09:31:26.6112713Z decoder_outputs = self.decoder( 2025-09-07T09:31:26.6113397Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1084, in forward 2025-09-07T09:31:26.6114300Z positions = self.embed_positions(input, past_key_values_length, position_ids=cache_position) 2025-09-07T09:31:26.6115197Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 101, in forward 2025-09-07T09:31:26.6115936Z return super().forward(position_ids + self.offset) 2025-09-07T09:31:26.6116216Z 2025-09-07T09:31:26.6116693Z 2025-09-07T09:31:26.8459814Z W0907 09:31:26.845000 9822 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:32:06.1358397Z pass 2025-09-07T09:32:11.9163443Z /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. 2025-09-07T09:32:11.9164871Z import pynvml # type: ignore[import] 2025-09-07T09:32:15.0667612Z 2025-09-07T09:32:19.3484891Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:19.3485311Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:32:19.3485622Z cuda train hf_Bert 2025-09-07T09:32:47.6925182Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:32:47.6926446Z pred = mod(**cloned_inputs) 2025-09-07T09:32:47.6927133Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 1308, in forward 2025-09-07T09:32:47.6927832Z outputs = self.bert( 2025-09-07T09:32:47.6928452Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 964, in forward 2025-09-07T09:32:47.6929160Z embedding_output = self.embeddings( 2025-09-07T09:32:47.6929851Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 186, in forward 2025-09-07T09:32:47.6931120Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T09:32:47.6931430Z 2025-09-07T09:32:47.6931435Z 2025-09-07T09:32:48.0175618Z W0907 09:32:48.016000 9960 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:33:17.3260459Z pass 2025-09-07T09:33:22.2658222Z /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. 2025-09-07T09:33:22.2659648Z import pynvml # type: ignore[import] 2025-09-07T09:33:25.0967963Z 2025-09-07T09:33:31.5877837Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:33:31.5878223Z loading model: 0it [00:06, ?it/s] 2025-09-07T09:33:31.5878548Z cuda train hf_Bert_large 2025-09-07T09:34:23.1565810Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:34:23.1567195Z pred = mod(**cloned_inputs) 2025-09-07T09:34:23.1567925Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 1308, in forward 2025-09-07T09:34:23.1568711Z outputs = self.bert( 2025-09-07T09:34:23.1569448Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 964, in forward 2025-09-07T09:34:23.1570228Z embedding_output = self.embeddings( 2025-09-07T09:34:23.1570999Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 186, in forward 2025-09-07T09:34:23.1571828Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T09:34:23.1572218Z 2025-09-07T09:34:23.1572223Z 2025-09-07T09:34:23.5836218Z W0907 09:34:23.582000 10098 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:35:31.2393814Z pass 2025-09-07T09:35:37.8954133Z /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. 2025-09-07T09:35:37.8956896Z import pynvml # type: ignore[import] 2025-09-07T09:35:40.7357118Z 2025-09-07T09:35:42.5918120Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T09:35:42.5920496Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T09:35:42.5922049Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T09:35:42.5923538Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T09:35:42.5925784Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T09:35:42.5928478Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T09:35:42.5930033Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T09:35:42.5931262Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T09:35:45.9709024Z 2025-09-07T09:35:45.9709380Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:35:45.9709866Z cuda train hf_BigBird 2025-09-07T09:37:30.5038322Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:37:30.5039716Z pred = mod(**cloned_inputs) 2025-09-07T09:37:30.5040520Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 2303, in forward 2025-09-07T09:37:30.5041366Z outputs = self.bert( 2025-09-07T09:37:30.5042121Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1991, in forward 2025-09-07T09:37:30.5043133Z encoder_outputs = self.encoder( 2025-09-07T09:37:30.5043936Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1585, in forward 2025-09-07T09:37:30.5044755Z layer_outputs = layer_module( 2025-09-07T09:37:30.5045449Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:37:30.5046189Z return super().__call__(*args, **kwargs) 2025-09-07T09:37:30.5046967Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1468, in forward 2025-09-07T09:37:30.5047794Z self_attention_outputs = self.attention( 2025-09-07T09:37:30.5049046Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1381, in forward 2025-09-07T09:37:30.5049859Z self_outputs = self.self( 2025-09-07T09:37:30.5050616Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 455, in forward 2025-09-07T09:37:30.5051467Z context_layer, attention_probs = self.bigbird_block_sparse_attention( 2025-09-07T09:37:30.5052408Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 592, in bigbird_block_sparse_attention 2025-09-07T09:37:30.5053325Z gathered_value = self.torch_gather_b2(blocked_value_matrix, rand_attn) 2025-09-07T09:37:30.5054208Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 957, in torch_gather_b2 2025-09-07T09:37:30.5055073Z out_flattened = flattened_params.index_select(0, flattened_indices) 2025-09-07T09:37:30.5055407Z 2025-09-07T09:37:30.5055415Z 2025-09-07T09:37:30.6307134Z W0907 09:37:30.629000 10236 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:38:02.2775853Z pass 2025-09-07T09:38:08.5884163Z /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. 2025-09-07T09:38:08.5885589Z import pynvml # type: ignore[import] 2025-09-07T09:38:11.3706832Z 2025-09-07T09:38:15.4060500Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:15.4061377Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:38:15.4061690Z cuda train hf_DistilBert 2025-09-07T09:38:32.6505705Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:38:32.6506947Z pred = mod(**cloned_inputs) 2025-09-07T09:38:32.6507690Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 826, in forward 2025-09-07T09:38:32.6508454Z dlbrt_output = self.distilbert( 2025-09-07T09:38:32.6509189Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 723, in forward 2025-09-07T09:38:32.6510105Z embeddings = self.embeddings(input_ids, inputs_embeds) # (bs, seq_length, dim) 2025-09-07T09:38:32.6511024Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 124, in forward 2025-09-07T09:38:32.6511990Z position_embeddings = self.position_embeddings(position_ids) # (bs, max_seq_length, dim) 2025-09-07T09:38:32.6512412Z 2025-09-07T09:38:32.6512422Z 2025-09-07T09:38:32.9316758Z W0907 09:38:32.930000 10748 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:38:47.3196762Z pass 2025-09-07T09:38:51.3872260Z /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. 2025-09-07T09:38:51.3873670Z import pynvml # type: ignore[import] 2025-09-07T09:38:54.0971813Z 2025-09-07T09:39:00.4467171Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:39:00.4468298Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:39:00.5442610Z 2025-09-07T09:39:00.5443116Z loading model: 0it [00:06, ?it/s] 2025-09-07T09:39:00.5443479Z cuda train hf_GPT2 2025-09-07T09:39:27.6676563Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 1183, in forward 2025-09-07T09:39:27.6677797Z transformer_outputs = self.transformer( 2025-09-07T09:39:27.6678512Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 860, in forward 2025-09-07T09:39:27.6679237Z position_embeds = self.wpe(position_ids) 2025-09-07T09:39:27.6679505Z 2025-09-07T09:39:27.6679510Z 2025-09-07T09:39:27.8951671Z W0907 09:39:27.894000 10886 site-packages/torch/_logging/_internal.py:1199] [11/0] Profiler function will be ignored 2025-09-07T09:39:48.5270598Z pass 2025-09-07T09:39:53.2319513Z /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. 2025-09-07T09:39:53.2320930Z import pynvml # type: ignore[import] 2025-09-07T09:39:55.9942916Z 2025-09-07T09:40:12.4245176Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:40:12.4246275Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:40:12.5993056Z 2025-09-07T09:40:12.5993414Z loading model: 0it [00:16, ?it/s] 2025-09-07T09:40:12.5993809Z cuda train hf_GPT2_large 2025-09-07T09:40:12.6227186Z pass_due_to_skip 2025-09-07T09:40:14.5829493Z /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. 2025-09-07T09:40:14.5830897Z import pynvml # type: ignore[import] 2025-09-07T09:40:17.2887588Z 2025-09-07T09:40:22.6606627Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:40:22.6607014Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:40:22.6607347Z cuda train hf_Longformer 2025-09-07T09:40:26.0396787Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T09:40:26.0398842Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T09:40:26.0400429Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] or: 2025-09-07T09:40:26.0401991Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T09:40:26.0404360Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] to include these operations in the captured graph. 2025-09-07T09:40:26.0405913Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T09:40:26.0407320Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break: from user code at: 2025-09-07T09:40:26.0409912Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:40:26.0412519Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] pred = mod(**cloned_inputs) 2025-09-07T09:40:26.0415557Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1703, in forward 2025-09-07T09:40:26.0418277Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] outputs = self.longformer( 2025-09-07T09:40:26.0420777Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1600, in forward 2025-09-07T09:40:26.0423461Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] encoder_outputs = self.encoder( 2025-09-07T09:40:26.0426087Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1244, in forward 2025-09-07T09:40:26.0428802Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] is_global_attn = is_index_global_attn.flatten().any().item() 2025-09-07T09:40:26.0430430Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T09:40:26.0431585Z W0907 09:40:26.038000 11070 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T09:41:34.7521433Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1259, in torch_dynamo_resume_in_forward_at_1244 2025-09-07T09:41:34.7524699Z layer_outputs = layer_module( 2025-09-07T09:41:34.7525719Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:41:34.7526797Z return super().__call__(*args, **kwargs) 2025-09-07T09:41:34.7528019Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1199, in forward 2025-09-07T09:41:34.7529407Z self_attn_outputs = self.attention( 2025-09-07T09:41:34.7530616Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1135, in forward 2025-09-07T09:41:34.7531877Z self_outputs = self.self( 2025-09-07T09:41:34.7533002Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 613, in forward 2025-09-07T09:41:34.7534356Z attn_output = self._sliding_chunks_matmul_attn_probs_value( 2025-09-07T09:41:34.7535866Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 874, in _sliding_chunks_matmul_attn_probs_value 2025-09-07T09:41:34.7537662Z chunked_value = padded_value.as_strided(size=chunked_value_size, stride=chunked_value_stride) 2025-09-07T09:41:34.7538327Z 2025-09-07T09:41:34.7538336Z 2025-09-07T09:41:35.5415247Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1596, in forward 2025-09-07T09:41:35.5416607Z embedding_output = self.embeddings( 2025-09-07T09:41:35.5417431Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 425, in forward 2025-09-07T09:41:35.5418296Z token_type_embeddings = self.token_type_embeddings(token_type_ids) 2025-09-07T09:41:35.5418624Z 2025-09-07T09:41:35.5418655Z 2025-09-07T09:41:35.5612290Z W0907 09:41:35.560000 11070 site-packages/torch/_logging/_internal.py:1199] [19/0] Profiler function will be ignored 2025-09-07T09:42:06.8087202Z pass 2025-09-07T09:42:11.8364360Z /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. 2025-09-07T09:42:11.8366034Z import pynvml # type: ignore[import] 2025-09-07T09:42:14.6335488Z 2025-09-07T09:42:16.8325776Z loading model: 0it [00:00, ?it/s]Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T09:42:16.8328173Z WARNING:transformers.models.reformer.modeling_reformer:Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T09:42:17.6520729Z 2025-09-07T09:42:17.6521218Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:42:17.6521696Z cuda train hf_Reformer 2025-09-07T09:42:23.5719842Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:42:23.5720798Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2095, in forward 2025-09-07T09:42:23.5721775Z least_common_mult_chunk_length = _get_least_common_mult_chunk_len(self.config) 2025-09-07T09:42:23.5723044Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 194, in _get_least_common_mult_chunk_len 2025-09-07T09:42:23.5724124Z return np.lcm(config.lsh_attn_chunk_length, config.local_attn_chunk_length) 2025-09-07T09:42:23.5725118Z 2025-09-07T09:42:23.5725311Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:42:23.5726199Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2099, in forward 2025-09-07T09:42:23.5727078Z input_shape[-1] % least_common_mult_chunk_length != 0 2025-09-07T09:42:23.5727373Z 2025-09-07T09:42:33.1614114Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T09:42:33.1615562Z attn_outputs = self.attention( 2025-09-07T09:42:33.1616378Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T09:42:33.1617329Z self_attention_outputs = self.self_attention( 2025-09-07T09:42:33.1618195Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T09:42:33.1619243Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T09:42:33.1620456Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T09:42:33.1621536Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T09:42:33.1621875Z 2025-09-07T09:42:33.1621879Z 2025-09-07T09:42:35.5916008Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T09:42:35.5918952Z attn_outputs = self.attention( 2025-09-07T09:42:35.5920556Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T09:42:35.5922211Z self_attention_outputs = self.self_attention( 2025-09-07T09:42:35.5933531Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T09:42:35.5935727Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T09:42:35.5938170Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T09:42:35.5940206Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T09:42:35.5940890Z 2025-09-07T09:42:35.5940900Z 2025-09-07T09:42:37.1094265Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T09:42:37.1095738Z attn_outputs = self.attention( 2025-09-07T09:42:37.1096574Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T09:42:37.1097517Z self_attention_outputs = self.self_attention( 2025-09-07T09:42:37.1098373Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T09:42:37.1099417Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T09:42:37.1100646Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T09:42:37.1102127Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T09:42:37.1102471Z 2025-09-07T09:42:37.1102476Z 2025-09-07T09:42:39.6793190Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2132, in torch_dynamo_resume_in_forward_at_2104 2025-09-07T09:42:39.6794695Z embedding_output = self.embeddings( 2025-09-07T09:42:39.6795525Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 357, in forward 2025-09-07T09:42:39.6796395Z inputs_embeds = self.word_embeddings(input_ids) 2025-09-07T09:42:39.6796687Z 2025-09-07T09:42:39.6796693Z 2025-09-07T09:42:39.6960303Z W0907 09:42:39.695000 11208 site-packages/torch/_logging/_internal.py:1199] [35/0] Profiler function will be ignored 2025-09-07T09:42:50.2796553Z pass 2025-09-07T09:42:54.1673454Z /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. 2025-09-07T09:42:54.1674971Z import pynvml # type: ignore[import] 2025-09-07T09:42:56.8870790Z 2025-09-07T09:43:05.1743129Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:43:05.1743599Z loading model: 0it [00:08, ?it/s] 2025-09-07T09:43:05.1744009Z cuda train hf_Roberta_base 2025-09-07T09:43:33.8333432Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:43:33.8334774Z pred = mod(**cloned_inputs) 2025-09-07T09:43:33.8335560Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 1094, in forward 2025-09-07T09:43:33.8336436Z outputs = self.roberta( 2025-09-07T09:43:33.8337750Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 817, in forward 2025-09-07T09:43:33.8338621Z embedding_output = self.embeddings( 2025-09-07T09:43:33.8339459Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 118, in forward 2025-09-07T09:43:33.8340349Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T09:43:33.8340736Z 2025-09-07T09:43:33.8340741Z 2025-09-07T09:43:34.0971005Z W0907 09:43:34.096000 11435 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:44:03.5295626Z pass 2025-09-07T09:44:08.4908637Z /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. 2025-09-07T09:44:08.4910203Z import pynvml # type: ignore[import] 2025-09-07T09:44:11.3166703Z 2025-09-07T09:44:15.1281826Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:44:15.1282299Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:44:15.1282658Z cuda train hf_T5 2025-09-07T09:44:50.4309262Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:44:50.4310622Z pred = mod(**cloned_inputs) 2025-09-07T09:44:50.4311368Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T09:44:50.4312565Z decoder_outputs = self.decoder( 2025-09-07T09:44:50.4313311Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T09:44:50.4314093Z layer_outputs = layer_module( 2025-09-07T09:44:50.4314807Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:44:50.4315552Z return super().__call__(*args, **kwargs) 2025-09-07T09:44:50.4316262Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 681, in forward 2025-09-07T09:44:50.4317034Z self_attention_outputs = self.layer[0]( 2025-09-07T09:44:50.4317790Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 599, in forward 2025-09-07T09:44:50.4318558Z attention_output = self.SelfAttention( 2025-09-07T09:44:50.4319272Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 539, in forward 2025-09-07T09:44:50.4320040Z position_bias = self.compute_bias( 2025-09-07T09:44:50.4320825Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 463, in compute_bias 2025-09-07T09:44:50.4321876Z values = self.relative_attention_bias(relative_position_bucket) # shape (query_length, key_length, num_heads) 2025-09-07T09:44:50.4322386Z 2025-09-07T09:44:50.4322391Z 2025-09-07T09:44:51.5080442Z pass 2025-09-07T09:44:55.4038975Z /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. 2025-09-07T09:44:55.4041765Z import pynvml # type: ignore[import] 2025-09-07T09:44:58.1507443Z 2025-09-07T09:45:03.9254738Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:45:03.9255492Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:45:03.9256199Z cuda train hf_T5_base 2025-09-07T09:45:05.2353932Z WARNING:common:fp64 golden ref were not generated for hf_T5_base. Setting accuracy check to cosine 2025-09-07T09:46:09.7629554Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:46:09.7630974Z pred = mod(**cloned_inputs) 2025-09-07T09:46:09.7631729Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T09:46:09.7632511Z decoder_outputs = self.decoder( 2025-09-07T09:46:09.7633259Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T09:46:09.7634017Z layer_outputs = layer_module( 2025-09-07T09:46:09.7634700Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:46:09.7635438Z return super().__call__(*args, **kwargs) 2025-09-07T09:46:09.7636173Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 681, in forward 2025-09-07T09:46:09.7636948Z self_attention_outputs = self.layer[0]( 2025-09-07T09:46:09.7637632Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 599, in forward 2025-09-07T09:46:09.7638299Z attention_output = self.SelfAttention( 2025-09-07T09:46:09.7638962Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 539, in forward 2025-09-07T09:46:09.7639635Z position_bias = self.compute_bias( 2025-09-07T09:46:09.7640319Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 463, in compute_bias 2025-09-07T09:46:09.7641570Z values = self.relative_attention_bias(relative_position_bucket) # shape (query_length, key_length, num_heads) 2025-09-07T09:46:09.7642098Z 2025-09-07T09:46:09.7642103Z 2025-09-07T09:46:10.1112560Z W0907 09:46:10.110000 11710 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:46:52.5250306Z pass 2025-09-07T09:46:58.3049628Z /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. 2025-09-07T09:46:58.3052428Z import pynvml # type: ignore[import] 2025-09-07T09:47:01.2546317Z 2025-09-07T09:47:13.4689074Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:13.4689555Z loading model: 0it [00:12, ?it/s] 2025-09-07T09:47:13.4689954Z cuda train hf_T5_large 2025-09-07T09:47:13.4923037Z pass_due_to_skip 2025-09-07T09:47:15.4421196Z /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. 2025-09-07T09:47:15.4423970Z import pynvml # type: ignore[import] 2025-09-07T09:47:18.0877572Z 2025-09-07T09:47:20.8296395Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:20.8296953Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:47:20.8297380Z cuda train hf_Whisper 2025-09-07T09:47:37.4495797Z W0907 09:47:37.448000 11889 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:47:47.1168637Z pass 2025-09-07T09:47:51.2659766Z /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. 2025-09-07T09:47:51.2661714Z import pynvml # type: ignore[import] 2025-09-07T09:47:54.0253901Z 2025-09-07T09:47:54.5203243Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:54.5203950Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:54.5204663Z cuda train hf_distil_whisper 2025-09-07T09:47:54.5208732Z Traceback (most recent call last): 2025-09-07T09:47:54.5209818Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:47:54.5210900Z ) = runner.load_model( 2025-09-07T09:47:54.5211900Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 325, in load_model 2025-09-07T09:47:54.5213082Z benchmark = benchmark_cls( 2025-09-07T09:47:54.5213956Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T09:47:54.5214968Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T09:47:54.5216061Z File "/torchbench/torchbenchmark/models/hf_distil_whisper/__init__.py", line 13, in __init__ 2025-09-07T09:47:54.5217444Z raise NotImplementedError("Training is not implemented.") 2025-09-07T09:47:54.5218412Z NotImplementedError: Training is not implemented. 2025-09-07T09:47:54.5218951Z 2025-09-07T09:47:54.5219211Z model_fail_to_load 2025-09-07T09:47:55.4881208Z accuracy pass_rate=80.00% 2025-09-07T09:47:55.4888454Z calls_captured gmean=0.00x mean=1418.067x 2025-09-07T09:47:55.4892934Z unique_graphs gmean=0.00x mean=3.867x 2025-09-07T09:47:55.4897168Z graph_breaks gmean=0.00x mean=6.400x 2025-09-07T09:47:55.4901589Z unique_graph_breaks gmean=0.00x mean=4.467x 2025-09-07T09:47:55.4905874Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:47:55.4909856Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:47:55.4915632Z cudagraph_skips gmean=0.00x mean=1.067x 2025-09-07T09:47:55.4916024Z compilation_latency mean=53.487 seconds 2025-09-07T09:47:56.5619545Z + [[ 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* ]] 2025-09-07T09:47:56.5622340Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:47:57.1778637Z /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. 2025-09-07T09:47:57.1781535Z import pynvml # type: ignore[import] 2025-09-07T09:48:00.9533868Z /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. 2025-09-07T09:48:00.9536509Z import pynvml # type: ignore[import] 2025-09-07T09:48:03.7595202Z 2025-09-07T09:48:09.4215505Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:48:09.4215899Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:48:09.4217230Z cuda train hf_Bart 2025-09-07T09:48:22.1955767Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:48:22.1957018Z pred = mod(**cloned_inputs) 2025-09-07T09:48:22.1957729Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1471, in forward 2025-09-07T09:48:22.1958434Z outputs = self.model( 2025-09-07T09:48:22.1959509Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1288, in forward 2025-09-07T09:48:22.1960218Z decoder_outputs = self.decoder( 2025-09-07T09:48:22.1960901Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1084, in forward 2025-09-07T09:48:22.1961802Z positions = self.embed_positions(input, past_key_values_length, position_ids=cache_position) 2025-09-07T09:48:22.1962696Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 101, in forward 2025-09-07T09:48:22.1963700Z return super().forward(position_ids + self.offset) 2025-09-07T09:48:22.1963977Z 2025-09-07T09:48:22.1963990Z 2025-09-07T09:48:23.1425756Z W0907 09:48:23.141000 12081 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:48:29.3832623Z pass 2025-09-07T09:48:32.7308100Z /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. 2025-09-07T09:48:32.7309516Z import pynvml # type: ignore[import] 2025-09-07T09:48:35.6689404Z 2025-09-07T09:48:40.6021215Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:48:40.6021594Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:48:40.6023115Z cuda train hf_Bert 2025-09-07T09:48:52.2943648Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:48:52.2946610Z pred = mod(**cloned_inputs) 2025-09-07T09:48:52.2947916Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 1308, in forward 2025-09-07T09:48:52.2949213Z outputs = self.bert( 2025-09-07T09:48:52.2950421Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 964, in forward 2025-09-07T09:48:52.2951757Z embedding_output = self.embeddings( 2025-09-07T09:48:52.2953053Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 186, in forward 2025-09-07T09:48:52.2954541Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T09:48:52.2955120Z 2025-09-07T09:48:52.2955128Z 2025-09-07T09:48:53.3469032Z W0907 09:48:53.346000 12261 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:48:58.1115135Z pass 2025-09-07T09:49:01.4705131Z /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. 2025-09-07T09:49:01.4706541Z import pynvml # type: ignore[import] 2025-09-07T09:49:05.1035184Z 2025-09-07T09:49:13.2174309Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:49:13.2174932Z loading model: 0it [00:08, ?it/s] 2025-09-07T09:49:13.2175917Z cuda train hf_Bert_large 2025-09-07T09:49:28.9202158Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:49:28.9203629Z pred = mod(**cloned_inputs) 2025-09-07T09:49:28.9204317Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 1308, in forward 2025-09-07T09:49:28.9205011Z outputs = self.bert( 2025-09-07T09:49:28.9206121Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 964, in forward 2025-09-07T09:49:28.9206834Z embedding_output = self.embeddings( 2025-09-07T09:49:28.9207516Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 186, in forward 2025-09-07T09:49:28.9208301Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T09:49:28.9208625Z 2025-09-07T09:49:28.9208630Z 2025-09-07T09:49:30.7872392Z W0907 09:49:30.786000 12421 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:49:41.3552065Z pass 2025-09-07T09:49:45.5629443Z /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. 2025-09-07T09:49:45.5630930Z import pynvml # type: ignore[import] 2025-09-07T09:49:48.6128387Z 2025-09-07T09:49:50.3681350Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T09:49:50.3683811Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T09:49:50.3685802Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T09:49:50.3686967Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T09:49:50.3689193Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T09:49:50.3691417Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T09:49:50.3692874Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T09:49:50.3694029Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T09:49:53.6567957Z 2025-09-07T09:49:53.6568384Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:49:53.6569962Z cuda train hf_BigBird 2025-09-07T09:50:45.3492518Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:50:45.3493792Z pred = mod(**cloned_inputs) 2025-09-07T09:50:45.3494492Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 2303, in forward 2025-09-07T09:50:45.3495247Z outputs = self.bert( 2025-09-07T09:50:45.3495923Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1991, in forward 2025-09-07T09:50:45.3496651Z encoder_outputs = self.encoder( 2025-09-07T09:50:45.3497940Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1585, in forward 2025-09-07T09:50:45.3498673Z layer_outputs = layer_module( 2025-09-07T09:50:45.3499314Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:50:45.3499954Z return super().__call__(*args, **kwargs) 2025-09-07T09:50:45.3500688Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1468, in forward 2025-09-07T09:50:45.3501434Z self_attention_outputs = self.attention( 2025-09-07T09:50:45.3502164Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1381, in forward 2025-09-07T09:50:45.3502891Z self_outputs = self.self( 2025-09-07T09:50:45.3503560Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 455, in forward 2025-09-07T09:50:45.3504389Z context_layer, attention_probs = self.bigbird_block_sparse_attention( 2025-09-07T09:50:45.3505330Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 592, in bigbird_block_sparse_attention 2025-09-07T09:50:45.3506263Z gathered_value = self.torch_gather_b2(blocked_value_matrix, rand_attn) 2025-09-07T09:50:45.3507136Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 957, in torch_gather_b2 2025-09-07T09:50:45.3507992Z out_flattened = flattened_params.index_select(0, flattened_indices) 2025-09-07T09:50:45.3508334Z 2025-09-07T09:50:45.3508526Z 2025-09-07T09:50:45.4199018Z W0907 09:50:45.419000 12581 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:50:52.7513588Z pass 2025-09-07T09:50:56.5529277Z /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. 2025-09-07T09:50:56.5531941Z import pynvml # type: ignore[import] 2025-09-07T09:50:59.2553910Z 2025-09-07T09:51:02.8953913Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:02.8954303Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:51:02.8954704Z cuda train hf_DistilBert 2025-09-07T09:51:12.5206408Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:51:12.5207683Z pred = mod(**cloned_inputs) 2025-09-07T09:51:12.5208443Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 826, in forward 2025-09-07T09:51:12.5209209Z dlbrt_output = self.distilbert( 2025-09-07T09:51:12.5209952Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 723, in forward 2025-09-07T09:51:12.5210860Z embeddings = self.embeddings(input_ids, inputs_embeds) # (bs, seq_length, dim) 2025-09-07T09:51:12.5211759Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 124, in forward 2025-09-07T09:51:12.5212708Z position_embeddings = self.position_embeddings(position_ids) # (bs, max_seq_length, dim) 2025-09-07T09:51:12.5213148Z 2025-09-07T09:51:12.5213159Z 2025-09-07T09:51:13.2728785Z W0907 09:51:13.271000 12742 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:51:15.8806700Z pass 2025-09-07T09:51:19.2693946Z /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. 2025-09-07T09:51:19.2696683Z import pynvml # type: ignore[import] 2025-09-07T09:51:22.0304015Z 2025-09-07T09:51:28.4589765Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:51:28.4590868Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:51:28.5501225Z 2025-09-07T09:51:28.5501483Z loading model: 0it [00:06, ?it/s] 2025-09-07T09:51:28.5502392Z cuda train hf_GPT2 2025-09-07T09:51:42.2385713Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 1183, in forward 2025-09-07T09:51:42.2388103Z transformer_outputs = self.transformer( 2025-09-07T09:51:42.2389494Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 860, in forward 2025-09-07T09:51:42.2390707Z position_embeds = self.wpe(position_ids) 2025-09-07T09:51:42.2391142Z 2025-09-07T09:51:42.2391151Z 2025-09-07T09:51:43.6886228Z W0907 09:51:43.687000 12902 site-packages/torch/_logging/_internal.py:1199] [11/0] Profiler function will be ignored 2025-09-07T09:51:46.9459130Z pass 2025-09-07T09:51:51.3397505Z /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. 2025-09-07T09:51:51.3399358Z import pynvml # type: ignore[import] 2025-09-07T09:51:54.0661280Z 2025-09-07T09:52:10.4779344Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:52:10.4780437Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T09:52:10.6561473Z 2025-09-07T09:52:10.6561843Z loading model: 0it [00:16, ?it/s] 2025-09-07T09:52:10.6563316Z cuda train hf_GPT2_large 2025-09-07T09:52:10.6803470Z pass_due_to_skip 2025-09-07T09:52:12.7544428Z /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. 2025-09-07T09:52:12.7545883Z import pynvml # type: ignore[import] 2025-09-07T09:52:15.7324855Z 2025-09-07T09:52:21.1736145Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:21.1736513Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:52:21.1738171Z cuda train hf_Longformer 2025-09-07T09:52:28.1713914Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T09:52:28.1715989Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T09:52:28.1717677Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] or: 2025-09-07T09:52:28.1719311Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T09:52:28.1721895Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] to include these operations in the captured graph. 2025-09-07T09:52:28.1723921Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T09:52:28.1725444Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break: from user code at: 2025-09-07T09:52:28.1728092Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:52:28.1730687Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] pred = mod(**cloned_inputs) 2025-09-07T09:52:28.1733352Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1703, in forward 2025-09-07T09:52:28.1736025Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] outputs = self.longformer( 2025-09-07T09:52:28.1738715Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1600, in forward 2025-09-07T09:52:28.1741424Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] encoder_outputs = self.encoder( 2025-09-07T09:52:28.1744118Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1244, in forward 2025-09-07T09:52:28.1747385Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] is_global_attn = is_index_global_attn.flatten().any().item() 2025-09-07T09:52:28.1749227Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T09:52:28.1750457Z W0907 09:52:28.170000 13108 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T09:52:32.4541833Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1596, in forward 2025-09-07T09:52:32.4543197Z embedding_output = self.embeddings( 2025-09-07T09:52:32.4543958Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 425, in forward 2025-09-07T09:52:32.4544828Z token_type_embeddings = self.token_type_embeddings(token_type_ids) 2025-09-07T09:52:32.4545188Z 2025-09-07T09:52:32.4545193Z 2025-09-07T09:52:37.3749685Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1259, in torch_dynamo_resume_in_forward_at_1244 2025-09-07T09:52:37.3751083Z layer_outputs = layer_module( 2025-09-07T09:52:37.3751708Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:52:37.3752364Z return super().__call__(*args, **kwargs) 2025-09-07T09:52:37.3753130Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1199, in forward 2025-09-07T09:52:37.3753901Z self_attn_outputs = self.attention( 2025-09-07T09:52:37.3754643Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1135, in forward 2025-09-07T09:52:37.3755413Z self_outputs = self.self( 2025-09-07T09:52:37.3756131Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 613, in forward 2025-09-07T09:52:37.3764065Z attn_output = self._sliding_chunks_matmul_attn_probs_value( 2025-09-07T09:52:37.3765285Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 874, in _sliding_chunks_matmul_attn_probs_value 2025-09-07T09:52:37.3766380Z chunked_value = padded_value.as_strided(size=chunked_value_size, stride=chunked_value_stride) 2025-09-07T09:52:37.3766824Z 2025-09-07T09:52:37.3766828Z 2025-09-07T09:52:38.8390178Z W0907 09:52:38.838000 13108 site-packages/torch/_logging/_internal.py:1199] [19/0] Profiler function will be ignored 2025-09-07T09:52:44.0840600Z pass 2025-09-07T09:52:47.3957605Z /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. 2025-09-07T09:52:47.3960526Z import pynvml # type: ignore[import] 2025-09-07T09:52:50.1756205Z 2025-09-07T09:52:52.1089385Z loading model: 0it [00:00, ?it/s]Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T09:52:52.1091754Z WARNING:transformers.models.reformer.modeling_reformer:Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T09:52:52.9200066Z 2025-09-07T09:52:52.9200906Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:52:52.9201786Z cuda train hf_Reformer 2025-09-07T09:53:04.0218839Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2132, in torch_dynamo_resume_in_forward_at_2104 2025-09-07T09:53:04.0220289Z embedding_output = self.embeddings( 2025-09-07T09:53:04.0221119Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 357, in forward 2025-09-07T09:53:04.0221978Z inputs_embeds = self.word_embeddings(input_ids) 2025-09-07T09:53:04.0222264Z 2025-09-07T09:53:04.0222309Z 2025-09-07T09:53:06.3867966Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T09:53:06.3869445Z attn_outputs = self.attention( 2025-09-07T09:53:06.3870270Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T09:53:06.3871093Z self_attention_outputs = self.self_attention( 2025-09-07T09:53:06.3871933Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T09:53:06.3872967Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T09:53:06.3874179Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T09:53:06.3875259Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T09:53:06.3875595Z 2025-09-07T09:53:06.3875606Z 2025-09-07T09:53:07.9273634Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T09:53:07.9275142Z attn_outputs = self.attention( 2025-09-07T09:53:07.9275955Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T09:53:07.9276815Z self_attention_outputs = self.self_attention( 2025-09-07T09:53:07.9277661Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T09:53:07.9278661Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T09:53:07.9279876Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T09:53:07.9280962Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T09:53:07.9281302Z 2025-09-07T09:53:07.9281307Z 2025-09-07T09:53:09.1145621Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T09:53:09.1147058Z attn_outputs = self.attention( 2025-09-07T09:53:09.1147874Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T09:53:09.1148699Z self_attention_outputs = self.self_attention( 2025-09-07T09:53:09.1149552Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T09:53:09.1150934Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T09:53:09.1152155Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T09:53:09.1153240Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T09:53:09.1153581Z 2025-09-07T09:53:09.1153585Z 2025-09-07T09:53:09.9290164Z W0907 09:53:09.927000 13300 site-packages/torch/_logging/_internal.py:1199] [35/0] Profiler function will be ignored 2025-09-07T09:53:12.4205273Z pass 2025-09-07T09:53:15.8476240Z /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. 2025-09-07T09:53:15.8478659Z import pynvml # type: ignore[import] 2025-09-07T09:53:20.0070759Z 2025-09-07T09:53:28.9210259Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:28.9211008Z loading model: 0it [00:08, ?it/s] 2025-09-07T09:53:28.9211739Z cuda train hf_Roberta_base 2025-09-07T09:53:41.0740030Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:53:41.0742633Z pred = mod(**cloned_inputs) 2025-09-07T09:53:41.0744179Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 1094, in forward 2025-09-07T09:53:41.0745778Z outputs = self.roberta( 2025-09-07T09:53:41.0747269Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 817, in forward 2025-09-07T09:53:41.0748952Z embedding_output = self.embeddings( 2025-09-07T09:53:41.0750524Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 118, in forward 2025-09-07T09:53:41.0752819Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T09:53:41.0753514Z 2025-09-07T09:53:41.0753523Z 2025-09-07T09:53:42.0887217Z W0907 09:53:42.087000 13478 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:53:46.8116563Z pass 2025-09-07T09:53:50.4685786Z /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. 2025-09-07T09:53:50.4688568Z import pynvml # type: ignore[import] 2025-09-07T09:53:53.1687890Z 2025-09-07T09:53:56.8558911Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:56.8559390Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:53:56.8559800Z cuda train hf_T5 2025-09-07T09:54:09.7318360Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:54:09.7319643Z pred = mod(**cloned_inputs) 2025-09-07T09:54:09.7320310Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T09:54:09.7320999Z decoder_outputs = self.decoder( 2025-09-07T09:54:09.7321643Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T09:54:09.7322312Z layer_outputs = layer_module( 2025-09-07T09:54:09.7323164Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:54:09.7324239Z return super().__call__(*args, **kwargs) 2025-09-07T09:54:09.7324918Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 681, in forward 2025-09-07T09:54:09.7325593Z self_attention_outputs = self.layer[0]( 2025-09-07T09:54:09.7326267Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 599, in forward 2025-09-07T09:54:09.7326950Z attention_output = self.SelfAttention( 2025-09-07T09:54:09.7327624Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 539, in forward 2025-09-07T09:54:09.7328287Z position_bias = self.compute_bias( 2025-09-07T09:54:09.7328973Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 463, in compute_bias 2025-09-07T09:54:09.7329947Z values = self.relative_attention_bias(relative_position_bucket) # shape (query_length, key_length, num_heads) 2025-09-07T09:54:09.7330443Z 2025-09-07T09:54:09.7330461Z 2025-09-07T09:54:11.6941358Z pass 2025-09-07T09:54:15.1916902Z /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. 2025-09-07T09:54:15.1918317Z import pynvml # type: ignore[import] 2025-09-07T09:54:17.9851858Z 2025-09-07T09:54:23.6726902Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:54:23.6727282Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:54:23.6727609Z cuda train hf_T5_base 2025-09-07T09:54:24.9823605Z WARNING:common:fp64 golden ref were not generated for hf_T5_base. Setting accuracy check to cosine 2025-09-07T09:54:42.6159999Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:54:42.6161297Z pred = mod(**cloned_inputs) 2025-09-07T09:54:42.6162426Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T09:54:42.6163413Z decoder_outputs = self.decoder( 2025-09-07T09:54:42.6164084Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T09:54:42.6164772Z layer_outputs = layer_module( 2025-09-07T09:54:42.6165375Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T09:54:42.6166023Z return super().__call__(*args, **kwargs) 2025-09-07T09:54:42.6166688Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 681, in forward 2025-09-07T09:54:42.6167371Z self_attention_outputs = self.layer[0]( 2025-09-07T09:54:42.6168026Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 599, in forward 2025-09-07T09:54:42.6168709Z attention_output = self.SelfAttention( 2025-09-07T09:54:42.6169374Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 539, in forward 2025-09-07T09:54:42.6170045Z position_bias = self.compute_bias( 2025-09-07T09:54:42.6170726Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 463, in compute_bias 2025-09-07T09:54:42.6171670Z values = self.relative_attention_bias(relative_position_bucket) # shape (query_length, key_length, num_heads) 2025-09-07T09:54:42.6172180Z 2025-09-07T09:54:42.6172184Z 2025-09-07T09:54:44.2193967Z W0907 09:54:44.218000 13798 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:54:51.6332156Z pass 2025-09-07T09:54:55.4296693Z /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. 2025-09-07T09:54:55.4298157Z import pynvml # type: ignore[import] 2025-09-07T09:54:58.3512520Z 2025-09-07T09:55:11.2742187Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:11.2742577Z loading model: 0it [00:12, ?it/s] 2025-09-07T09:55:11.2742891Z cuda train hf_T5_large 2025-09-07T09:55:11.2980867Z pass_due_to_skip 2025-09-07T09:55:13.2640568Z /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. 2025-09-07T09:55:13.2642004Z import pynvml # type: ignore[import] 2025-09-07T09:55:16.1732436Z 2025-09-07T09:55:18.8679327Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:18.8679727Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:55:18.8680058Z cuda train hf_Whisper 2025-09-07T09:55:29.4463628Z W0907 09:55:29.445000 14000 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:55:31.6410690Z pass 2025-09-07T09:55:34.8130131Z /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. 2025-09-07T09:55:34.8131556Z import pynvml # type: ignore[import] 2025-09-07T09:55:37.5219982Z 2025-09-07T09:55:38.0151118Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:38.0151737Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:38.0152290Z cuda train hf_distil_whisper 2025-09-07T09:55:38.0157742Z Traceback (most recent call last): 2025-09-07T09:55:38.0159238Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:55:38.0160198Z ) = runner.load_model( 2025-09-07T09:55:38.0161093Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 325, in load_model 2025-09-07T09:55:38.0162138Z benchmark = benchmark_cls( 2025-09-07T09:55:38.0163276Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T09:55:38.0164176Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T09:55:38.0165210Z File "/torchbench/torchbenchmark/models/hf_distil_whisper/__init__.py", line 13, in __init__ 2025-09-07T09:55:38.0166404Z raise NotImplementedError("Training is not implemented.") 2025-09-07T09:55:38.0167286Z NotImplementedError: Training is not implemented. 2025-09-07T09:55:38.0167800Z 2025-09-07T09:55:38.0167967Z model_fail_to_load 2025-09-07T09:55:39.1884197Z accuracy pass_rate=80.00% 2025-09-07T09:55:39.1894164Z calls_captured gmean=0.00x mean=1418.067x 2025-09-07T09:55:39.1901433Z unique_graphs gmean=0.00x mean=3.867x 2025-09-07T09:55:39.1907852Z graph_breaks gmean=0.00x mean=6.400x 2025-09-07T09:55:39.1914608Z unique_graph_breaks gmean=0.00x mean=4.467x 2025-09-07T09:55:39.1921314Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:55:39.1928398Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:55:39.1935013Z cudagraph_skips gmean=0.00x mean=1.067x 2025-09-07T09:55:39.1936919Z compilation_latency mean=15.964 seconds 2025-09-07T09:55:40.3149152Z + [[ 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* ]] 2025-09-07T09:55:40.3153823Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T09:55:40.3155324Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:55:40.9338312Z /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. 2025-09-07T09:55:40.9339695Z import pynvml # type: ignore[import] 2025-09-07T09:55:44.8683676Z /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. 2025-09-07T09:55:44.8685126Z import pynvml # type: ignore[import] 2025-09-07T09:55:47.5211180Z 2025-09-07T09:55:53.3477452Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:53.3477826Z loading model: 0it [00:05, ?it/s] 2025-09-07T09:55:53.3478151Z cuda train hf_Bart 2025-09-07T09:57:22.6343603Z W0907 09:57:22.633000 14234 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T09:58:27.8955716Z pass 2025-09-07T09:58:34.3232382Z /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. 2025-09-07T09:58:34.3233798Z import pynvml # type: ignore[import] 2025-09-07T09:58:37.1623960Z 2025-09-07T09:58:41.4178273Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:58:41.4178659Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:58:41.4178973Z cuda train hf_Bert 2025-09-07T09:59:40.8270123Z W0907 09:59:40.826000 15099 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:00:27.5650060Z pass 2025-09-07T10:00:33.2778205Z /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. 2025-09-07T10:00:33.2779622Z import pynvml # type: ignore[import] 2025-09-07T10:00:36.0969154Z 2025-09-07T10:00:42.6025163Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:00:42.6025695Z loading model: 0it [00:06, ?it/s] 2025-09-07T10:00:42.6026212Z cuda train hf_Bert_large 2025-09-07T10:02:39.7138575Z W0907 10:02:39.712000 15467 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:04:35.7587080Z pass 2025-09-07T10:04:44.0330585Z /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. 2025-09-07T10:04:44.0333233Z import pynvml # type: ignore[import] 2025-09-07T10:04:46.9506080Z 2025-09-07T10:04:48.7054160Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T10:04:48.7058900Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T10:04:48.7060377Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T10:04:48.7061535Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T10:04:48.7063802Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T10:04:48.7066030Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T10:04:48.7067482Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T10:04:48.7068629Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T10:04:52.1335005Z 2025-09-07T10:04:52.1335429Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:04:52.1335834Z cuda train hf_BigBird 2025-09-07T10:05:40.5729312Z W0907 10:05:40.572000 15795 site-packages/torch/_inductor/utils.py:2298] [2/0_1] DeviceCopy in input program 2025-09-07T10:08:16.3118873Z W0907 10:08:16.310000 15795 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:09:05.4389258Z pass 2025-09-07T10:09:13.5090362Z /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. 2025-09-07T10:09:13.5093504Z import pynvml # type: ignore[import] 2025-09-07T10:09:16.2088775Z 2025-09-07T10:09:20.1906563Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:09:20.1906942Z loading model: 0it [00:03, ?it/s] 2025-09-07T10:09:20.1907271Z cuda train hf_DistilBert 2025-09-07T10:09:54.6734538Z W0907 10:09:54.672000 16463 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:10:16.5494641Z pass 2025-09-07T10:10:21.1289457Z /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. 2025-09-07T10:10:21.1290900Z import pynvml # type: ignore[import] 2025-09-07T10:10:23.9207969Z 2025-09-07T10:10:30.4011954Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:10:30.4013036Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:10:30.4961802Z 2025-09-07T10:10:30.4962290Z loading model: 0it [00:06, ?it/s] 2025-09-07T10:10:30.4962675Z cuda train hf_GPT2 2025-09-07T10:11:22.1470791Z W0907 10:11:22.146000 16791 site-packages/torch/_logging/_internal.py:1199] [11/0] Profiler function will be ignored 2025-09-07T10:11:54.2703283Z pass 2025-09-07T10:11:59.8954482Z /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. 2025-09-07T10:11:59.8956142Z import pynvml # type: ignore[import] 2025-09-07T10:12:02.7383360Z 2025-09-07T10:12:20.5391199Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:12:20.5392296Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:12:20.7191571Z 2025-09-07T10:12:20.7192005Z loading model: 0it [00:17, ?it/s] 2025-09-07T10:12:20.7192372Z cuda train hf_GPT2_large 2025-09-07T10:12:20.7429310Z pass_due_to_skip 2025-09-07T10:12:22.7759819Z /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. 2025-09-07T10:12:22.7761334Z import pynvml # type: ignore[import] 2025-09-07T10:12:25.6535608Z 2025-09-07T10:12:31.0014158Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:12:31.0014547Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:12:31.0014864Z cuda train hf_Longformer 2025-09-07T10:12:34.3803624Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T10:12:34.3805765Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T10:12:34.3807505Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] or: 2025-09-07T10:12:34.3809141Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T10:12:34.3811672Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] to include these operations in the captured graph. 2025-09-07T10:12:34.3813377Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T10:12:34.3814873Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break: from user code at: 2025-09-07T10:12:34.3817233Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:12:34.3819890Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] pred = mod(**cloned_inputs) 2025-09-07T10:12:34.3822632Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1703, in forward 2025-09-07T10:12:34.3825343Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] outputs = self.longformer( 2025-09-07T10:12:34.3828046Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1600, in forward 2025-09-07T10:12:34.3830764Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] encoder_outputs = self.encoder( 2025-09-07T10:12:34.3833487Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1244, in forward 2025-09-07T10:12:34.3836759Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] is_global_attn = is_index_global_attn.flatten().any().item() 2025-09-07T10:12:34.3838474Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T10:12:34.3839726Z W0907 10:12:34.379000 17205 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T10:14:40.8196108Z W0907 10:14:40.818000 17205 site-packages/torch/_logging/_internal.py:1199] [19/0] Profiler function will be ignored 2025-09-07T10:15:28.3934399Z pass 2025-09-07T10:15:36.1087163Z /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. 2025-09-07T10:15:36.1088611Z import pynvml # type: ignore[import] 2025-09-07T10:15:38.8917081Z 2025-09-07T10:15:40.9403894Z loading model: 0it [00:00, ?it/s]Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T10:15:40.9408116Z WARNING:transformers.models.reformer.modeling_reformer:Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T10:15:41.7764098Z 2025-09-07T10:15:41.7764666Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:15:41.7765363Z cuda train hf_Reformer 2025-09-07T10:16:26.6244348Z W0907 10:16:26.623000 17713 site-packages/torch/_logging/_internal.py:1199] [35/0] Profiler function will be ignored 2025-09-07T10:16:42.7965454Z pass 2025-09-07T10:16:46.7479886Z /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. 2025-09-07T10:16:46.7482744Z import pynvml # type: ignore[import] 2025-09-07T10:16:49.4574897Z 2025-09-07T10:16:57.9570488Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:16:57.9570874Z loading model: 0it [00:08, ?it/s] 2025-09-07T10:16:57.9571201Z cuda train hf_Roberta_base 2025-09-07T10:17:57.0871244Z W0907 10:17:57.086000 18355 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:18:43.1621365Z pass 2025-09-07T10:18:48.7390571Z /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. 2025-09-07T10:18:48.7391981Z import pynvml # type: ignore[import] 2025-09-07T10:18:51.5118524Z 2025-09-07T10:18:55.1399515Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:18:55.1399924Z loading model: 0it [00:03, ?it/s] 2025-09-07T10:18:55.1400234Z cuda train hf_T5 2025-09-07T10:20:09.3153678Z pass 2025-09-07T10:20:13.4653018Z /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. 2025-09-07T10:20:13.4654416Z import pynvml # type: ignore[import] 2025-09-07T10:20:16.1691954Z 2025-09-07T10:20:22.0301108Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:20:22.0301470Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:20:22.0301791Z cuda train hf_T5_base 2025-09-07T10:20:23.3437768Z WARNING:common:fp64 golden ref were not generated for hf_T5_base. Setting accuracy check to cosine 2025-09-07T10:22:57.5448936Z W0907 10:22:57.543000 18990 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:24:02.5012531Z pass 2025-09-07T10:24:09.7435950Z /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. 2025-09-07T10:24:09.7566789Z import pynvml # type: ignore[import] 2025-09-07T10:24:12.5322570Z 2025-09-07T10:24:24.9436244Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:24:24.9436630Z loading model: 0it [00:12, ?it/s] 2025-09-07T10:24:24.9436960Z cuda train hf_T5_large 2025-09-07T10:24:24.9671922Z pass_due_to_skip 2025-09-07T10:24:26.9319438Z /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. 2025-09-07T10:24:26.9321841Z import pynvml # type: ignore[import] 2025-09-07T10:24:29.8168023Z 2025-09-07T10:24:32.4457022Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:24:32.4457480Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:24:32.4457802Z cuda train hf_Whisper 2025-09-07T10:25:05.4884549Z W0907 10:25:05.487000 19399 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:25:20.3813426Z pass 2025-09-07T10:25:24.4852824Z /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. 2025-09-07T10:25:24.4855479Z import pynvml # type: ignore[import] 2025-09-07T10:25:27.2430644Z 2025-09-07T10:25:27.7457911Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:25:27.7458494Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:25:27.7459099Z cuda train hf_distil_whisper 2025-09-07T10:25:27.7463353Z Traceback (most recent call last): 2025-09-07T10:25:27.7464311Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:25:27.7465307Z ) = runner.load_model( 2025-09-07T10:25:27.7466284Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 325, in load_model 2025-09-07T10:25:27.7467418Z benchmark = benchmark_cls( 2025-09-07T10:25:27.7468201Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T10:25:27.7469096Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T10:25:27.7470177Z File "/torchbench/torchbenchmark/models/hf_distil_whisper/__init__.py", line 13, in __init__ 2025-09-07T10:25:27.7471404Z raise NotImplementedError("Training is not implemented.") 2025-09-07T10:25:27.7472275Z NotImplementedError: Training is not implemented. 2025-09-07T10:25:27.7472782Z 2025-09-07T10:25:27.7472946Z model_fail_to_load 2025-09-07T10:25:28.6486272Z accuracy pass_rate=80.00% 2025-09-07T10:25:28.6493589Z calls_captured gmean=0.00x mean=1442.400x 2025-09-07T10:25:28.6498516Z unique_graphs gmean=0.00x mean=3.867x 2025-09-07T10:25:28.6502687Z graph_breaks gmean=0.00x mean=6.400x 2025-09-07T10:25:28.6507822Z unique_graph_breaks gmean=0.00x mean=4.467x 2025-09-07T10:25:28.6512126Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:25:28.6516458Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:25:28.6520801Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:25:28.6522217Z compilation_latency mean=103.233 seconds 2025-09-07T10:25:29.6178593Z + [[ 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* ]] 2025-09-07T10:25:29.6180164Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:25:29.6181614Z + [[ 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* ]] 2025-09-07T10:25:29.6183057Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:25:29.6184429Z + [[ 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* ]] 2025-09-07T10:25:29.6185826Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:25:29.6187183Z + [[ 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* ]] 2025-09-07T10:25:29.6188561Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T10:25:29.6189947Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T10:25:30.2331887Z /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. 2025-09-07T10:25:30.2333323Z import pynvml # type: ignore[import] 2025-09-07T10:25:34.1245511Z /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. 2025-09-07T10:25:34.1246941Z import pynvml # type: ignore[import] 2025-09-07T10:25:36.8704636Z 2025-09-07T10:25:42.6444528Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:25:42.6445127Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:25:42.6445704Z cuda train hf_Bart 2025-09-07T10:26:07.8656963Z Autotune Choices Stats: 2025-09-07T10:26:07.8658255Z {"num_choices": 20, "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=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.05939200147986412, "best_triton_pos": 0} 2025-09-07T10:26:07.8664268Z AUTOTUNE addmm(2048x3072, 2048x768, 768x3072) 2025-09-07T10:26:07.8664614Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:26:07.8664968Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:26:07.8665792Z triton_mm_88 0.0594 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 2025-09-07T10:26:07.8666979Z triton_mm_87 0.0635 ms 93.5% 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 2025-09-07T10:26:07.8668141Z triton_mm_81 0.0655 ms 90.6% 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=3, num_warps=4 2025-09-07T10:26:07.8669656Z triton_mm_84 0.0666 ms 89.2% 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=3, num_warps=4 2025-09-07T10:26:07.8670824Z triton_mm_89 0.0666 ms 89.2% 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=5, num_warps=8 2025-09-07T10:26:07.8671987Z triton_mm_83 0.0676 ms 87.9% 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 2025-09-07T10:26:07.8672728Z bias_addmm 0.0737 ms 80.6% 2025-09-07T10:26:07.8673006Z addmm 0.0737 ms 80.6% 2025-09-07T10:26:07.8673684Z triton_mm_85 0.0778 ms 76.3% 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 2025-09-07T10:26:07.8674859Z triton_mm_82 0.0788 ms 75.3% 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 2025-09-07T10:26:07.8675880Z SingleProcess AUTOTUNE benchmarking takes 0.8929 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T10:26:10.5961490Z Autotune Choices Stats: 2025-09-07T10:26:10.5963728Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_17", "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=5, num_warps=8", "best_time": 0.021503999829292297, "best_triton_pos": 0} 2025-09-07T10:26:10.5968962Z AUTOTUNE mm(2048x768, 768x768) 2025-09-07T10:26:10.5969432Z strides: [768, 1], [1, 768] 2025-09-07T10:26:10.5969851Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:10.5971023Z triton_mm_17 0.0215 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=5, num_warps=8 2025-09-07T10:26:10.5973295Z triton_mm_11 0.0225 ms 95.5% 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 2025-09-07T10:26:10.5975113Z triton_mm_16 0.0225 ms 95.5% 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 2025-09-07T10:26:10.5976811Z triton_mm_9 0.0236 ms 91.3% 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=3, num_warps=4 2025-09-07T10:26:10.5978663Z triton_mm_12 0.0236 ms 91.3% 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 2025-09-07T10:26:10.5979840Z mm 0.0246 ms 87.5% 2025-09-07T10:26:10.5980887Z triton_mm_10 0.0246 ms 87.5% 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 2025-09-07T10:26:10.5982987Z triton_mm_13 0.0256 ms 84.0% 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=4, num_warps=8 2025-09-07T10:26:10.5984954Z triton_mm_15 0.0256 ms 84.0% 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 2025-09-07T10:26:10.5986749Z triton_mm_7 0.0287 ms 75.0% 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 2025-09-07T10:26:10.5988216Z SingleProcess AUTOTUNE benchmarking takes 0.2863 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:11.0138625Z Autotune Choices Stats: 2025-09-07T10:26:11.0141822Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.05939200147986412, "best_triton_pos": 1, "best_triton_time": 0.05939200147986412, "best_triton_kernel": "triton_mm_101", "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"} 2025-09-07T10:26:11.0146670Z AUTOTUNE mm(2048x3072, 3072x768) 2025-09-07T10:26:11.0147032Z strides: [3072, 1], [1, 3072] 2025-09-07T10:26:11.0147334Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:11.0147628Z mm 0.0594 ms 100.0% 2025-09-07T10:26:11.0148342Z triton_mm_101 0.0594 ms 100.0% 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 2025-09-07T10:26:11.0149543Z triton_mm_106 0.0604 ms 98.3% 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 2025-09-07T10:26:11.0150756Z triton_mm_107 0.0645 ms 92.1% 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 2025-09-07T10:26:11.0151950Z triton_mm_102 0.0707 ms 84.1% 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=3, num_warps=4 2025-09-07T10:26:11.0153121Z triton_mm_99 0.0727 ms 81.7% 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 2025-09-07T10:26:11.0154280Z triton_mm_100 0.0727 ms 81.7% 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=4, num_warps=8 2025-09-07T10:26:11.0155462Z triton_mm_105 0.0748 ms 79.5% 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 2025-09-07T10:26:11.0156977Z triton_mm_103 0.0768 ms 77.3% 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 2025-09-07T10:26:11.0158163Z triton_mm_97 0.0819 ms 72.5% 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=3, num_warps=8 2025-09-07T10:26:11.0159176Z SingleProcess AUTOTUNE benchmarking takes 0.4161 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:11.8527459Z Autotune Choices Stats: 2025-09-07T10:26:11.8528939Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.6410239934921265, "best_triton_pos": 1, "best_triton_time": 0.822272002696991, "best_triton_kernel": "triton_mm_1744", "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"} 2025-09-07T10:26:11.8535799Z AUTOTUNE mm(2048x768, 768x50272) 2025-09-07T10:26:11.8536084Z strides: [768, 1], [50304, 1] 2025-09-07T10:26:11.8536384Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:11.8536702Z mm 0.6410 ms 100.0% 2025-09-07T10:26:11.8537494Z triton_mm_1744 0.8223 ms 78.0% 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 2025-09-07T10:26:11.8538690Z triton_mm_1737 0.8622 ms 74.3% 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=3, num_warps=4 2025-09-07T10:26:11.8539889Z triton_mm_1743 0.8837 ms 72.5% 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 2025-09-07T10:26:11.8541092Z triton_mm_1739 0.9441 ms 67.9% 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 2025-09-07T10:26:11.8542605Z triton_mm_1740 0.9626 ms 66.6% 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 2025-09-07T10:26:11.8543802Z triton_mm_1745 1.0598 ms 60.5% 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 2025-09-07T10:26:11.8544992Z triton_mm_1738 1.1264 ms 56.9% 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=4, num_warps=8 2025-09-07T10:26:11.8546180Z triton_mm_1742 1.1633 ms 55.1% 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=2, num_warps=8 2025-09-07T10:26:11.8547358Z triton_mm_1741 1.1694 ms 54.8% 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 2025-09-07T10:26:11.8548393Z SingleProcess AUTOTUNE benchmarking takes 0.8039 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:30.4441558Z Autotune Choices Stats: 2025-09-07T10:26:30.4443262Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.5703679919242859, "best_triton_pos": 1, "best_triton_time": 1.1335680484771729, "best_triton_kernel": "triton_mm_1762", "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"} 2025-09-07T10:26:30.4452052Z AUTOTUNE mm(50265x2048, 2048x768) 2025-09-07T10:26:30.4452362Z strides: [1, 50304], [768, 1] 2025-09-07T10:26:30.4452660Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:30.4452970Z mm 0.5704 ms 100.0% 2025-09-07T10:26:30.4453727Z triton_mm_1762 1.1336 ms 50.3% 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 2025-09-07T10:26:30.4455305Z triton_mm_1760 1.2913 ms 44.2% 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=2, num_warps=8 2025-09-07T10:26:30.4456496Z triton_mm_1761 1.2923 ms 44.1% 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 2025-09-07T10:26:30.4457778Z triton_mm_1755 1.2943 ms 44.1% 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 2025-09-07T10:26:30.4458968Z triton_mm_1757 1.4070 ms 40.5% 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 2025-09-07T10:26:30.4460171Z triton_mm_1763 1.5995 ms 35.7% 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 2025-09-07T10:26:30.4461370Z triton_mm_1758 1.6824 ms 33.9% 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=3, num_warps=4 2025-09-07T10:26:30.4462557Z triton_mm_1752 1.6906 ms 33.7% 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=2, num_warps=4 2025-09-07T10:26:30.4463735Z triton_mm_1756 1.7920 ms 31.8% 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 2025-09-07T10:26:30.4464741Z SingleProcess AUTOTUNE benchmarking takes 0.8274 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:26:31.1424618Z Autotune Choices Stats: 2025-09-07T10:26:31.1425870Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1798", "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": 0.055296000093221664, "best_triton_pos": 0} 2025-09-07T10:26:31.1433777Z AUTOTUNE mm(2048x768, 768x3072) 2025-09-07T10:26:31.1434107Z strides: [768, 1], [3072, 1] 2025-09-07T10:26:31.1434403Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:31.1435171Z triton_mm_1798 0.0553 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 2025-09-07T10:26:31.1436372Z triton_mm_1793 0.0584 ms 94.7% 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 2025-09-07T10:26:31.1437557Z triton_mm_1791 0.0594 ms 93.1% 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 2025-09-07T10:26:31.1438761Z triton_mm_1794 0.0604 ms 91.5% 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=3, num_warps=4 2025-09-07T10:26:31.1439947Z triton_mm_1797 0.0604 ms 91.5% 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 2025-09-07T10:26:31.1440691Z mm 0.0645 ms 85.7% 2025-09-07T10:26:31.1441385Z triton_mm_1799 0.0645 ms 85.7% 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 2025-09-07T10:26:31.1442560Z triton_mm_1792 0.0696 ms 79.4% 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=4, num_warps=8 2025-09-07T10:26:31.1443996Z triton_mm_1796 0.0737 ms 75.0% 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=2, num_warps=8 2025-09-07T10:26:31.1445529Z triton_mm_1795 0.0758 ms 73.0% 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=4, num_warps=8 2025-09-07T10:26:31.1446573Z SingleProcess AUTOTUNE benchmarking takes 0.4001 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:26:32.0997758Z Autotune Choices Stats: 2025-09-07T10:26:32.0999255Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.055296000093221664, "best_triton_pos": 1, "best_triton_time": 0.05939200147986412, "best_triton_kernel": "triton_mm_1809", "best_triton_kernel_desc": "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"} 2025-09-07T10:26:32.1007498Z AUTOTUNE mm(768x2048, 2048x3072) 2025-09-07T10:26:32.1007799Z strides: [1, 768], [3072, 1] 2025-09-07T10:26:32.1008171Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:32.1008489Z mm 0.0553 ms 100.0% 2025-09-07T10:26:32.1009183Z triton_mm_1809 0.0594 ms 93.1% 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 2025-09-07T10:26:32.1010376Z triton_mm_1811 0.0604 ms 91.5% 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 2025-09-07T10:26:32.1011556Z triton_mm_1812 0.0645 ms 85.7% 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 2025-09-07T10:26:32.1012743Z triton_mm_1813 0.0717 ms 77.1% 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 2025-09-07T10:26:32.1014286Z triton_mm_1816 0.0717 ms 77.1% 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=3, num_warps=4 2025-09-07T10:26:32.1015475Z triton_mm_1815 0.0748 ms 74.0% 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 2025-09-07T10:26:32.1016648Z triton_mm_1810 0.0758 ms 73.0% 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 2025-09-07T10:26:32.1017900Z triton_mm_1807 0.0799 ms 69.2% 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 2025-09-07T10:26:32.1019085Z triton_mm_1808 0.0829 ms 66.7% 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 2025-09-07T10:26:32.1020121Z SingleProcess AUTOTUNE benchmarking takes 0.3975 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:32.7198559Z Autotune Choices Stats: 2025-09-07T10:26:32.7201524Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.055296000093221664, "best_triton_pos": 1, "best_triton_time": 0.060416001826524734, "best_triton_kernel": "triton_mm_1845", "best_triton_kernel_desc": "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"} 2025-09-07T10:26:32.7209057Z AUTOTUNE mm(3072x2048, 2048x768) 2025-09-07T10:26:32.7209656Z strides: [1, 3072], [768, 1] 2025-09-07T10:26:32.7210246Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:32.7210859Z mm 0.0553 ms 100.0% 2025-09-07T10:26:32.7212292Z triton_mm_1845 0.0604 ms 91.5% 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 2025-09-07T10:26:32.7215138Z triton_mm_1847 0.0625 ms 88.5% 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 2025-09-07T10:26:32.7217612Z triton_mm_1848 0.0655 ms 84.4% 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 2025-09-07T10:26:32.7220021Z triton_mm_1852 0.0696 ms 79.4% 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 2025-09-07T10:26:32.7222408Z triton_mm_1849 0.0727 ms 76.1% 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 2025-09-07T10:26:32.7224845Z triton_mm_1851 0.0727 ms 76.1% 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 2025-09-07T10:26:32.7227250Z triton_mm_1846 0.0758 ms 73.0% 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 2025-09-07T10:26:32.7229619Z triton_mm_1843 0.0799 ms 69.2% 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 2025-09-07T10:26:32.7231983Z triton_mm_1844 0.0819 ms 67.5% 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 2025-09-07T10:26:32.7234024Z SingleProcess AUTOTUNE benchmarking takes 0.3983 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:33.3067508Z Autotune Choices Stats: 2025-09-07T10:26:33.3069401Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.030719999223947525, "best_triton_kernel": "triton_mm_1883", "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"} 2025-09-07T10:26:33.3077224Z AUTOTUNE mm(768x2048, 2048x768) 2025-09-07T10:26:33.3077517Z strides: [1, 768], [768, 1] 2025-09-07T10:26:33.3077809Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:33.3078112Z mm 0.0225 ms 100.0% 2025-09-07T10:26:33.3078808Z triton_mm_1883 0.0307 ms 73.3% 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 2025-09-07T10:26:33.3079994Z triton_mm_1880 0.0317 ms 71.0% 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 2025-09-07T10:26:33.3081183Z triton_mm_1879 0.0328 ms 68.8% 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 2025-09-07T10:26:33.3082375Z triton_mm_1882 0.0338 ms 66.7% 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=4, num_warps=8 2025-09-07T10:26:33.3083785Z triton_mm_1885 0.0338 ms 66.7% 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 2025-09-07T10:26:33.3084953Z triton_mm_1881 0.0399 ms 56.4% 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 2025-09-07T10:26:33.3086135Z triton_mm_1884 0.0399 ms 56.4% 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 2025-09-07T10:26:33.3087515Z triton_mm_1888 0.0410 ms 55.0% 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 2025-09-07T10:26:33.3088728Z triton_mm_1873 0.0420 ms 53.7% 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 2025-09-07T10:26:33.3089757Z SingleProcess AUTOTUNE benchmarking takes 0.3082 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:35.7362182Z Autotune Choices Stats: 2025-09-07T10:26:35.7363956Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.5754879713058472, "best_triton_pos": 1, "best_triton_time": 0.9205759763717651, "best_triton_kernel": "triton_mm_1780", "best_triton_kernel_desc": "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"} 2025-09-07T10:26:35.7373471Z AUTOTUNE mm(2048x50272, 50272x768) 2025-09-07T10:26:35.7373785Z strides: [50304, 1], [768, 1] 2025-09-07T10:26:35.7374097Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:35.7374390Z mm 0.5755 ms 100.0% 2025-09-07T10:26:35.7375105Z triton_mm_1780 0.9206 ms 62.5% 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 2025-09-07T10:26:35.7376320Z triton_mm_1781 0.9329 ms 61.7% 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 2025-09-07T10:26:35.7377608Z triton_mm_1779 0.9656 ms 59.6% 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 2025-09-07T10:26:35.7378816Z triton_mm_1775 0.9820 ms 58.6% 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 2025-09-07T10:26:35.7380355Z triton_mm_1773 1.0363 ms 55.5% 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 2025-09-07T10:26:35.7381527Z triton_mm_1776 1.2739 ms 45.2% 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=3, num_warps=4 2025-09-07T10:26:35.7382714Z triton_mm_1774 1.2923 ms 44.5% 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 2025-09-07T10:26:35.7383897Z triton_mm_1777 1.2954 ms 44.4% 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 2025-09-07T10:26:35.7385089Z triton_mm_1771 1.3353 ms 43.1% 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 2025-09-07T10:26:35.7386121Z SingleProcess AUTOTUNE benchmarking takes 0.7998 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:36.1437822Z Autotune Choices Stats: 2025-09-07T10:26:36.1439050Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1835", "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=5, num_warps=8", "best_time": 0.05939200147986412, "best_triton_pos": 0} 2025-09-07T10:26:36.1449510Z AUTOTUNE mm(2048x3072, 3072x768) 2025-09-07T10:26:36.1449832Z strides: [3072, 1], [768, 1] 2025-09-07T10:26:36.1450141Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:36.1450897Z triton_mm_1835 0.0594 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=5, num_warps=8 2025-09-07T10:26:36.1452506Z triton_mm_1829 0.0604 ms 98.3% 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 2025-09-07T10:26:36.1453259Z mm 0.0625 ms 95.1% 2025-09-07T10:26:36.1453951Z triton_mm_1834 0.0625 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=3, num_warps=4 2025-09-07T10:26:36.1455148Z triton_mm_1827 0.0686 ms 86.6% 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=3, num_warps=4 2025-09-07T10:26:36.1456333Z triton_mm_1833 0.0717 ms 82.9% 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 2025-09-07T10:26:36.1457599Z triton_mm_1830 0.0737 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 2025-09-07T10:26:36.1458780Z triton_mm_1831 0.0748 ms 79.5% 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 2025-09-07T10:26:36.1459971Z triton_mm_1828 0.0768 ms 77.3% 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 2025-09-07T10:26:36.1461150Z triton_mm_1825 0.0819 ms 72.5% 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=3, num_warps=8 2025-09-07T10:26:36.1462169Z SingleProcess AUTOTUNE benchmarking takes 0.4062 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:36.4212692Z Autotune Choices Stats: 2025-09-07T10:26:36.4214263Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1870", "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": 0.021503999829292297, "best_triton_pos": 0} 2025-09-07T10:26:36.4225042Z AUTOTUNE mm(2048x768, 768x768) 2025-09-07T10:26:36.4225340Z strides: [768, 1], [768, 1] 2025-09-07T10:26:36.4225626Z dtypes: torch.float16, torch.float16 2025-09-07T10:26:36.4226399Z triton_mm_1870 0.0215 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 2025-09-07T10:26:36.4227605Z triton_mm_1871 0.0215 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=5, num_warps=8 2025-09-07T10:26:36.4228797Z triton_mm_1865 0.0225 ms 95.5% 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 2025-09-07T10:26:36.4229980Z triton_mm_1866 0.0236 ms 91.3% 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 2025-09-07T10:26:36.4231162Z triton_mm_1863 0.0246 ms 87.5% 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 2025-09-07T10:26:36.4232341Z triton_mm_1864 0.0246 ms 87.5% 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 2025-09-07T10:26:36.4233526Z triton_mm_1869 0.0246 ms 87.5% 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 2025-09-07T10:26:36.4234272Z mm 0.0256 ms 84.0% 2025-09-07T10:26:36.4234959Z triton_mm_1867 0.0256 ms 84.0% 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=4, num_warps=8 2025-09-07T10:26:36.4236294Z triton_mm_1861 0.0287 ms 75.0% 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 2025-09-07T10:26:36.4237315Z SingleProcess AUTOTUNE benchmarking takes 0.2769 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:26:43.0015482Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:26:43.0016733Z pred = mod(**cloned_inputs) 2025-09-07T10:26:43.0017406Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1471, in forward 2025-09-07T10:26:43.0018205Z outputs = self.model( 2025-09-07T10:26:43.0018869Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1288, in forward 2025-09-07T10:26:43.0019590Z decoder_outputs = self.decoder( 2025-09-07T10:26:43.0020271Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 1084, in forward 2025-09-07T10:26:43.0021159Z positions = self.embed_positions(input, past_key_values_length, position_ids=cache_position) 2025-09-07T10:26:43.0022060Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bart/modeling_bart.py", line 101, in forward 2025-09-07T10:26:43.0022795Z return super().forward(position_ids + self.offset) 2025-09-07T10:26:43.0023055Z 2025-09-07T10:26:43.0023071Z 2025-09-07T10:26:44.8752946Z W0907 10:26:44.874000 19961 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:27:23.9908415Z pass 2025-09-07T10:27:29.7638229Z /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. 2025-09-07T10:27:29.7641642Z import pynvml # type: ignore[import] 2025-09-07T10:27:32.5571972Z 2025-09-07T10:27:36.9377281Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:27:36.9377711Z loading model: 0it [00:04, ?it/s] 2025-09-07T10:27:36.9378033Z cuda train hf_Bert 2025-09-07T10:27:59.5595490Z Autotune Choices Stats: 2025-09-07T10:27:59.5597044Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_mm_17", "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"} 2025-09-07T10:27:59.5607198Z AUTOTUNE addmm(2048x768, 2048x768, 768x768) 2025-09-07T10:27:59.5607555Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:27:59.5607904Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:27:59.5608260Z bias_addmm 0.0215 ms 100.0% 2025-09-07T10:27:59.5608991Z triton_mm_17 0.0225 ms 95.5% 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 2025-09-07T10:27:59.5610171Z triton_mm_11 0.0236 ms 91.3% 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 2025-09-07T10:27:59.5611342Z triton_mm_16 0.0236 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=3, num_warps=4 2025-09-07T10:27:59.5612522Z triton_mm_9 0.0246 ms 87.5% 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 2025-09-07T10:27:59.5614026Z triton_mm_10 0.0246 ms 87.5% 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 2025-09-07T10:27:59.5615312Z triton_mm_12 0.0246 ms 87.5% 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=3, num_warps=4 2025-09-07T10:27:59.5616472Z triton_mm_13 0.0256 ms 84.0% 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=4, num_warps=8 2025-09-07T10:27:59.5617729Z triton_mm_15 0.0256 ms 84.0% 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 2025-09-07T10:27:59.5618903Z triton_mm_7 0.0287 ms 75.0% 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 2025-09-07T10:27:59.5619915Z SingleProcess AUTOTUNE benchmarking takes 0.3299 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:28:00.3915613Z Autotune Choices Stats: 2025-09-07T10:28:00.3916810Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_1329", "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": 0.5754879713058472, "best_triton_pos": 0} 2025-09-07T10:28:00.3929238Z AUTOTUNE addmm(2048x30522, 2048x768, 768x30522) 2025-09-07T10:28:00.3929622Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:28:00.3929970Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:28:00.3931248Z triton_mm_1329 0.5755 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 2025-09-07T10:28:00.3932469Z triton_mm_1330 0.5908 ms 97.4% 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 2025-09-07T10:28:00.3933673Z triton_mm_1323 0.6431 ms 89.5% 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 2025-09-07T10:28:00.3934428Z bias_addmm 0.6646 ms 86.6% 2025-09-07T10:28:00.3935148Z triton_mm_1326 0.6963 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=3, num_warps=4 2025-09-07T10:28:00.3936323Z triton_mm_1325 0.7137 ms 80.6% 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 2025-09-07T10:28:00.3937511Z triton_mm_1331 0.7342 ms 78.4% 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 2025-09-07T10:28:00.3938795Z triton_mm_1327 0.8335 ms 69.0% 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=4, num_warps=8 2025-09-07T10:28:00.3939979Z triton_mm_1324 0.8540 ms 67.4% 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=4, num_warps=8 2025-09-07T10:28:00.3941156Z triton_mm_1320 0.8765 ms 65.7% 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=2, num_warps=4 2025-09-07T10:28:00.3942178Z SingleProcess AUTOTUNE benchmarking takes 0.7767 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:28:14.1893963Z Autotune Choices Stats: 2025-09-07T10:28:14.1895895Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.36454400420188904, "best_triton_pos": 1, "best_triton_time": 0.5550079941749573, "best_triton_kernel": "triton_mm_1359", "best_triton_kernel_desc": "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"} 2025-09-07T10:28:14.1907694Z AUTOTUNE mm(30522x2048, 2048x768) 2025-09-07T10:28:14.1908008Z strides: [1, 30528], [768, 1] 2025-09-07T10:28:14.1908308Z dtypes: torch.float16, torch.float16 2025-09-07T10:28:14.1908620Z mm 0.3645 ms 100.0% 2025-09-07T10:28:14.1909325Z triton_mm_1359 0.5550 ms 65.7% 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 2025-09-07T10:28:14.1910508Z triton_mm_1365 0.5919 ms 61.6% 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 2025-09-07T10:28:14.1911730Z triton_mm_1366 0.6205 ms 58.7% 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 2025-09-07T10:28:14.1912921Z triton_mm_1361 0.6226 ms 58.6% 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 2025-09-07T10:28:14.1914106Z triton_mm_1364 0.7404 ms 49.2% 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=2, num_warps=8 2025-09-07T10:28:14.1915300Z triton_mm_1367 0.7721 ms 47.2% 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=5, num_warps=8 2025-09-07T10:28:14.1916690Z triton_mm_1362 0.7741 ms 47.1% 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=3, num_warps=4 2025-09-07T10:28:14.1917883Z triton_mm_1356 0.8366 ms 43.6% 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 2025-09-07T10:28:14.1919054Z triton_mm_1360 0.8448 ms 43.2% 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 2025-09-07T10:28:14.1920080Z SingleProcess AUTOTUNE benchmarking takes 0.7304 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:28:16.6700621Z Autotune Choices Stats: 2025-09-07T10:28:16.6703452Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.3665919899940491, "best_triton_pos": 1, "best_triton_time": 0.5550079941749573, "best_triton_kernel": "triton_mm_1349", "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"} 2025-09-07T10:28:16.6714292Z AUTOTUNE mm(2048x30528, 30528x768) 2025-09-07T10:28:16.6714871Z strides: [30528, 1], [768, 1] 2025-09-07T10:28:16.6715398Z dtypes: torch.float16, torch.float16 2025-09-07T10:28:16.6715952Z mm 0.3666 ms 100.0% 2025-09-07T10:28:16.6717296Z triton_mm_1349 0.5550 ms 66.1% 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 2025-09-07T10:28:16.6719629Z triton_mm_1348 0.5847 ms 62.7% 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 2025-09-07T10:28:16.6721931Z triton_mm_1343 0.5970 ms 61.4% 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 2025-09-07T10:28:16.6724629Z triton_mm_1347 0.5990 ms 61.2% 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 2025-09-07T10:28:16.6727441Z triton_mm_1341 0.6246 ms 58.7% 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 2025-09-07T10:28:16.6729775Z triton_mm_1344 0.7250 ms 50.6% 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 2025-09-07T10:28:16.6732078Z triton_mm_1342 0.7782 ms 47.1% 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=4, num_warps=8 2025-09-07T10:28:16.6734361Z triton_mm_1345 0.7803 ms 47.0% 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=4, num_warps=8 2025-09-07T10:28:16.6736671Z triton_mm_1339 0.7895 ms 46.4% 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 2025-09-07T10:28:16.6738706Z SingleProcess AUTOTUNE benchmarking takes 0.7250 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:28:22.2635301Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:28:22.2636558Z pred = mod(**cloned_inputs) 2025-09-07T10:28:22.2637280Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 1308, in forward 2025-09-07T10:28:22.2637969Z outputs = self.bert( 2025-09-07T10:28:22.2638621Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 964, in forward 2025-09-07T10:28:22.2639705Z embedding_output = self.embeddings( 2025-09-07T10:28:22.2640414Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 186, in forward 2025-09-07T10:28:22.2641197Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T10:28:22.2641511Z 2025-09-07T10:28:22.2641516Z 2025-09-07T10:28:23.2260785Z W0907 10:28:23.225000 23262 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:28:52.7466908Z pass 2025-09-07T10:28:58.2943197Z /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. 2025-09-07T10:28:58.2944664Z import pynvml # type: ignore[import] 2025-09-07T10:29:01.0878397Z 2025-09-07T10:29:07.9000195Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:29:07.9000566Z loading model: 0it [00:06, ?it/s] 2025-09-07T10:29:45.8219392Z cuda train hf_Bert_large 2025-09-07T10:29:45.8219796Z Autotune Choices Stats: 2025-09-07T10:29:45.8221248Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.06656000018119812, "best_triton_pos": 1, "best_triton_time": 0.07475200295448303, "best_triton_kernel": "triton_mm_88", "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"} 2025-09-07T10:29:45.8234138Z AUTOTUNE addmm(2048x3072, 2048x1024, 1024x3072) 2025-09-07T10:29:45.8234572Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:29:45.8234912Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:29:45.8235296Z bias_addmm 0.0666 ms 100.0% 2025-09-07T10:29:45.8236029Z triton_mm_88 0.0748 ms 89.0% 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 2025-09-07T10:29:45.8237611Z triton_mm_87 0.0788 ms 84.4% 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 2025-09-07T10:29:45.8238803Z triton_mm_83 0.0809 ms 82.3% 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 2025-09-07T10:29:45.8239972Z triton_mm_84 0.0809 ms 82.3% 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 2025-09-07T10:29:45.8240703Z addmm 0.0840 ms 79.3% 2025-09-07T10:29:45.8241413Z triton_mm_89 0.0860 ms 77.4% 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 2025-09-07T10:29:45.8242591Z triton_mm_81 0.0901 ms 73.9% 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 2025-09-07T10:29:45.8243954Z triton_mm_85 0.0993 ms 67.0% 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=4, num_warps=8 2025-09-07T10:29:45.8245127Z triton_mm_82 0.1014 ms 65.7% 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=4, num_warps=8 2025-09-07T10:29:45.8246148Z SingleProcess AUTOTUNE benchmarking takes 0.5082 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T10:29:48.9481234Z Autotune Choices Stats: 2025-09-07T10:29:48.9482788Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.03174399957060814, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "best_triton_kernel": "triton_mm_11", "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"} 2025-09-07T10:29:48.9496791Z AUTOTUNE addmm(2048x1024, 2048x1024, 1024x1024) 2025-09-07T10:29:48.9497135Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:29:48.9497488Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:29:48.9497943Z bias_addmm 0.0317 ms 100.0% 2025-09-07T10:29:48.9498671Z triton_mm_11 0.0348 ms 91.2% 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 2025-09-07T10:29:48.9499850Z triton_mm_12 0.0369 ms 86.1% 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=3, num_warps=4 2025-09-07T10:29:48.9501013Z triton_mm_9 0.0379 ms 83.8% 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=3, num_warps=4 2025-09-07T10:29:48.9501754Z addmm 0.0399 ms 79.5% 2025-09-07T10:29:48.9502435Z triton_mm_6 0.0399 ms 79.5% 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=2, num_warps=4 2025-09-07T10:29:48.9503582Z triton_mm_7 0.0410 ms 77.5% 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=3, num_warps=8 2025-09-07T10:29:48.9504734Z triton_mm_10 0.0410 ms 77.5% 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 2025-09-07T10:29:48.9505903Z triton_mm_16 0.0410 ms 77.5% 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 2025-09-07T10:29:48.9507294Z triton_mm_15 0.0430 ms 73.8% 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 2025-09-07T10:29:48.9508306Z SingleProcess AUTOTUNE benchmarking takes 0.3560 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:29:49.2722027Z Autotune Choices Stats: 2025-09-07T10:29:49.2723683Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.02969600073993206, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "best_triton_kernel": "triton_mm_66", "best_triton_kernel_desc": "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"} 2025-09-07T10:29:49.2744772Z AUTOTUNE mm(2048x1024, 1024x1024) 2025-09-07T10:29:49.2745096Z strides: [1024, 1], [1, 1024] 2025-09-07T10:29:49.2745399Z dtypes: torch.float16, torch.float16 2025-09-07T10:29:49.2745701Z mm 0.0297 ms 100.0% 2025-09-07T10:29:49.2746409Z triton_mm_66 0.0348 ms 85.3% 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 2025-09-07T10:29:49.2755139Z triton_mm_65 0.0358 ms 82.9% 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 2025-09-07T10:29:49.2756445Z triton_mm_63 0.0369 ms 80.6% 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=3, num_warps=4 2025-09-07T10:29:49.2757628Z triton_mm_70 0.0389 ms 76.3% 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 2025-09-07T10:29:49.2758812Z triton_mm_60 0.0399 ms 74.4% 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=2, num_warps=4 2025-09-07T10:29:49.2760254Z triton_mm_61 0.0399 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 2025-09-07T10:29:49.2761419Z triton_mm_64 0.0399 ms 74.4% 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=4, num_warps=8 2025-09-07T10:29:49.2762594Z triton_mm_67 0.0399 ms 74.4% 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 2025-09-07T10:29:49.2763933Z triton_mm_69 0.0410 ms 72.5% 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 2025-09-07T10:29:49.2764959Z SingleProcess AUTOTUNE benchmarking takes 0.3211 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:29:49.7453435Z Autotune Choices Stats: 2025-09-07T10:29:49.7456169Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.07577600330114365, "best_triton_pos": 1, "best_triton_time": 0.08908800035715103, "best_triton_kernel": "triton_mm_101", "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"} 2025-09-07T10:29:49.7469407Z AUTOTUNE mm(2048x3072, 3072x1024) 2025-09-07T10:29:49.7469949Z strides: [3072, 1], [1, 3072] 2025-09-07T10:29:49.7470477Z dtypes: torch.float16, torch.float16 2025-09-07T10:29:49.7471011Z mm 0.0758 ms 100.0% 2025-09-07T10:29:49.7472271Z triton_mm_101 0.0891 ms 85.1% 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 2025-09-07T10:29:49.7474532Z triton_mm_102 0.0911 ms 83.1% 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=3, num_warps=4 2025-09-07T10:29:49.7477188Z triton_mm_106 0.0952 ms 79.6% 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=3, num_warps=4 2025-09-07T10:29:49.7479419Z triton_mm_99 0.0973 ms 77.9% 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 2025-09-07T10:29:49.7481612Z triton_mm_97 0.1055 ms 71.8% 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 2025-09-07T10:29:49.7484095Z triton_mm_105 0.1055 ms 71.8% 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 2025-09-07T10:29:49.7486346Z triton_mm_100 0.1065 ms 71.2% 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 2025-09-07T10:29:49.7488536Z triton_mm_96 0.1075 ms 70.5% 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=2, num_warps=4 2025-09-07T10:29:49.7490722Z triton_mm_103 0.1075 ms 70.5% 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 2025-09-07T10:29:49.7492515Z SingleProcess AUTOTUNE benchmarking takes 0.4704 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:29:50.7417382Z Autotune Choices Stats: 2025-09-07T10:29:50.7418660Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_2625", "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": 0.7229440212249756, "best_triton_pos": 0} 2025-09-07T10:29:50.7433712Z AUTOTUNE addmm(2048x30522, 2048x1024, 1024x30522) 2025-09-07T10:29:50.7434112Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:29:50.7434469Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:29:50.7435276Z triton_mm_2625 0.7229 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 2025-09-07T10:29:50.7436503Z triton_mm_2626 0.7281 ms 99.3% 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 2025-09-07T10:29:50.7437267Z bias_addmm 0.8161 ms 88.6% 2025-09-07T10:29:50.7437990Z triton_mm_2619 0.8530 ms 84.8% 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=3, num_warps=4 2025-09-07T10:29:50.7439179Z triton_mm_2622 0.8704 ms 83.1% 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=3, num_warps=4 2025-09-07T10:29:50.7440368Z triton_mm_2621 0.8796 ms 82.2% 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 2025-09-07T10:29:50.7441540Z triton_mm_2627 0.9093 ms 79.5% 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 2025-09-07T10:29:50.7442726Z triton_mm_2620 1.0465 ms 69.1% 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=4, num_warps=8 2025-09-07T10:29:50.7444129Z triton_mm_2623 1.0865 ms 66.5% 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 2025-09-07T10:29:50.7445539Z triton_mm_2617 1.1295 ms 64.0% 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 2025-09-07T10:29:50.7446572Z SingleProcess AUTOTUNE benchmarking takes 0.8080 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:30:15.4762606Z Autotune Choices Stats: 2025-09-07T10:30:15.4764257Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.4638719856739044, "best_triton_pos": 1, "best_triton_time": 0.7055360078811646, "best_triton_kernel": "triton_mm_2655", "best_triton_kernel_desc": "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"} 2025-09-07T10:30:15.4791461Z AUTOTUNE mm(30522x2048, 2048x1024) 2025-09-07T10:30:15.4791860Z strides: [1, 30528], [1024, 1] 2025-09-07T10:30:15.4792202Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:15.4792507Z mm 0.4639 ms 100.0% 2025-09-07T10:30:15.4793211Z triton_mm_2655 0.7055 ms 65.7% 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 2025-09-07T10:30:15.4794424Z triton_mm_2661 0.7629 ms 60.8% 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 2025-09-07T10:30:15.4795625Z triton_mm_2662 0.8223 ms 56.4% 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 2025-09-07T10:30:15.4796809Z triton_mm_2657 0.8458 ms 54.8% 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 2025-09-07T10:30:15.4798003Z triton_mm_2660 0.9452 ms 49.1% 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=2, num_warps=8 2025-09-07T10:30:15.4799585Z triton_mm_2658 1.0168 ms 45.6% 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 2025-09-07T10:30:15.4800783Z triton_mm_2663 1.0250 ms 45.3% 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 2025-09-07T10:30:15.4801955Z triton_mm_2652 1.0813 ms 42.9% 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=2, num_warps=4 2025-09-07T10:30:15.4803243Z triton_mm_2656 1.1172 ms 41.5% 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 2025-09-07T10:30:15.4804280Z SingleProcess AUTOTUNE benchmarking takes 0.7861 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:30:16.3269057Z Autotune Choices Stats: 2025-09-07T10:30:16.3270319Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_2716", "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": 0.07577600330114365, "best_triton_pos": 0} 2025-09-07T10:30:16.3286876Z AUTOTUNE mm(2048x1024, 1024x3072) 2025-09-07T10:30:16.3287223Z strides: [1024, 1], [3072, 1] 2025-09-07T10:30:16.3287534Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:16.3288318Z triton_mm_2716 0.0758 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 2025-09-07T10:30:16.3289090Z mm 0.0788 ms 96.1% 2025-09-07T10:30:16.3289788Z triton_mm_2715 0.0788 ms 96.1% 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 2025-09-07T10:30:16.3291405Z triton_mm_2711 0.0799 ms 94.9% 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 2025-09-07T10:30:16.3292598Z triton_mm_2709 0.0809 ms 93.7% 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 2025-09-07T10:30:16.3293785Z triton_mm_2712 0.0850 ms 89.2% 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=3, num_warps=4 2025-09-07T10:30:16.3294981Z triton_mm_2717 0.0860 ms 88.1% 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 2025-09-07T10:30:16.3296174Z triton_mm_2710 0.0932 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 2025-09-07T10:30:16.3297359Z triton_mm_2714 0.0973 ms 77.9% 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=2, num_warps=8 2025-09-07T10:30:16.3298633Z triton_mm_2713 0.1004 ms 75.5% 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 2025-09-07T10:30:16.3299656Z SingleProcess AUTOTUNE benchmarking takes 0.4513 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:30:17.3396967Z Autotune Choices Stats: 2025-09-07T10:30:17.3398474Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.060416001826524734, "best_triton_pos": 1, "best_triton_time": 0.07065600156784058, "best_triton_kernel": "triton_mm_2734", "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"} 2025-09-07T10:30:17.3416373Z AUTOTUNE mm(1024x2048, 2048x3072) 2025-09-07T10:30:17.3416747Z strides: [1, 1024], [3072, 1] 2025-09-07T10:30:17.3417050Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:17.3417348Z mm 0.0604 ms 100.0% 2025-09-07T10:30:17.3418151Z triton_mm_2734 0.0707 ms 85.5% 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 2025-09-07T10:30:17.3419371Z triton_mm_2733 0.0748 ms 80.8% 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 2025-09-07T10:30:17.3420574Z triton_mm_2727 0.0768 ms 78.7% 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 2025-09-07T10:30:17.3421768Z triton_mm_2730 0.0829 ms 72.8% 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 2025-09-07T10:30:17.3422962Z triton_mm_2729 0.0840 ms 72.0% 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 2025-09-07T10:30:17.3424149Z triton_mm_2735 0.0860 ms 70.2% 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=5, num_warps=8 2025-09-07T10:30:17.3425325Z triton_mm_2731 0.0963 ms 62.8% 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 2025-09-07T10:30:17.3426505Z triton_mm_2728 0.1004 ms 60.2% 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 2025-09-07T10:30:17.3428013Z triton_mm_2732 0.1004 ms 60.2% 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=2, num_warps=8 2025-09-07T10:30:17.3429051Z SingleProcess AUTOTUNE benchmarking takes 0.4521 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:30:18.0146539Z Autotune Choices Stats: 2025-09-07T10:30:18.0148046Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.060416001826524734, "best_triton_pos": 1, "best_triton_time": 0.06963200122117996, "best_triton_kernel": "triton_mm_2770", "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"} 2025-09-07T10:30:18.0167498Z AUTOTUNE mm(3072x2048, 2048x1024) 2025-09-07T10:30:18.0167828Z strides: [1, 3072], [1024, 1] 2025-09-07T10:30:18.0168158Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:18.0168465Z mm 0.0604 ms 100.0% 2025-09-07T10:30:18.0169186Z triton_mm_2770 0.0696 ms 86.8% 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 2025-09-07T10:30:18.0170398Z triton_mm_2769 0.0727 ms 83.1% 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 2025-09-07T10:30:18.0171595Z triton_mm_2763 0.0748 ms 80.8% 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=3, num_warps=4 2025-09-07T10:30:18.0172781Z triton_mm_2766 0.0788 ms 76.6% 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 2025-09-07T10:30:18.0173973Z triton_mm_2765 0.0799 ms 75.6% 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 2025-09-07T10:30:18.0175599Z triton_mm_2771 0.0840 ms 72.0% 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 2025-09-07T10:30:18.0176798Z triton_mm_2768 0.0911 ms 66.3% 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=2, num_warps=8 2025-09-07T10:30:18.0178073Z triton_mm_2767 0.0922 ms 65.6% 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 2025-09-07T10:30:18.0179452Z triton_mm_2764 0.0983 ms 61.5% 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 2025-09-07T10:30:18.0180487Z SingleProcess AUTOTUNE benchmarking takes 0.4507 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:30:18.9383640Z Autotune Choices Stats: 2025-09-07T10:30:18.9385176Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03276799991726875, "best_triton_pos": 1, "best_triton_time": 0.04198399931192398, "best_triton_kernel": "triton_mm_2693", "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"} 2025-09-07T10:30:18.9404024Z AUTOTUNE mm(1024x2048, 2048x1024) 2025-09-07T10:30:18.9404336Z strides: [1, 1024], [1024, 1] 2025-09-07T10:30:18.9404641Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:18.9404948Z mm 0.0328 ms 100.0% 2025-09-07T10:30:18.9405655Z triton_mm_2693 0.0420 ms 78.0% 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 2025-09-07T10:30:18.9406865Z triton_mm_2698 0.0420 ms 78.0% 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 2025-09-07T10:30:18.9408388Z triton_mm_2689 0.0430 ms 76.2% 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 2025-09-07T10:30:18.9409578Z triton_mm_2690 0.0440 ms 74.4% 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=5, num_warps=4 2025-09-07T10:30:18.9410772Z triton_mm_2699 0.0440 ms 74.4% 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 2025-09-07T10:30:18.9411959Z triton_mm_2691 0.0451 ms 72.7% 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 2025-09-07T10:30:18.9413146Z triton_mm_2694 0.0471 ms 69.6% 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 2025-09-07T10:30:18.9414336Z triton_mm_2697 0.0481 ms 68.1% 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 2025-09-07T10:30:18.9415517Z triton_mm_2692 0.0512 ms 64.0% 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 2025-09-07T10:30:18.9416518Z SingleProcess AUTOTUNE benchmarking takes 0.3305 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:30:22.7879335Z Autotune Choices Stats: 2025-09-07T10:30:22.7880805Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.4679679870605469, "best_triton_pos": 1, "best_triton_time": 0.8386560082435608, "best_triton_kernel": "triton_mm_2639", "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"} 2025-09-07T10:30:22.7899948Z AUTOTUNE mm(2048x30528, 30528x1024) 2025-09-07T10:30:22.7900269Z strides: [30528, 1], [1024, 1] 2025-09-07T10:30:22.7900568Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:22.7900869Z mm 0.4680 ms 100.0% 2025-09-07T10:30:22.7901557Z triton_mm_2639 0.8387 ms 55.8% 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 2025-09-07T10:30:22.7902743Z triton_mm_2637 0.8776 ms 53.3% 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=3, num_warps=4 2025-09-07T10:30:22.7903939Z triton_mm_2644 0.9349 ms 50.1% 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=3, num_warps=4 2025-09-07T10:30:22.7905141Z triton_mm_2640 0.9769 ms 47.9% 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=3, num_warps=4 2025-09-07T10:30:22.7906324Z triton_mm_2634 0.9974 ms 46.9% 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=2, num_warps=4 2025-09-07T10:30:22.7907509Z triton_mm_2643 1.0066 ms 46.5% 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 2025-09-07T10:30:22.7908705Z triton_mm_2645 1.0619 ms 44.1% 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 2025-09-07T10:30:22.7909873Z triton_mm_2635 1.0844 ms 43.2% 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 2025-09-07T10:30:22.7911485Z triton_mm_2641 1.0885 ms 43.0% 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=4, num_warps=8 2025-09-07T10:30:22.7912509Z SingleProcess AUTOTUNE benchmarking takes 0.7633 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:30:23.1021096Z Autotune Choices Stats: 2025-09-07T10:30:23.1022537Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03276799991726875, "best_triton_pos": 1, "best_triton_time": 0.03276799991726875, "best_triton_kernel": "triton_mm_2675", "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"} 2025-09-07T10:30:23.1042188Z AUTOTUNE mm(2048x1024, 1024x1024) 2025-09-07T10:30:23.1042517Z strides: [1024, 1], [1024, 1] 2025-09-07T10:30:23.1042942Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:23.1043250Z mm 0.0328 ms 100.0% 2025-09-07T10:30:23.1043971Z triton_mm_2675 0.0328 ms 100.0% 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 2025-09-07T10:30:23.1045173Z triton_mm_2673 0.0338 ms 97.0% 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 2025-09-07T10:30:23.1046348Z triton_mm_2676 0.0358 ms 91.4% 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 2025-09-07T10:30:23.1047525Z triton_mm_2674 0.0389 ms 84.2% 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 2025-09-07T10:30:23.1048935Z triton_mm_2680 0.0389 ms 84.2% 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 2025-09-07T10:30:23.1050124Z triton_mm_2671 0.0399 ms 82.1% 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 2025-09-07T10:30:23.1051305Z triton_mm_2677 0.0399 ms 82.1% 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 2025-09-07T10:30:23.1052611Z triton_mm_2679 0.0410 ms 80.0% 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 2025-09-07T10:30:23.1053807Z triton_mm_2681 0.0430 ms 76.2% 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=5, num_warps=8 2025-09-07T10:30:23.1054816Z SingleProcess AUTOTUNE benchmarking takes 0.3117 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:30:23.5596762Z Autotune Choices Stats: 2025-09-07T10:30:23.5598226Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.07372800260782242, "best_triton_pos": 1, "best_triton_time": 0.08191999793052673, "best_triton_kernel": "triton_mm_2745", "best_triton_kernel_desc": "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"} 2025-09-07T10:30:23.5617750Z AUTOTUNE mm(2048x3072, 3072x1024) 2025-09-07T10:30:23.5618077Z strides: [3072, 1], [1024, 1] 2025-09-07T10:30:23.5618376Z dtypes: torch.float16, torch.float16 2025-09-07T10:30:23.5618683Z mm 0.0737 ms 100.0% 2025-09-07T10:30:23.5619388Z triton_mm_2745 0.0819 ms 90.0% 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 2025-09-07T10:30:23.5620590Z triton_mm_2747 0.0829 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 2025-09-07T10:30:23.5621984Z triton_mm_2748 0.0881 ms 83.7% 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 2025-09-07T10:30:23.5623162Z triton_mm_2752 0.0942 ms 78.3% 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 2025-09-07T10:30:23.5624347Z triton_mm_2743 0.0983 ms 75.0% 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 2025-09-07T10:30:23.5625537Z triton_mm_2749 0.0993 ms 74.2% 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 2025-09-07T10:30:23.5626741Z triton_mm_2751 0.1014 ms 72.7% 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 2025-09-07T10:30:23.5628067Z triton_mm_2744 0.1055 ms 69.9% 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 2025-09-07T10:30:23.5629251Z triton_mm_2742 0.1096 ms 67.3% 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=2, num_warps=4 2025-09-07T10:30:23.5630269Z SingleProcess AUTOTUNE benchmarking takes 0.4550 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:30:31.2415535Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:30:31.2417196Z pred = mod(**cloned_inputs) 2025-09-07T10:30:31.2417964Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 1308, in forward 2025-09-07T10:30:31.2418665Z outputs = self.bert( 2025-09-07T10:30:31.2419310Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 964, in forward 2025-09-07T10:30:31.2420004Z embedding_output = self.embeddings( 2025-09-07T10:30:31.2420690Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py", line 186, in forward 2025-09-07T10:30:31.2421471Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T10:30:31.2421781Z 2025-09-07T10:30:31.2421785Z 2025-09-07T10:30:32.9504469Z W0907 10:30:32.949000 24785 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:31:39.2258990Z pass 2025-09-07T10:31:47.0625871Z /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. 2025-09-07T10:31:47.0627284Z import pynvml # type: ignore[import] 2025-09-07T10:31:50.0097306Z 2025-09-07T10:31:51.7552408Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T10:31:51.7554710Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T10:31:51.7560421Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T10:31:51.7561784Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T10:31:51.7564377Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T10:31:51.7566608Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T10:31:51.7568092Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T10:31:51.7569243Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T10:31:55.1986661Z 2025-09-07T10:31:55.1987051Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:31:55.1987457Z cuda train hf_BigBird 2025-09-07T10:33:07.6937326Z Autotune Choices Stats: 2025-09-07T10:33:07.6938890Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.09830400347709656, "best_triton_pos": 1, "best_triton_time": 0.11059200018644333, "best_triton_kernel": "triton_mm_352", "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"} 2025-09-07T10:33:07.6977567Z AUTOTUNE addmm(4096x3072, 4096x768, 768x3072) 2025-09-07T10:33:07.6977961Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:33:07.6978339Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:33:07.6978715Z bias_addmm 0.0983 ms 100.0% 2025-09-07T10:33:07.6979458Z triton_mm_352 0.1106 ms 88.9% 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=3, num_warps=4 2025-09-07T10:33:07.6980645Z triton_mm_345 0.1208 ms 81.4% 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 2025-09-07T10:33:07.6981822Z triton_mm_351 0.1208 ms 81.4% 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 2025-09-07T10:33:07.6983009Z triton_mm_348 0.1239 ms 79.3% 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 2025-09-07T10:33:07.6984186Z triton_mm_347 0.1300 ms 75.6% 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 2025-09-07T10:33:07.6985370Z triton_mm_353 0.1300 ms 75.6% 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 2025-09-07T10:33:07.6986113Z addmm 0.1331 ms 73.8% 2025-09-07T10:33:07.6986796Z triton_mm_349 0.1485 ms 66.2% 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 2025-09-07T10:33:07.6987964Z triton_mm_346 0.1556 ms 63.2% 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 2025-09-07T10:33:07.6988980Z SingleProcess AUTOTUNE benchmarking takes 0.6314 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T10:33:10.8931108Z Autotune Choices Stats: 2025-09-07T10:33:10.8934302Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03174399957060814, "best_triton_pos": 1, "best_triton_time": 0.03276799991726875, "best_triton_kernel": "triton_mm_16", "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"} 2025-09-07T10:33:10.8953672Z AUTOTUNE mm(4096x768, 768x768) 2025-09-07T10:33:10.8954222Z strides: [768, 1], [1, 768] 2025-09-07T10:33:10.8954732Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:10.8955269Z mm 0.0317 ms 100.0% 2025-09-07T10:33:10.8956568Z triton_mm_16 0.0328 ms 96.9% 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=3, num_warps=4 2025-09-07T10:33:10.8958811Z triton_mm_15 0.0348 ms 91.2% 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 2025-09-07T10:33:10.8960973Z triton_mm_11 0.0358 ms 88.6% 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 2025-09-07T10:33:10.8963544Z triton_mm_12 0.0358 ms 88.6% 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 2025-09-07T10:33:10.8965489Z triton_mm_17 0.0358 ms 88.6% 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 2025-09-07T10:33:10.8967489Z triton_mm_9 0.0369 ms 86.1% 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 2025-09-07T10:33:10.8969888Z triton_mm_10 0.0410 ms 77.5% 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 2025-09-07T10:33:10.8971883Z triton_mm_13 0.0410 ms 77.5% 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 2025-09-07T10:33:10.8973853Z triton_mm_14 0.0430 ms 73.8% 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=2, num_warps=8 2025-09-07T10:33:10.8975549Z SingleProcess AUTOTUNE benchmarking takes 0.3338 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:33:11.2667221Z Autotune Choices Stats: 2025-09-07T10:33:11.2669687Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.03174399957060814, "best_triton_pos": 1, "best_triton_time": 0.03379200026392937, "best_triton_kernel": "triton_mm_34", "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"} 2025-09-07T10:33:11.2690619Z AUTOTUNE addmm(4096x768, 4096x768, 768x768) 2025-09-07T10:33:11.2691142Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:33:11.2691648Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:33:11.2692208Z bias_addmm 0.0317 ms 100.0% 2025-09-07T10:33:11.2693433Z triton_mm_34 0.0338 ms 93.9% 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=3, num_warps=4 2025-09-07T10:33:11.2695303Z triton_mm_33 0.0358 ms 88.6% 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 2025-09-07T10:33:11.2697210Z triton_mm_29 0.0379 ms 83.8% 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 2025-09-07T10:33:11.2699773Z triton_mm_35 0.0379 ms 83.8% 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 2025-09-07T10:33:11.2701841Z triton_mm_30 0.0399 ms 79.5% 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=3, num_warps=4 2025-09-07T10:33:11.2703031Z addmm 0.0430 ms 73.8% 2025-09-07T10:33:11.2704170Z triton_mm_27 0.0430 ms 73.8% 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=3, num_warps=4 2025-09-07T10:33:11.2706304Z triton_mm_28 0.0430 ms 73.8% 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 2025-09-07T10:33:11.2708415Z triton_mm_31 0.0430 ms 73.8% 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 2025-09-07T10:33:11.2710314Z SingleProcess AUTOTUNE benchmarking takes 0.3719 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:33:11.5158593Z Autotune Choices Stats: 2025-09-07T10:33:11.5160688Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_61", "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": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T10:33:11.5182658Z AUTOTUNE bmm(48x64x64, 48x64x1024) 2025-09-07T10:33:11.5183247Z strides: [4096, 64, 1], [65536, 1, 64] 2025-09-07T10:33:11.5183781Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:11.5185593Z triton_bmm_61 0.0164 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 2025-09-07T10:33:11.5187811Z triton_bmm_62 0.0164 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 2025-09-07T10:33:11.5190096Z triton_bmm_58 0.0174 ms 94.1% 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 2025-09-07T10:33:11.5192326Z triton_bmm_65 0.0174 ms 94.1% 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 2025-09-07T10:33:11.5194568Z triton_bmm_66 0.0174 ms 94.1% 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 2025-09-07T10:33:11.5196829Z triton_bmm_70 0.0174 ms 94.1% 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=5, num_warps=8 2025-09-07T10:33:11.5199051Z triton_bmm_55 0.0184 ms 88.9% 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 2025-09-07T10:33:11.5201267Z triton_bmm_63 0.0184 ms 88.9% 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 2025-09-07T10:33:11.5203619Z triton_bmm_68 0.0184 ms 88.9% 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 2025-09-07T10:33:11.5205861Z triton_bmm_59 0.0195 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:33:11.5207810Z SingleProcess AUTOTUNE benchmarking takes 0.2457 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T10:33:11.7510696Z Autotune Choices Stats: 2025-09-07T10:33:11.7513279Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_79", "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": 0.021503999829292297, "best_triton_pos": 0} 2025-09-07T10:33:11.7534922Z AUTOTUNE bmm(48x64x1024, 48x1024x64) 2025-09-07T10:33:11.7535553Z strides: [65536, 1024, 1], [65536, 64, 1] 2025-09-07T10:33:11.7536131Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:11.7537650Z triton_bmm_79 0.0215 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 2025-09-07T10:33:11.7539965Z triton_bmm_83 0.0215 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=4, num_warps=4 2025-09-07T10:33:11.7542324Z triton_bmm_85 0.0215 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=8 2025-09-07T10:33:11.7543724Z bmm 0.0236 ms 91.3% 2025-09-07T10:33:11.7545036Z triton_bmm_75 0.0236 ms 91.3% 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 2025-09-07T10:33:11.7547321Z triton_bmm_78 0.0236 ms 91.3% 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 2025-09-07T10:33:11.7549594Z triton_bmm_82 0.0236 ms 91.3% 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 2025-09-07T10:33:11.7552208Z triton_bmm_73 0.0246 ms 87.5% 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 2025-09-07T10:33:11.7554361Z triton_bmm_72 0.0256 ms 84.0% 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 2025-09-07T10:33:11.7556507Z triton_bmm_74 0.0256 ms 84.0% 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 2025-09-07T10:33:11.7558285Z SingleProcess AUTOTUNE benchmarking takes 0.2346 seconds and 0.0003 seconds precompiling for 16 choices 2025-09-07T10:33:11.9846977Z Autotune Choices Stats: 2025-09-07T10:33:11.9849125Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_90", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T10:33:11.9871727Z AUTOTUNE bmm(48x64x64, 48x64x448) 2025-09-07T10:33:11.9872324Z strides: [4096, 64, 1], [28672, 1, 64] 2025-09-07T10:33:11.9872904Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:11.9874305Z triton_bmm_90 0.0123 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 2025-09-07T10:33:11.9876514Z triton_bmm_92 0.0123 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=2, num_warps=4 2025-09-07T10:33:11.9878744Z triton_bmm_93 0.0123 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 2025-09-07T10:33:11.9880981Z triton_bmm_94 0.0123 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 2025-09-07T10:33:11.9883845Z triton_bmm_99 0.0123 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 2025-09-07T10:33:11.9886115Z triton_bmm_100 0.0123 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 2025-09-07T10:33:11.9888393Z triton_bmm_102 0.0123 ms 100.0% 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=5, num_warps=8 2025-09-07T10:33:11.9890650Z triton_bmm_87 0.0133 ms 92.3% 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 2025-09-07T10:33:11.9892875Z triton_bmm_91 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:33:11.9895113Z triton_bmm_95 0.0133 ms 92.3% 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=3, num_warps=4 2025-09-07T10:33:11.9897022Z SingleProcess AUTOTUNE benchmarking takes 0.2331 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:33:12.2006101Z Autotune Choices Stats: 2025-09-07T10:33:12.2008218Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_105", "best_kernel_desc": "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", "best_time": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T10:33:12.2031716Z AUTOTUNE bmm(48x64x448, 48x448x64) 2025-09-07T10:33:12.2032765Z strides: [28672, 448, 1], [28672, 64, 1] 2025-09-07T10:33:12.2033340Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:12.2034704Z triton_bmm_105 0.0143 ms 100.0% 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 2025-09-07T10:33:12.2036884Z triton_bmm_106 0.0143 ms 100.0% 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 2025-09-07T10:33:12.2039060Z triton_bmm_110 0.0143 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 2025-09-07T10:33:12.2041255Z triton_bmm_111 0.0143 ms 100.0% 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 2025-09-07T10:33:12.2043803Z triton_bmm_114 0.0143 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 2025-09-07T10:33:12.2046076Z triton_bmm_115 0.0143 ms 100.0% 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=4, num_warps=4 2025-09-07T10:33:12.2048309Z triton_bmm_117 0.0143 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=8 2025-09-07T10:33:12.2049637Z bmm 0.0154 ms 93.3% 2025-09-07T10:33:12.2050889Z triton_bmm_104 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:33:12.2053096Z triton_bmm_107 0.0154 ms 93.3% 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 2025-09-07T10:33:12.2055011Z SingleProcess AUTOTUNE benchmarking takes 0.2154 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T10:33:12.4757227Z Autotune Choices Stats: 2025-09-07T10:33:12.4759966Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_126", "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=5, num_warps=4", "best_time": 0.03276799991726875, "best_triton_pos": 0} 2025-09-07T10:33:12.4783523Z AUTOTUNE bmm(576x64x64, 576x64x192) 2025-09-07T10:33:12.4784170Z strides: [4096, 64, 1], [12288, 1, 64] 2025-09-07T10:33:12.4784762Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:12.4786166Z triton_bmm_126 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=5, num_warps=4 2025-09-07T10:33:12.4788540Z triton_bmm_129 0.0328 ms 100.0% 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 2025-09-07T10:33:12.4790971Z triton_bmm_130 0.0328 ms 100.0% 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=4, num_warps=4 2025-09-07T10:33:12.4793319Z triton_bmm_125 0.0338 ms 97.0% 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 2025-09-07T10:33:12.4795662Z triton_bmm_134 0.0338 ms 97.0% 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=5, num_warps=8 2025-09-07T10:33:12.4798000Z triton_bmm_119 0.0358 ms 91.4% 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 2025-09-07T10:33:12.4800648Z triton_bmm_122 0.0358 ms 91.4% 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 2025-09-07T10:33:12.4803135Z triton_bmm_124 0.0358 ms 91.4% 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=2, num_warps=4 2025-09-07T10:33:12.4805455Z triton_bmm_131 0.0358 ms 91.4% 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=3, num_warps=4 2025-09-07T10:33:12.4807773Z triton_bmm_127 0.0369 ms 88.9% 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 2025-09-07T10:33:12.4809752Z SingleProcess AUTOTUNE benchmarking takes 0.2746 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T10:33:12.7324990Z Autotune Choices Stats: 2025-09-07T10:33:12.7327344Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_159", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T10:33:12.7352503Z AUTOTUNE bmm(48x768x64, 48x64x64) 2025-09-07T10:33:12.7353099Z strides: [49152, 64, 1], [4096, 64, 1] 2025-09-07T10:33:12.7353686Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:12.7355124Z triton_bmm_159 0.0143 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 2025-09-07T10:33:12.7357412Z triton_bmm_157 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:33:12.7359704Z triton_bmm_158 0.0154 ms 93.3% 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=2, num_warps=4 2025-09-07T10:33:12.7362395Z triton_bmm_160 0.0154 ms 93.3% 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=5, num_warps=4 2025-09-07T10:33:12.7365038Z triton_bmm_163 0.0154 ms 93.3% 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 2025-09-07T10:33:12.7367304Z triton_bmm_164 0.0154 ms 93.3% 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=4, num_warps=4 2025-09-07T10:33:12.7369593Z triton_bmm_165 0.0154 ms 93.3% 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 2025-09-07T10:33:12.7371895Z triton_bmm_166 0.0154 ms 93.3% 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 2025-09-07T10:33:12.7374243Z triton_bmm_167 0.0154 ms 93.3% 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=2, num_warps=8 2025-09-07T10:33:12.7376600Z triton_bmm_168 0.0154 ms 93.3% 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 2025-09-07T10:33:12.7378643Z SingleProcess AUTOTUNE benchmarking takes 0.2554 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:33:12.9860381Z Autotune Choices Stats: 2025-09-07T10:33:12.9862542Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_199", "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": 0.03788800165057182, "best_triton_pos": 0} 2025-09-07T10:33:12.9887703Z AUTOTUNE bmm(576x64x192, 576x192x64) 2025-09-07T10:33:12.9888345Z strides: [12288, 192, 1], [12288, 64, 1] 2025-09-07T10:33:12.9888977Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:12.9890359Z triton_bmm_199 0.0379 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 2025-09-07T10:33:12.9892532Z triton_bmm_195 0.0389 ms 97.4% 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 2025-09-07T10:33:12.9894715Z triton_bmm_196 0.0399 ms 94.9% 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 2025-09-07T10:33:12.9896893Z triton_bmm_202 0.0399 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=5, num_warps=8 2025-09-07T10:33:12.9899240Z triton_bmm_194 0.0410 ms 92.5% 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=2, num_warps=4 2025-09-07T10:33:12.9901480Z triton_bmm_200 0.0410 ms 92.5% 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=4, num_warps=4 2025-09-07T10:33:12.9903698Z triton_bmm_190 0.0420 ms 90.2% 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 2025-09-07T10:33:12.9905879Z triton_bmm_197 0.0420 ms 90.2% 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 2025-09-07T10:33:12.9907939Z triton_bmm_193 0.0430 ms 88.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:33:12.9910351Z triton_bmm_198 0.0430 ms 88.1% 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=4, num_warps=8 2025-09-07T10:33:12.9912261Z SingleProcess AUTOTUNE benchmarking takes 0.2521 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T10:33:13.5526099Z Autotune Choices Stats: 2025-09-07T10:33:13.5528853Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.10035199671983719, "best_triton_pos": 1, "best_triton_time": 0.10342399775981903, "best_triton_kernel": "triton_mm_370", "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"} 2025-09-07T10:33:13.5553620Z AUTOTUNE mm(4096x3072, 3072x768) 2025-09-07T10:33:13.5554234Z strides: [3072, 1], [1, 3072] 2025-09-07T10:33:13.5554737Z dtypes: torch.float16, torch.float16 2025-09-07T10:33:13.5555283Z mm 0.1004 ms 100.0% 2025-09-07T10:33:13.5556602Z triton_mm_370 0.1034 ms 97.0% 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 2025-09-07T10:33:13.5558867Z triton_mm_369 0.1167 ms 86.0% 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 2025-09-07T10:33:13.5561112Z triton_mm_365 0.1208 ms 83.1% 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 2025-09-07T10:33:13.5563670Z triton_mm_366 0.1290 ms 77.8% 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 2025-09-07T10:33:13.5566203Z triton_mm_371 0.1341 ms 74.8% 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 2025-09-07T10:33:13.5568458Z triton_mm_364 0.1434 ms 70.0% 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 2025-09-07T10:33:13.5570689Z triton_mm_363 0.1444 ms 69.5% 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 2025-09-07T10:33:13.5572927Z triton_mm_362 0.1546 ms 64.9% 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 2025-09-07T10:33:13.5575163Z triton_mm_367 0.1546 ms 64.9% 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 2025-09-07T10:33:13.5577111Z SingleProcess AUTOTUNE benchmarking takes 0.5574 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:33:14.8760431Z Autotune Choices Stats: 2025-09-07T10:33:14.8762668Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_4497", "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": 1.8903039693832397, "best_triton_pos": 0} 2025-09-07T10:33:14.8788208Z AUTOTUNE addmm(4096x50358, 4096x768, 768x50358) 2025-09-07T10:33:14.8788845Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:33:14.8789462Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:33:14.8790977Z triton_mm_4497 1.8903 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 2025-09-07T10:33:14.8793287Z triton_mm_4498 2.0326 ms 93.0% 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 2025-09-07T10:33:14.8795955Z triton_mm_4491 2.1043 ms 89.8% 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=3, num_warps=4 2025-09-07T10:33:14.8797370Z bias_addmm 2.1699 ms 87.1% 2025-09-07T10:33:14.8798714Z triton_mm_4494 2.2661 ms 83.4% 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 2025-09-07T10:33:14.8800970Z triton_mm_4493 2.3316 ms 81.1% 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 2025-09-07T10:33:14.8803377Z triton_mm_4499 2.3788 ms 79.5% 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 2025-09-07T10:33:14.8805639Z triton_mm_4495 2.8283 ms 66.8% 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 2025-09-07T10:33:14.8807893Z triton_mm_4492 2.8457 ms 66.4% 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=4, num_warps=8 2025-09-07T10:33:14.8810135Z triton_mm_4489 2.8815 ms 65.6% 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 2025-09-07T10:33:14.8812048Z SingleProcess AUTOTUNE benchmarking takes 1.0467 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:34:08.5228555Z Autotune Choices Stats: 2025-09-07T10:34:08.5230036Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 1.1048959493637085, "best_triton_pos": 1, "best_triton_time": 1.837056040763855, "best_triton_kernel": "triton_mm_4527", "best_triton_kernel_desc": "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"} 2025-09-07T10:34:08.5257183Z AUTOTUNE mm(50358x4096, 4096x768) 2025-09-07T10:34:08.5257592Z strides: [1, 50368], [768, 1] 2025-09-07T10:34:08.5257889Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:08.5258179Z mm 1.1049 ms 100.0% 2025-09-07T10:34:08.5258887Z triton_mm_4527 1.8371 ms 60.1% 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 2025-09-07T10:34:08.5260082Z triton_mm_4533 1.8964 ms 58.3% 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 2025-09-07T10:34:08.5261271Z triton_mm_4529 2.0429 ms 54.1% 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 2025-09-07T10:34:08.5262480Z triton_mm_4534 2.0838 ms 53.0% 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 2025-09-07T10:34:08.5263667Z triton_mm_4532 2.3644 ms 46.7% 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=2, num_warps=8 2025-09-07T10:34:08.5264847Z triton_mm_4535 2.6071 ms 42.4% 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 2025-09-07T10:34:08.5266037Z triton_mm_4530 2.6194 ms 42.2% 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=3, num_warps=4 2025-09-07T10:34:08.5267222Z triton_mm_4528 2.7146 ms 40.7% 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=4, num_warps=8 2025-09-07T10:34:08.5268684Z triton_mm_4524 2.7525 ms 40.1% 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=2, num_warps=4 2025-09-07T10:34:08.5269710Z SingleProcess AUTOTUNE benchmarking takes 0.9673 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:34:09.3578558Z Autotune Choices Stats: 2025-09-07T10:34:09.3580028Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.0942080020904541, "best_triton_pos": 1, "best_triton_time": 0.10342399775981903, "best_triton_kernel": "triton_mm_4588", "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"} 2025-09-07T10:34:09.3606702Z AUTOTUNE mm(4096x768, 768x3072) 2025-09-07T10:34:09.3607038Z strides: [768, 1], [3072, 1] 2025-09-07T10:34:09.3607330Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:09.3607635Z mm 0.0942 ms 100.0% 2025-09-07T10:34:09.3608346Z triton_mm_4588 0.1034 ms 91.1% 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=3, num_warps=4 2025-09-07T10:34:09.3609545Z triton_mm_4581 0.1106 ms 85.2% 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 2025-09-07T10:34:09.3610720Z triton_mm_4583 0.1116 ms 84.4% 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 2025-09-07T10:34:09.3611902Z triton_mm_4584 0.1137 ms 82.9% 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=3, num_warps=4 2025-09-07T10:34:09.3615251Z triton_mm_4587 0.1147 ms 82.1% 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 2025-09-07T10:34:09.3616459Z triton_mm_4589 0.1229 ms 76.7% 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 2025-09-07T10:34:09.3617768Z triton_mm_4582 0.1290 ms 73.0% 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 2025-09-07T10:34:09.3618964Z triton_mm_4586 0.1372 ms 68.7% 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=2, num_warps=8 2025-09-07T10:34:09.3620153Z triton_mm_4578 0.1464 ms 64.3% 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=2, num_warps=4 2025-09-07T10:34:09.3621186Z SingleProcess AUTOTUNE benchmarking takes 0.5426 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:34:10.6886610Z Autotune Choices Stats: 2025-09-07T10:34:10.6887868Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_5155", "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=5, num_warps=4", "best_time": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T10:34:10.6915315Z AUTOTUNE bmm(48x1024x64, 48x64x64) 2025-09-07T10:34:10.6915658Z strides: [65536, 1, 1024], [4096, 64, 1] 2025-09-07T10:34:10.6915994Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:10.6916763Z triton_bmm_5155 0.0164 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 2025-09-07T10:34:10.6917962Z triton_bmm_5158 0.0164 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 2025-09-07T10:34:10.6919540Z triton_bmm_5159 0.0164 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=4, num_warps=4 2025-09-07T10:34:10.6920746Z triton_bmm_5154 0.0174 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=3, num_warps=8 2025-09-07T10:34:10.6921940Z triton_bmm_5160 0.0174 ms 94.1% 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=3, num_warps=4 2025-09-07T10:34:10.6923387Z triton_bmm_5164 0.0174 ms 94.1% 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 2025-09-07T10:34:10.6924159Z bmm 0.0184 ms 88.9% 2025-09-07T10:34:10.6924835Z triton_bmm_5156 0.0184 ms 88.9% 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=3, num_warps=4 2025-09-07T10:34:10.6926031Z triton_bmm_5163 0.0184 ms 88.9% 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=3, num_warps=4 2025-09-07T10:34:10.6927219Z triton_bmm_5152 0.0195 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:34:10.6928240Z SingleProcess AUTOTUNE benchmarking takes 0.2528 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:12.8780296Z Autotune Choices Stats: 2025-09-07T10:34:12.8781529Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_5189", "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": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T10:34:12.8808670Z AUTOTUNE bmm(48x64x64, 48x64x1024) 2025-09-07T10:34:12.8809004Z strides: [4096, 1, 64], [65536, 1024, 1] 2025-09-07T10:34:12.8809329Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:12.8810091Z triton_bmm_5189 0.0174 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 2025-09-07T10:34:12.8811293Z triton_bmm_5190 0.0174 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 2025-09-07T10:34:12.8812493Z triton_bmm_5191 0.0174 ms 100.0% 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 2025-09-07T10:34:12.8813702Z triton_bmm_5193 0.0174 ms 100.0% 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 2025-09-07T10:34:12.8814894Z triton_bmm_5194 0.0174 ms 100.0% 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=4, num_warps=4 2025-09-07T10:34:12.8816092Z triton_bmm_5198 0.0174 ms 100.0% 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=5, num_warps=8 2025-09-07T10:34:12.8817289Z triton_bmm_5195 0.0184 ms 94.4% 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=3, num_warps=4 2025-09-07T10:34:12.8818534Z triton_bmm_5187 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:34:12.8819713Z triton_bmm_5188 0.0195 ms 89.5% 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=2, num_warps=4 2025-09-07T10:34:12.8821083Z triton_bmm_5192 0.0195 ms 89.5% 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 2025-09-07T10:34:12.8822118Z SingleProcess AUTOTUNE benchmarking takes 0.2410 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T10:34:16.5338544Z Autotune Choices Stats: 2025-09-07T10:34:16.5340049Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.09216000139713287, "best_triton_pos": 1, "best_triton_time": 0.11980800330638885, "best_triton_kernel": "triton_mm_4599", "best_triton_kernel_desc": "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"} 2025-09-07T10:34:16.5368695Z AUTOTUNE mm(768x4096, 4096x3072) 2025-09-07T10:34:16.5369016Z strides: [1, 768], [3072, 1] 2025-09-07T10:34:16.5369319Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:16.5369626Z mm 0.0922 ms 100.0% 2025-09-07T10:34:16.5370349Z triton_mm_4599 0.1198 ms 76.9% 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 2025-09-07T10:34:16.5371541Z triton_mm_4601 0.1229 ms 75.0% 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 2025-09-07T10:34:16.5372712Z triton_mm_4602 0.1270 ms 72.6% 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 2025-09-07T10:34:16.5373907Z triton_mm_4606 0.1321 ms 69.8% 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 2025-09-07T10:34:16.5375473Z triton_mm_4605 0.1372 ms 67.2% 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 2025-09-07T10:34:16.5376669Z triton_mm_4603 0.1382 ms 66.7% 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 2025-09-07T10:34:16.5377951Z triton_mm_4607 0.1556 ms 59.2% 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=5, num_warps=8 2025-09-07T10:34:16.5379137Z triton_mm_4600 0.1567 ms 58.8% 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 2025-09-07T10:34:16.5380318Z triton_mm_4598 0.1577 ms 58.4% 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=5, num_warps=4 2025-09-07T10:34:16.5381341Z SingleProcess AUTOTUNE benchmarking takes 0.5538 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:17.1032929Z Autotune Choices Stats: 2025-09-07T10:34:17.1034400Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.0942080020904541, "best_triton_pos": 1, "best_triton_time": 0.11673600226640701, "best_triton_kernel": "triton_mm_4637", "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"} 2025-09-07T10:34:17.1063607Z AUTOTUNE mm(3072x4096, 4096x768) 2025-09-07T10:34:17.1063921Z strides: [1, 3072], [768, 1] 2025-09-07T10:34:17.1064272Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:17.1064577Z mm 0.0942 ms 100.0% 2025-09-07T10:34:17.1065281Z triton_mm_4637 0.1167 ms 80.7% 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 2025-09-07T10:34:17.1066794Z triton_mm_4635 0.1188 ms 79.3% 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=3, num_warps=4 2025-09-07T10:34:17.1067994Z triton_mm_4638 0.1219 ms 77.3% 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 2025-09-07T10:34:17.1069184Z triton_mm_4642 0.1321 ms 71.3% 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 2025-09-07T10:34:17.1070389Z triton_mm_4641 0.1372 ms 68.7% 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 2025-09-07T10:34:17.1071585Z triton_mm_4639 0.1434 ms 65.7% 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 2025-09-07T10:34:17.1072768Z triton_mm_4636 0.1505 ms 62.6% 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 2025-09-07T10:34:17.1073948Z triton_mm_4643 0.1556 ms 60.5% 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 2025-09-07T10:34:17.1075127Z triton_mm_4632 0.1587 ms 59.4% 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=2, num_warps=4 2025-09-07T10:34:17.1076127Z SingleProcess AUTOTUNE benchmarking takes 0.5600 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:17.6053525Z Autotune Choices Stats: 2025-09-07T10:34:17.6055317Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03481600061058998, "best_triton_pos": 1, "best_triton_time": 0.05222399905323982, "best_triton_kernel": "triton_mm_4565", "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"} 2025-09-07T10:34:17.6083904Z AUTOTUNE mm(768x4096, 4096x768) 2025-09-07T10:34:17.6084221Z strides: [1, 768], [768, 1] 2025-09-07T10:34:17.6084553Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:17.6084855Z mm 0.0348 ms 100.0% 2025-09-07T10:34:17.6085567Z triton_mm_4565 0.0522 ms 66.7% 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 2025-09-07T10:34:17.6086759Z triton_mm_4562 0.0543 ms 64.2% 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 2025-09-07T10:34:17.6087955Z triton_mm_4564 0.0584 ms 59.6% 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 2025-09-07T10:34:17.6089152Z triton_mm_4567 0.0584 ms 59.6% 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 2025-09-07T10:34:17.6090308Z triton_mm_4561 0.0604 ms 57.6% 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 2025-09-07T10:34:17.6091484Z triton_mm_4555 0.0707 ms 49.3% 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 2025-09-07T10:34:17.6092662Z triton_mm_4563 0.0707 ms 49.3% 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=3, num_warps=4 2025-09-07T10:34:17.6094036Z triton_mm_4566 0.0717 ms 48.6% 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 2025-09-07T10:34:17.6095228Z triton_mm_4570 0.0727 ms 47.9% 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=3, num_warps=4 2025-09-07T10:34:17.6096254Z SingleProcess AUTOTUNE benchmarking takes 0.3794 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:20.1084814Z Autotune Choices Stats: 2025-09-07T10:34:20.1086313Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 1.3731839656829834, "best_triton_pos": 1, "best_triton_time": 1.8810880184173584, "best_triton_kernel": "triton_mm_4516", "best_triton_kernel_desc": "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"} 2025-09-07T10:34:20.1117347Z AUTOTUNE mm(4096x50360, 50360x768) 2025-09-07T10:34:20.1117703Z strides: [50368, 1], [768, 1] 2025-09-07T10:34:20.1118003Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:20.1118334Z mm 1.3732 ms 100.0% 2025-09-07T10:34:20.1119048Z triton_mm_4516 1.8811 ms 73.0% 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 2025-09-07T10:34:20.1120269Z triton_mm_4515 1.8944 ms 72.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:34:20.1121479Z triton_mm_4517 2.1125 ms 65.0% 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 2025-09-07T10:34:20.1122677Z triton_mm_4509 2.1238 ms 64.7% 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=3, num_warps=4 2025-09-07T10:34:20.1124449Z triton_mm_4514 2.3357 ms 58.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:34:20.1125636Z triton_mm_4507 2.5487 ms 53.9% 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 2025-09-07T10:34:20.1126808Z triton_mm_4511 2.5723 ms 53.4% 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 2025-09-07T10:34:20.1127989Z triton_mm_4510 2.6112 ms 52.6% 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 2025-09-07T10:34:20.1129188Z triton_mm_4512 2.8744 ms 47.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:34:20.1130232Z SingleProcess AUTOTUNE benchmarking takes 1.0049 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:20.4336974Z Autotune Choices Stats: 2025-09-07T10:34:20.4338223Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4552", "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": 0.03174399957060814, "best_triton_pos": 0} 2025-09-07T10:34:20.4367372Z AUTOTUNE mm(4096x768, 768x768) 2025-09-07T10:34:20.4367663Z strides: [768, 1], [768, 1] 2025-09-07T10:34:20.4367958Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:20.4368732Z triton_mm_4552 0.0317 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 2025-09-07T10:34:20.4370243Z triton_mm_4551 0.0338 ms 93.9% 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 2025-09-07T10:34:20.4371000Z mm 0.0348 ms 91.2% 2025-09-07T10:34:20.4371678Z triton_mm_4545 0.0358 ms 88.6% 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=3, num_warps=4 2025-09-07T10:34:20.4372856Z triton_mm_4547 0.0358 ms 88.6% 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 2025-09-07T10:34:20.4374040Z triton_mm_4548 0.0358 ms 88.6% 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 2025-09-07T10:34:20.4375228Z triton_mm_4553 0.0369 ms 86.1% 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 2025-09-07T10:34:20.4376419Z triton_mm_4546 0.0399 ms 79.5% 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 2025-09-07T10:34:20.4377688Z triton_mm_4549 0.0420 ms 75.6% 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 2025-09-07T10:34:20.4378876Z triton_mm_4550 0.0420 ms 75.6% 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=2, num_warps=8 2025-09-07T10:34:20.4379900Z SingleProcess AUTOTUNE benchmarking takes 0.3219 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:34:20.9849860Z Autotune Choices Stats: 2025-09-07T10:34:20.9851661Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.09830400347709656, "best_triton_pos": 1, "best_triton_time": 0.1013759970664978, "best_triton_kernel": "triton_mm_4624", "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"} 2025-09-07T10:34:20.9882054Z AUTOTUNE mm(4096x3072, 3072x768) 2025-09-07T10:34:20.9882500Z strides: [3072, 1], [768, 1] 2025-09-07T10:34:20.9883211Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:20.9883660Z mm 0.0983 ms 100.0% 2025-09-07T10:34:20.9884586Z triton_mm_4624 0.1014 ms 97.0% 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 2025-09-07T10:34:20.9886420Z triton_mm_4623 0.1085 ms 90.6% 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 2025-09-07T10:34:20.9888169Z triton_mm_4625 0.1178 ms 83.5% 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 2025-09-07T10:34:20.9889731Z triton_mm_4617 0.1198 ms 82.1% 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 2025-09-07T10:34:20.9891279Z triton_mm_4619 0.1219 ms 80.7% 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 2025-09-07T10:34:20.9892832Z triton_mm_4620 0.1229 ms 80.0% 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 2025-09-07T10:34:20.9894384Z triton_mm_4622 0.1516 ms 64.9% 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=2, num_warps=8 2025-09-07T10:34:20.9896399Z triton_mm_4621 0.1567 ms 62.7% 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 2025-09-07T10:34:20.9898183Z triton_mm_4618 0.1577 ms 62.3% 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 2025-09-07T10:34:20.9899522Z SingleProcess AUTOTUNE benchmarking takes 0.5476 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:21.2308880Z Autotune Choices Stats: 2025-09-07T10:34:21.2311053Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_5085", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T10:34:21.2340653Z AUTOTUNE bmm(48x448x64, 48x64x64) 2025-09-07T10:34:21.2341239Z strides: [28672, 1, 448], [4096, 64, 1] 2025-09-07T10:34:21.2341841Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:21.2343258Z triton_bmm_5085 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:34:21.2345522Z triton_bmm_5086 0.0123 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=2, num_warps=4 2025-09-07T10:34:21.2347748Z triton_bmm_5088 0.0123 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 2025-09-07T10:34:21.2349978Z triton_bmm_5089 0.0123 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 2025-09-07T10:34:21.2352579Z triton_bmm_5095 0.0123 ms 100.0% 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=2, num_warps=8 2025-09-07T10:34:21.2354825Z triton_bmm_5080 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T10:34:21.2357239Z triton_bmm_5084 0.0133 ms 92.3% 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 2025-09-07T10:34:21.2359418Z triton_bmm_5087 0.0133 ms 92.3% 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 2025-09-07T10:34:21.2361616Z triton_bmm_5090 0.0133 ms 92.3% 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=4, num_warps=8 2025-09-07T10:34:21.2364180Z triton_bmm_5091 0.0133 ms 92.3% 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 2025-09-07T10:34:21.2366075Z SingleProcess AUTOTUNE benchmarking takes 0.2407 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:21.5146763Z Autotune Choices Stats: 2025-09-07T10:34:21.5148932Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_4888", "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=5, num_warps=4", "best_time": 0.03276799991726875, "best_triton_pos": 0} 2025-09-07T10:34:21.5180247Z AUTOTUNE bmm(576x192x64, 576x64x64) 2025-09-07T10:34:21.5180842Z strides: [12288, 1, 192], [4096, 64, 1] 2025-09-07T10:34:21.5181436Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:21.5182873Z triton_bmm_4888 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=5, num_warps=4 2025-09-07T10:34:21.5185494Z triton_bmm_4891 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 2025-09-07T10:34:21.5187733Z triton_bmm_4892 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=4, num_warps=4 2025-09-07T10:34:21.5190177Z triton_bmm_4887 0.0338 ms 97.0% 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 2025-09-07T10:34:21.5192405Z triton_bmm_4897 0.0338 ms 97.0% 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 2025-09-07T10:34:21.5194654Z triton_bmm_4889 0.0348 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 2025-09-07T10:34:21.5196898Z triton_bmm_4893 0.0348 ms 94.1% 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=3, num_warps=4 2025-09-07T10:34:21.5199058Z triton_bmm_4896 0.0348 ms 94.1% 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 2025-09-07T10:34:21.5201286Z triton_bmm_4886 0.0358 ms 91.4% 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=2, num_warps=4 2025-09-07T10:34:21.5203820Z triton_bmm_4890 0.0358 ms 91.4% 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 2025-09-07T10:34:21.5206089Z SingleProcess AUTOTUNE benchmarking takes 0.2823 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:34:21.7371031Z Autotune Choices Stats: 2025-09-07T10:34:21.7373337Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_4826", "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=4, num_warps=4", "best_time": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T10:34:21.7404886Z AUTOTUNE bmm(48x64x768, 48x768x64) 2025-09-07T10:34:21.7405489Z strides: [49152, 1, 64], [49152, 64, 1] 2025-09-07T10:34:21.7406085Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:21.7407569Z triton_bmm_4826 0.0174 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=4, num_warps=4 2025-09-07T10:34:21.7409960Z triton_bmm_4822 0.0184 ms 94.4% 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=5, num_warps=4 2025-09-07T10:34:21.7412319Z triton_bmm_4828 0.0184 ms 94.4% 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=8 2025-09-07T10:34:21.7413767Z bmm 0.0195 ms 89.5% 2025-09-07T10:34:21.7415102Z triton_bmm_4818 0.0195 ms 89.5% 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 2025-09-07T10:34:21.7417778Z triton_bmm_4821 0.0195 ms 89.5% 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=3, num_warps=8 2025-09-07T10:34:21.7420107Z triton_bmm_4824 0.0195 ms 89.5% 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=4, num_warps=8 2025-09-07T10:34:21.7422427Z triton_bmm_4825 0.0195 ms 89.5% 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=3, num_warps=4 2025-09-07T10:34:21.7425202Z triton_bmm_4816 0.0205 ms 85.0% 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 2025-09-07T10:34:21.7427536Z triton_bmm_4817 0.0205 ms 85.0% 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 2025-09-07T10:34:21.7429555Z SingleProcess AUTOTUNE benchmarking takes 0.2218 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T10:34:21.9717068Z Autotune Choices Stats: 2025-09-07T10:34:21.9719221Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_4787", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T10:34:21.9753167Z AUTOTUNE bmm(48x64x64, 48x64x448) 2025-09-07T10:34:21.9753557Z strides: [4096, 1, 64], [28672, 448, 1] 2025-09-07T10:34:21.9753876Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:21.9754654Z triton_bmm_4787 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:34:21.9755869Z triton_bmm_4788 0.0123 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=2, num_warps=4 2025-09-07T10:34:21.9757070Z triton_bmm_4789 0.0123 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 2025-09-07T10:34:21.9758626Z triton_bmm_4790 0.0123 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 2025-09-07T10:34:21.9759835Z triton_bmm_4792 0.0123 ms 100.0% 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 2025-09-07T10:34:21.9761023Z triton_bmm_4795 0.0123 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 2025-09-07T10:34:21.9762229Z triton_bmm_4796 0.0123 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 2025-09-07T10:34:21.9763662Z triton_bmm_4782 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T10:34:21.9764859Z triton_bmm_4783 0.0133 ms 92.3% 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 2025-09-07T10:34:21.9766047Z triton_bmm_4786 0.0133 ms 92.3% 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 2025-09-07T10:34:21.9767065Z SingleProcess AUTOTUNE benchmarking takes 0.2282 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:34:22.2213542Z Autotune Choices Stats: 2025-09-07T10:34:22.2214726Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_4837", "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=5, num_warps=4", "best_time": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T10:34:22.2247985Z AUTOTUNE bmm(48x768x64, 48x64x64) 2025-09-07T10:34:22.2248380Z strides: [49152, 64, 1], [4096, 1, 64] 2025-09-07T10:34:22.2248697Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:22.2249767Z triton_bmm_4837 0.0143 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 2025-09-07T10:34:22.2250975Z triton_bmm_4840 0.0143 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 2025-09-07T10:34:22.2252183Z triton_bmm_4841 0.0143 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=4, num_warps=4 2025-09-07T10:34:22.2253382Z triton_bmm_4833 0.0154 ms 93.3% 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 2025-09-07T10:34:22.2254560Z triton_bmm_4835 0.0154 ms 93.3% 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=2, num_warps=4 2025-09-07T10:34:22.2255746Z triton_bmm_4836 0.0154 ms 93.3% 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 2025-09-07T10:34:22.2256944Z triton_bmm_4842 0.0154 ms 93.3% 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 2025-09-07T10:34:22.2258208Z triton_bmm_4844 0.0154 ms 93.3% 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=2, num_warps=8 2025-09-07T10:34:22.2259411Z triton_bmm_4845 0.0154 ms 93.3% 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 2025-09-07T10:34:22.2260763Z triton_bmm_4846 0.0154 ms 93.3% 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=5, num_warps=8 2025-09-07T10:34:22.2261799Z SingleProcess AUTOTUNE benchmarking takes 0.2480 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:34:22.4973688Z Autotune Choices Stats: 2025-09-07T10:34:22.4974888Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_5024", "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=5, num_warps=4", "best_time": 0.03276799991726875, "best_triton_pos": 0} 2025-09-07T10:34:22.5008916Z AUTOTUNE bmm(576x64x64, 576x64x192) 2025-09-07T10:34:22.5009266Z strides: [4096, 1, 64], [12288, 192, 1] 2025-09-07T10:34:22.5009579Z dtypes: torch.float16, torch.float16 2025-09-07T10:34:22.5010363Z triton_bmm_5024 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=5, num_warps=4 2025-09-07T10:34:22.5011608Z triton_bmm_5027 0.0328 ms 100.0% 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 2025-09-07T10:34:22.5012819Z triton_bmm_5032 0.0328 ms 100.0% 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=5, num_warps=8 2025-09-07T10:34:22.5014013Z triton_bmm_5023 0.0338 ms 97.0% 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 2025-09-07T10:34:22.5015195Z triton_bmm_5028 0.0338 ms 97.0% 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=4, num_warps=4 2025-09-07T10:34:22.5016385Z triton_bmm_5025 0.0348 ms 94.1% 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 2025-09-07T10:34:22.5017950Z triton_bmm_5029 0.0348 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 2025-09-07T10:34:22.5019144Z triton_bmm_5022 0.0358 ms 91.4% 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=2, num_warps=4 2025-09-07T10:34:22.5020330Z triton_bmm_5021 0.0369 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:34:22.5021526Z triton_bmm_5026 0.0369 ms 88.9% 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=4, num_warps=8 2025-09-07T10:34:22.5022556Z SingleProcess AUTOTUNE benchmarking takes 0.2685 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:34:36.5474091Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:34:36.5476482Z pred = mod(**cloned_inputs) 2025-09-07T10:34:36.5477824Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 2303, in forward 2025-09-07T10:34:36.5479246Z outputs = self.bert( 2025-09-07T10:34:36.5480483Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1991, in forward 2025-09-07T10:34:36.5481832Z encoder_outputs = self.encoder( 2025-09-07T10:34:36.5483529Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1585, in forward 2025-09-07T10:34:36.5485481Z layer_outputs = layer_module( 2025-09-07T10:34:36.5486556Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T10:34:36.5487744Z return super().__call__(*args, **kwargs) 2025-09-07T10:34:36.5489086Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1468, in forward 2025-09-07T10:34:36.5490455Z self_attention_outputs = self.attention( 2025-09-07T10:34:36.5491819Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 1381, in forward 2025-09-07T10:34:36.5493182Z self_outputs = self.self( 2025-09-07T10:34:36.5494441Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 455, in forward 2025-09-07T10:34:36.5495999Z context_layer, attention_probs = self.bigbird_block_sparse_attention( 2025-09-07T10:34:36.5497910Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 592, in bigbird_block_sparse_attention 2025-09-07T10:34:36.5499701Z gathered_value = self.torch_gather_b2(blocked_value_matrix, rand_attn) 2025-09-07T10:34:36.5511775Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/big_bird/modeling_big_bird.py", line 957, in torch_gather_b2 2025-09-07T10:34:36.5513442Z out_flattened = flattened_params.index_select(0, flattened_indices) 2025-09-07T10:34:36.5514081Z 2025-09-07T10:34:36.5514090Z 2025-09-07T10:34:38.2892151Z W0907 10:34:38.288000 27901 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:35:09.3326339Z pass 2025-09-07T10:35:17.3221635Z /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. 2025-09-07T10:35:17.3223101Z import pynvml # type: ignore[import] 2025-09-07T10:35:19.9849567Z 2025-09-07T10:35:23.9525980Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:35:23.9526361Z loading model: 0it [00:03, ?it/s] 2025-09-07T10:35:23.9526676Z cuda train hf_DistilBert 2025-09-07T10:35:50.2678737Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:35:50.2680016Z pred = mod(**cloned_inputs) 2025-09-07T10:35:50.2680766Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 826, in forward 2025-09-07T10:35:50.2681577Z dlbrt_output = self.distilbert( 2025-09-07T10:35:50.2682308Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 723, in forward 2025-09-07T10:35:50.2683429Z embeddings = self.embeddings(input_ids, inputs_embeds) # (bs, seq_length, dim) 2025-09-07T10:35:50.2684351Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/distilbert/modeling_distilbert.py", line 124, in forward 2025-09-07T10:35:50.2685313Z position_embeddings = self.position_embeddings(position_ids) # (bs, max_seq_length, dim) 2025-09-07T10:35:50.2685740Z 2025-09-07T10:35:50.2685750Z 2025-09-07T10:35:50.7623680Z W0907 10:35:50.761000 34668 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:36:05.1398875Z pass 2025-09-07T10:36:09.3035254Z /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. 2025-09-07T10:36:09.3037189Z import pynvml # type: ignore[import] 2025-09-07T10:36:12.2674890Z 2025-09-07T10:36:18.6316308Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:36:18.6317397Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:36:18.7229156Z 2025-09-07T10:36:18.7229516Z loading model: 0it [00:06, ?it/s] 2025-09-07T10:36:18.7229917Z cuda train hf_GPT2 2025-09-07T10:36:39.3237858Z Autotune Choices Stats: 2025-09-07T10:36:39.3239410Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.03174399957060814, "best_triton_pos": 1, "best_triton_time": 0.03379200026392937, "best_triton_kernel": "triton_mm_52", "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"} 2025-09-07T10:36:39.3273124Z AUTOTUNE addmm(1024x3072, 1024x768, 768x3072) 2025-09-07T10:36:39.3273483Z strides: [0, 1], [768, 1], [3072, 1] 2025-09-07T10:36:39.3273839Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:36:39.3274193Z bias_addmm 0.0317 ms 100.0% 2025-09-07T10:36:39.3274925Z triton_mm_52 0.0338 ms 93.9% 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=3, num_warps=4 2025-09-07T10:36:39.3276121Z triton_mm_51 0.0348 ms 91.2% 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 2025-09-07T10:36:39.3277296Z triton_mm_47 0.0369 ms 86.1% 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 2025-09-07T10:36:39.3278822Z triton_mm_53 0.0369 ms 86.1% 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 2025-09-07T10:36:39.3280003Z triton_mm_45 0.0379 ms 83.8% 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=3, num_warps=4 2025-09-07T10:36:39.3281158Z triton_mm_46 0.0420 ms 75.6% 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 2025-09-07T10:36:39.3282332Z triton_mm_50 0.0420 ms 75.6% 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=2, num_warps=8 2025-09-07T10:36:39.3283742Z triton_mm_48 0.0430 ms 73.8% 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 2025-09-07T10:36:39.3284488Z addmm 0.0451 ms 70.5% 2025-09-07T10:36:39.3285033Z SingleProcess AUTOTUNE benchmarking takes 0.3705 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T10:36:42.0211374Z Autotune Choices Stats: 2025-09-07T10:36:42.0212583Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_9", "best_kernel_desc": "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", "best_time": 0.027648000046610832, "best_triton_pos": 0} 2025-09-07T10:36:42.0245167Z AUTOTUNE mm(1024x768, 768x2304) 2025-09-07T10:36:42.0245491Z strides: [768, 1], [2304, 1] 2025-09-07T10:36:42.0245842Z dtypes: torch.float16, torch.float16 2025-09-07T10:36:42.0246596Z triton_mm_9 0.0276 ms 100.0% 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 2025-09-07T10:36:42.0248192Z triton_mm_11 0.0276 ms 100.0% 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 2025-09-07T10:36:42.0249372Z triton_mm_12 0.0276 ms 100.0% 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 2025-09-07T10:36:42.0250111Z mm 0.0297 ms 93.1% 2025-09-07T10:36:42.0250796Z triton_mm_16 0.0307 ms 90.0% 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 2025-09-07T10:36:42.0251977Z triton_mm_10 0.0317 ms 87.1% 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=4, num_warps=8 2025-09-07T10:36:42.0253157Z triton_mm_13 0.0328 ms 84.4% 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 2025-09-07T10:36:42.0254317Z triton_mm_15 0.0328 ms 84.4% 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 2025-09-07T10:36:42.0255490Z triton_mm_17 0.0348 ms 79.4% 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 2025-09-07T10:36:42.0256653Z triton_mm_6 0.0358 ms 77.1% 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=2, num_warps=4 2025-09-07T10:36:42.0257733Z SingleProcess AUTOTUNE benchmarking takes 0.3065 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:36:42.2881034Z Autotune Choices Stats: 2025-09-07T10:36:42.2882987Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.016383999958634377, "best_triton_kernel": "triton_mm_29", "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"} 2025-09-07T10:36:42.2914527Z AUTOTUNE mm(1024x768, 768x768) 2025-09-07T10:36:42.2914844Z strides: [768, 1], [768, 1] 2025-09-07T10:36:42.2915135Z dtypes: torch.float16, torch.float16 2025-09-07T10:36:42.2915438Z mm 0.0164 ms 100.0% 2025-09-07T10:36:42.2916134Z triton_mm_29 0.0164 ms 100.0% 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 2025-09-07T10:36:42.2917308Z triton_mm_25 0.0174 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=3, num_warps=8 2025-09-07T10:36:42.2918477Z triton_mm_28 0.0174 ms 94.1% 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=4, num_warps=8 2025-09-07T10:36:42.2919656Z triton_mm_31 0.0174 ms 94.1% 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 2025-09-07T10:36:42.2920830Z triton_mm_34 0.0195 ms 84.2% 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 2025-09-07T10:36:42.2921985Z triton_mm_26 0.0205 ms 80.0% 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 2025-09-07T10:36:42.2923263Z triton_mm_27 0.0205 ms 80.0% 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 2025-09-07T10:36:42.2924603Z triton_mm_30 0.0205 ms 80.0% 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 2025-09-07T10:36:42.2925785Z triton_mm_35 0.0205 ms 80.0% 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 2025-09-07T10:36:42.2926811Z SingleProcess AUTOTUNE benchmarking takes 0.2663 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:36:42.6541976Z Autotune Choices Stats: 2025-09-07T10:36:42.6543140Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_65", "best_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", "best_time": 0.04095999896526337, "best_triton_pos": 0} 2025-09-07T10:36:42.6576830Z AUTOTUNE mm(1024x3072, 3072x768) 2025-09-07T10:36:42.6577150Z strides: [3072, 1], [768, 1] 2025-09-07T10:36:42.6577496Z dtypes: torch.float16, torch.float16 2025-09-07T10:36:42.6578268Z triton_mm_65 0.0410 ms 100.0% 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 2025-09-07T10:36:42.6579021Z mm 0.0430 ms 95.2% 2025-09-07T10:36:42.6579709Z triton_mm_61 0.0451 ms 90.9% 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 2025-09-07T10:36:42.6580878Z triton_mm_62 0.0451 ms 90.9% 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 2025-09-07T10:36:42.6582050Z triton_mm_64 0.0471 ms 87.0% 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 2025-09-07T10:36:42.6583215Z triton_mm_67 0.0502 ms 81.6% 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 2025-09-07T10:36:42.6584654Z triton_mm_71 0.0573 ms 71.4% 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 2025-09-07T10:36:42.6585828Z triton_mm_63 0.0584 ms 70.2% 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 2025-09-07T10:36:42.6587001Z triton_mm_58 0.0604 ms 67.8% 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 2025-09-07T10:36:42.6588180Z triton_mm_70 0.0614 ms 66.7% 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 2025-09-07T10:36:42.6589197Z SingleProcess AUTOTUNE benchmarking takes 0.3647 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:36:43.4176361Z Autotune Choices Stats: 2025-09-07T10:36:43.4177903Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.32972800731658936, "best_triton_pos": 1, "best_triton_time": 0.4331519901752472, "best_triton_kernel": "triton_mm_880", "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"} 2025-09-07T10:36:43.4212015Z AUTOTUNE mm(1024x768, 768x50264) 2025-09-07T10:36:43.4212359Z strides: [768, 1], [50304, 1] 2025-09-07T10:36:43.4212665Z dtypes: torch.float16, torch.float16 2025-09-07T10:36:43.4212958Z mm 0.3297 ms 100.0% 2025-09-07T10:36:43.4213670Z triton_mm_880 0.4332 ms 76.1% 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=3, num_warps=4 2025-09-07T10:36:43.4215164Z triton_mm_873 0.4557 ms 72.4% 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 2025-09-07T10:36:43.4216357Z triton_mm_879 0.4618 ms 71.4% 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 2025-09-07T10:36:43.4217616Z triton_mm_875 0.5120 ms 64.4% 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 2025-09-07T10:36:43.4218797Z triton_mm_876 0.5284 ms 62.4% 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 2025-09-07T10:36:43.4219962Z triton_mm_881 0.5315 ms 62.0% 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 2025-09-07T10:36:43.4221160Z triton_mm_874 0.5878 ms 56.1% 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=4, num_warps=8 2025-09-07T10:36:43.4222341Z triton_mm_878 0.6083 ms 54.2% 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=2, num_warps=8 2025-09-07T10:36:43.4223518Z triton_mm_877 0.6205 ms 53.1% 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 2025-09-07T10:36:43.4224530Z SingleProcess AUTOTUNE benchmarking takes 0.7187 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:36:58.2465787Z Autotune Choices Stats: 2025-09-07T10:36:58.2467004Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_898", "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": 0.5713919997215271, "best_triton_pos": 0} 2025-09-07T10:36:58.2504513Z AUTOTUNE mm(50257x1024, 1024x768) 2025-09-07T10:36:58.2504880Z strides: [1, 50257], [768, 1] 2025-09-07T10:36:58.2505180Z dtypes: torch.float16, torch.float16 2025-09-07T10:36:58.2505963Z triton_mm_898 0.5714 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 2025-09-07T10:36:58.2507172Z triton_mm_897 0.6625 ms 86.2% 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 2025-09-07T10:36:58.2508361Z triton_mm_896 0.6707 ms 85.2% 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=2, num_warps=8 2025-09-07T10:36:58.2509547Z triton_mm_891 0.6758 ms 84.5% 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 2025-09-07T10:36:58.2510705Z triton_mm_893 0.7219 ms 79.1% 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 2025-09-07T10:36:58.2511886Z triton_mm_899 0.8079 ms 70.7% 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 2025-09-07T10:36:58.2513060Z triton_mm_894 0.8837 ms 64.7% 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 2025-09-07T10:36:58.2514225Z triton_mm_892 0.8909 ms 64.1% 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=4, num_warps=8 2025-09-07T10:36:58.2519105Z triton_mm_888 0.8919 ms 64.1% 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=2, num_warps=4 2025-09-07T10:36:58.2519842Z mm 0.9329 ms 61.3% 2025-09-07T10:36:58.2520355Z SingleProcess AUTOTUNE benchmarking takes 0.7401 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:36:58.8837828Z Autotune Choices Stats: 2025-09-07T10:36:58.8839328Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.02969600073993206, "best_triton_pos": 1, "best_triton_time": 0.03276799991726875, "best_triton_kernel": "triton_mm_934", "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"} 2025-09-07T10:36:58.8875401Z AUTOTUNE mm(1024x768, 768x3072) 2025-09-07T10:36:58.8875763Z strides: [768, 1], [1, 768] 2025-09-07T10:36:58.8876065Z dtypes: torch.float16, torch.float16 2025-09-07T10:36:58.8876375Z mm 0.0297 ms 100.0% 2025-09-07T10:36:58.8877105Z triton_mm_934 0.0328 ms 90.6% 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=3, num_warps=4 2025-09-07T10:36:58.8878302Z triton_mm_929 0.0348 ms 85.3% 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 2025-09-07T10:36:58.8879468Z triton_mm_933 0.0348 ms 85.3% 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 2025-09-07T10:36:58.8880652Z triton_mm_927 0.0358 ms 82.9% 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 2025-09-07T10:36:58.8881835Z triton_mm_930 0.0358 ms 82.9% 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=3, num_warps=4 2025-09-07T10:36:58.8883585Z triton_mm_935 0.0358 ms 82.9% 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 2025-09-07T10:36:58.8884777Z triton_mm_928 0.0410 ms 72.5% 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 2025-09-07T10:36:58.8885950Z triton_mm_931 0.0410 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 2025-09-07T10:36:58.8887135Z triton_mm_932 0.0410 ms 72.5% 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=2, num_warps=8 2025-09-07T10:36:58.8888156Z SingleProcess AUTOTUNE benchmarking takes 0.3252 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:37:00.3460510Z Autotune Choices Stats: 2025-09-07T10:37:00.3462026Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03481600061058998, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "best_triton_kernel": "triton_mm_947", "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"} 2025-09-07T10:37:00.3499911Z AUTOTUNE mm(3072x1024, 1024x768) 2025-09-07T10:37:00.3500226Z strides: [1, 3072], [768, 1] 2025-09-07T10:37:00.3500572Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:00.3500877Z mm 0.0348 ms 100.0% 2025-09-07T10:37:00.3501576Z triton_mm_947 0.0348 ms 100.0% 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 2025-09-07T10:37:00.3503189Z triton_mm_945 0.0358 ms 97.1% 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 2025-09-07T10:37:00.3504384Z triton_mm_948 0.0358 ms 97.1% 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=3, num_warps=4 2025-09-07T10:37:00.3505557Z triton_mm_949 0.0379 ms 91.9% 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 2025-09-07T10:37:00.3506736Z triton_mm_946 0.0389 ms 89.5% 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 2025-09-07T10:37:00.3507916Z triton_mm_952 0.0399 ms 87.2% 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 2025-09-07T10:37:00.3509105Z triton_mm_951 0.0410 ms 85.0% 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 2025-09-07T10:37:00.3510280Z triton_mm_953 0.0420 ms 82.9% 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 2025-09-07T10:37:00.3511451Z triton_mm_943 0.0461 ms 75.6% 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 2025-09-07T10:37:00.3512460Z SingleProcess AUTOTUNE benchmarking takes 0.3244 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:37:00.6901542Z Autotune Choices Stats: 2025-09-07T10:37:00.6902711Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_983", "best_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", "best_time": 0.03379200026392937, "best_triton_pos": 0} 2025-09-07T10:37:00.6938915Z AUTOTUNE mm(768x1024, 1024x3072) 2025-09-07T10:37:00.6939613Z strides: [1, 768], [3072, 1] 2025-09-07T10:37:00.6939917Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:00.6940690Z triton_mm_983 0.0338 ms 100.0% 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 2025-09-07T10:37:00.6941442Z mm 0.0348 ms 97.1% 2025-09-07T10:37:00.6942113Z triton_mm_981 0.0348 ms 97.1% 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 2025-09-07T10:37:00.6943282Z triton_mm_984 0.0379 ms 89.2% 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=3, num_warps=4 2025-09-07T10:37:00.6944467Z triton_mm_982 0.0389 ms 86.8% 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 2025-09-07T10:37:00.6945639Z triton_mm_985 0.0389 ms 86.8% 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 2025-09-07T10:37:00.6946811Z triton_mm_988 0.0399 ms 84.6% 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=3, num_warps=4 2025-09-07T10:37:00.6947998Z triton_mm_987 0.0410 ms 82.5% 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 2025-09-07T10:37:00.6949180Z triton_mm_989 0.0420 ms 80.5% 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 2025-09-07T10:37:00.6950524Z triton_mm_979 0.0461 ms 73.3% 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 2025-09-07T10:37:00.6951540Z SingleProcess AUTOTUNE benchmarking takes 0.3193 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:37:01.2701863Z Autotune Choices Stats: 2025-09-07T10:37:01.2703367Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.023552000522613525, "best_triton_pos": 1, "best_triton_time": 0.02457600086927414, "best_triton_kernel": "triton_mm_1061", "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"} 2025-09-07T10:37:01.2741500Z AUTOTUNE mm(768x1024, 1024x2304) 2025-09-07T10:37:01.2741863Z strides: [1, 768], [2304, 1] 2025-09-07T10:37:01.2742194Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:01.2742500Z mm 0.0236 ms 100.0% 2025-09-07T10:37:01.2743227Z triton_mm_1061 0.0246 ms 95.8% 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 2025-09-07T10:37:01.2744436Z triton_mm_1060 0.0256 ms 92.0% 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 2025-09-07T10:37:01.2745626Z triton_mm_1055 0.0266 ms 88.5% 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 2025-09-07T10:37:01.2746808Z triton_mm_1053 0.0287 ms 82.1% 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 2025-09-07T10:37:01.2747996Z triton_mm_1059 0.0287 ms 82.1% 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 2025-09-07T10:37:01.2749520Z triton_mm_1054 0.0297 ms 79.3% 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 2025-09-07T10:37:01.2750722Z triton_mm_1057 0.0297 ms 79.3% 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 2025-09-07T10:37:01.2751903Z triton_mm_1056 0.0307 ms 76.7% 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 2025-09-07T10:37:01.2753086Z triton_mm_1051 0.0338 ms 69.7% 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 2025-09-07T10:37:01.2754112Z SingleProcess AUTOTUNE benchmarking takes 0.3012 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:37:01.8891551Z Autotune Choices Stats: 2025-09-07T10:37:01.8894348Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "best_triton_kernel": "triton_mm_1019", "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"} 2025-09-07T10:37:01.8931194Z AUTOTUNE mm(768x1024, 1024x768) 2025-09-07T10:37:01.8931732Z strides: [1, 768], [768, 1] 2025-09-07T10:37:01.8932268Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:01.8932805Z mm 0.0164 ms 100.0% 2025-09-07T10:37:01.8934117Z triton_mm_1019 0.0195 ms 84.2% 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 2025-09-07T10:37:01.8936868Z triton_mm_1015 0.0205 ms 80.0% 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 2025-09-07T10:37:01.8939267Z triton_mm_1016 0.0205 ms 80.0% 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 2025-09-07T10:37:01.8941550Z triton_mm_1018 0.0205 ms 80.0% 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 2025-09-07T10:37:01.8943838Z triton_mm_1021 0.0205 ms 80.0% 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=4, num_warps=8 2025-09-07T10:37:01.8946128Z triton_mm_1017 0.0246 ms 66.7% 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 2025-09-07T10:37:01.8948373Z triton_mm_1020 0.0246 ms 66.7% 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 2025-09-07T10:37:01.8950654Z triton_mm_1025 0.0246 ms 66.7% 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 2025-09-07T10:37:01.8952845Z triton_mm_1024 0.0256 ms 64.0% 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 2025-09-07T10:37:01.8954690Z SingleProcess AUTOTUNE benchmarking takes 0.2737 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:37:04.6537141Z Autotune Choices Stats: 2025-09-07T10:37:04.6540098Z {"num_choices": 22, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.3123199939727783, "best_triton_pos": 1, "best_triton_time": 0.5539839863777161, "best_triton_kernel": "triton_mm_911", "best_triton_kernel_desc": "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"} 2025-09-07T10:37:04.6586905Z AUTOTUNE mm(1024x50264, 50264x768) 2025-09-07T10:37:04.6587495Z strides: [50304, 1], [768, 1] 2025-09-07T10:37:04.6588045Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:04.6588590Z mm 0.3123 ms 100.0% 2025-09-07T10:37:04.6589923Z triton_mm_911 0.5540 ms 56.4% 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 2025-09-07T10:37:04.6592226Z triton_mm_907 0.6093 ms 51.3% 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 2025-09-07T10:37:04.6594558Z triton_mm_910 0.6584 ms 47.4% 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 2025-09-07T10:37:04.6596924Z triton_mm_913 0.6717 ms 46.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:37:04.6599263Z triton_mm_908 0.7741 ms 40.3% 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 2025-09-07T10:37:04.6601607Z triton_mm_916 0.8335 ms 37.5% 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 2025-09-07T10:37:04.6604265Z triton_mm_917 0.8428 ms 37.1% 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 2025-09-07T10:37:04.6606610Z triton_mm_912 0.8837 ms 35.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:37:04.6609267Z triton_mm_904 0.9134 ms 34.2% 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 2025-09-07T10:37:04.6611246Z SingleProcess AUTOTUNE benchmarking takes 1.2807 seconds and 0.0002 seconds precompiling for 22 choices 2025-09-07T10:37:05.5777042Z Autotune Choices Stats: 2025-09-07T10:37:05.5779368Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03379200026392937, "best_triton_pos": 1, "best_triton_time": 0.04198399931192398, "best_triton_kernel": "triton_mm_965", "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"} 2025-09-07T10:37:05.5821568Z AUTOTUNE mm(1024x3072, 3072x768) 2025-09-07T10:37:05.5822046Z strides: [3072, 1], [1, 3072] 2025-09-07T10:37:05.5822443Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:05.5822832Z mm 0.0338 ms 100.0% 2025-09-07T10:37:05.5823804Z triton_mm_965 0.0420 ms 80.5% 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 2025-09-07T10:37:05.5825417Z triton_mm_962 0.0440 ms 76.7% 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 2025-09-07T10:37:05.5827035Z triton_mm_961 0.0461 ms 73.3% 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 2025-09-07T10:37:05.5828821Z triton_mm_964 0.0461 ms 73.3% 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 2025-09-07T10:37:05.5830637Z triton_mm_967 0.0481 ms 70.2% 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 2025-09-07T10:37:05.5832839Z triton_mm_970 0.0584 ms 57.9% 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=3, num_warps=4 2025-09-07T10:37:05.5834724Z triton_mm_966 0.0625 ms 54.1% 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=3, num_warps=4 2025-09-07T10:37:05.5836565Z triton_mm_971 0.0625 ms 54.1% 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 2025-09-07T10:37:05.5838395Z triton_mm_963 0.0635 ms 53.2% 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 2025-09-07T10:37:05.5840002Z SingleProcess AUTOTUNE benchmarking takes 0.9218 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:37:05.8457953Z Autotune Choices Stats: 2025-09-07T10:37:05.8460169Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.016383999958634377, "best_triton_kernel": "triton_mm_1001", "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"} 2025-09-07T10:37:05.8502406Z AUTOTUNE mm(1024x768, 768x768) 2025-09-07T10:37:05.8502885Z strides: [768, 1], [1, 768] 2025-09-07T10:37:05.8503326Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:05.8503754Z mm 0.0164 ms 100.0% 2025-09-07T10:37:05.8504832Z triton_mm_1001 0.0164 ms 100.0% 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 2025-09-07T10:37:05.8507129Z triton_mm_997 0.0174 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=3, num_warps=8 2025-09-07T10:37:05.8508994Z triton_mm_1000 0.0174 ms 94.1% 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=4, num_warps=8 2025-09-07T10:37:05.8510812Z triton_mm_1003 0.0174 ms 94.1% 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 2025-09-07T10:37:05.8512660Z triton_mm_1007 0.0195 ms 84.2% 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=5, num_warps=8 2025-09-07T10:37:05.8514505Z triton_mm_998 0.0205 ms 80.0% 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 2025-09-07T10:37:05.8516331Z triton_mm_999 0.0205 ms 80.0% 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 2025-09-07T10:37:05.8518187Z triton_mm_1002 0.0205 ms 80.0% 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 2025-09-07T10:37:05.8520030Z triton_mm_1006 0.0215 ms 76.2% 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 2025-09-07T10:37:05.8521579Z SingleProcess AUTOTUNE benchmarking takes 0.2668 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:37:06.1733344Z Autotune Choices Stats: 2025-09-07T10:37:06.1735675Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.03379200026392937, "best_triton_kernel": "triton_mm_1037", "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"} 2025-09-07T10:37:06.1778806Z AUTOTUNE mm(1024x2304, 2304x768) 2025-09-07T10:37:06.1779360Z strides: [2304, 1], [1, 2304] 2025-09-07T10:37:06.1779824Z dtypes: torch.float16, torch.float16 2025-09-07T10:37:06.1780313Z mm 0.0276 ms 100.0% 2025-09-07T10:37:06.1781540Z triton_mm_1037 0.0338 ms 81.8% 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 2025-09-07T10:37:06.1783548Z triton_mm_1033 0.0358 ms 77.1% 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 2025-09-07T10:37:06.1785370Z triton_mm_1034 0.0358 ms 77.1% 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 2025-09-07T10:37:06.1787231Z triton_mm_1036 0.0369 ms 75.0% 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 2025-09-07T10:37:06.1789247Z triton_mm_1039 0.0379 ms 73.0% 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=4, num_warps=8 2025-09-07T10:37:06.1791077Z triton_mm_1042 0.0461 ms 60.0% 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 2025-09-07T10:37:06.1792871Z triton_mm_1030 0.0492 ms 56.2% 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 2025-09-07T10:37:06.1794667Z triton_mm_1035 0.0492 ms 56.2% 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 2025-09-07T10:37:06.1797146Z triton_mm_1038 0.0492 ms 56.2% 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=3, num_warps=4 2025-09-07T10:37:06.1798575Z SingleProcess AUTOTUNE benchmarking takes 0.3264 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:37:10.0213254Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 1183, in forward 2025-09-07T10:37:10.0214475Z transformer_outputs = self.transformer( 2025-09-07T10:37:10.0215171Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 860, in forward 2025-09-07T10:37:10.0215914Z position_embeds = self.wpe(position_ids) 2025-09-07T10:37:10.0216156Z 2025-09-07T10:37:10.0216161Z 2025-09-07T10:37:11.2131536Z W0907 10:37:11.212000 35139 site-packages/torch/_logging/_internal.py:1199] [11/0] Profiler function will be ignored 2025-09-07T10:37:32.2348960Z pass 2025-09-07T10:37:37.4865108Z /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. 2025-09-07T10:37:37.4866522Z import pynvml # type: ignore[import] 2025-09-07T10:37:40.2492938Z 2025-09-07T10:37:57.2500892Z loading model: 0it [00:00, ?it/s]`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:37:57.2501978Z WARNING:transformers.modeling_utils:`loss_type=None` was set in the config but it is unrecognised.Using the default loss: `ForCausalLMLoss`. 2025-09-07T10:37:57.4429523Z 2025-09-07T10:37:57.4429865Z loading model: 0it [00:17, ?it/s] 2025-09-07T10:37:57.4430237Z cuda train hf_GPT2_large 2025-09-07T10:37:57.4833041Z pass_due_to_skip 2025-09-07T10:37:59.6753495Z /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. 2025-09-07T10:37:59.6754902Z import pynvml # type: ignore[import] 2025-09-07T10:38:02.5093855Z 2025-09-07T10:38:08.0162209Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:38:08.0162608Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:38:08.0163207Z cuda train hf_Longformer 2025-09-07T10:38:11.4398225Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T10:38:11.4399384Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T10:38:11.4400287Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] or: 2025-09-07T10:38:11.4401129Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T10:38:11.4402143Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] to include these operations in the captured graph. 2025-09-07T10:38:11.4403198Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T10:38:11.4403986Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] Graph break: from user code at: 2025-09-07T10:38:11.4405368Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:38:11.4407278Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] pred = mod(**cloned_inputs) 2025-09-07T10:38:11.4408668Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1703, in forward 2025-09-07T10:38:11.4410061Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] outputs = self.longformer( 2025-09-07T10:38:11.4411434Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1600, in forward 2025-09-07T10:38:11.4412803Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] encoder_outputs = self.encoder( 2025-09-07T10:38:11.4414206Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1244, in forward 2025-09-07T10:38:11.4415684Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] is_global_attn = is_index_global_attn.flatten().any().item() 2025-09-07T10:38:11.4416571Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T10:38:11.4417272Z W0907 10:38:11.439000 38947 site-packages/torch/_dynamo/variables/tensor.py:1048] [2/0] 2025-09-07T10:38:58.0151771Z Autotune Choices Stats: 2025-09-07T10:38:58.0152973Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_63", "best_kernel_desc": "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", "best_time": 0.0798719972372055, "best_triton_pos": 0} 2025-09-07T10:38:58.0192268Z AUTOTUNE bmm(144x512x64, 144x64x512) 2025-09-07T10:38:58.0192609Z strides: [32768, 64, 1], [32768, 512, 1] 2025-09-07T10:38:58.0193323Z dtypes: torch.float16, torch.float16 2025-09-07T10:38:58.0194094Z triton_bmm_63 0.0799 ms 100.0% 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 2025-09-07T10:38:58.0195293Z triton_bmm_61 0.0809 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=3, num_warps=8 2025-09-07T10:38:58.0196456Z triton_bmm_65 0.0809 ms 98.7% 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 2025-09-07T10:38:58.0197630Z triton_bmm_66 0.0809 ms 98.7% 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=4, num_warps=4 2025-09-07T10:38:58.0198818Z triton_bmm_67 0.0809 ms 98.7% 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 2025-09-07T10:38:58.0199993Z triton_bmm_70 0.0809 ms 98.7% 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 2025-09-07T10:38:58.0201178Z triton_bmm_71 0.0809 ms 98.7% 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 2025-09-07T10:38:58.0202352Z triton_bmm_72 0.0809 ms 98.7% 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 2025-09-07T10:38:58.0203520Z bmm 0.0819 ms 97.5% 2025-09-07T10:38:58.0204218Z triton_bmm_62 0.0819 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=5, num_warps=4 2025-09-07T10:38:58.0205241Z SingleProcess AUTOTUNE benchmarking takes 0.4340 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:38:58.4939321Z Autotune Choices Stats: 2025-09-07T10:38:58.4940534Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_81", "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": 0.10956799983978271, "best_triton_pos": 0} 2025-09-07T10:38:58.4980188Z AUTOTUNE bmm(192x256x768, 192x768x64) 2025-09-07T10:38:58.4980542Z strides: [197120, 769, 1], [49152, 64, 1] 2025-09-07T10:38:58.4980875Z dtypes: torch.float16, torch.float16 2025-09-07T10:38:58.4981640Z triton_bmm_81 0.1096 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 2025-09-07T10:38:58.4982863Z triton_bmm_85 0.1096 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=4, num_warps=4 2025-09-07T10:38:58.4984060Z triton_bmm_90 0.1137 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 2025-09-07T10:38:58.4985243Z triton_bmm_79 0.1229 ms 89.2% 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 2025-09-07T10:38:58.4986412Z triton_bmm_82 0.1239 ms 88.4% 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=3, num_warps=4 2025-09-07T10:38:58.4987587Z triton_bmm_84 0.1249 ms 87.7% 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=4 2025-09-07T10:38:58.4989099Z triton_bmm_88 0.1249 ms 87.7% 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=2, num_warps=8 2025-09-07T10:38:58.4990283Z triton_bmm_80 0.1280 ms 85.6% 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 2025-09-07T10:38:58.4991442Z triton_bmm_89 0.1321 ms 82.9% 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=3, num_warps=4 2025-09-07T10:38:58.4992614Z triton_bmm_83 0.1331 ms 82.3% 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=4, num_warps=8 2025-09-07T10:38:58.4993637Z SingleProcess AUTOTUNE benchmarking takes 0.4782 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:39:12.2146296Z Autotune Choices Stats: 2025-09-07T10:39:12.2147844Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 1.334272027015686, "best_triton_pos": 1, "best_triton_time": 1.743872046470642, "best_triton_kernel": "triton_mm_1773", "best_triton_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"} 2025-09-07T10:39:12.2189448Z AUTOTUNE addmm(4096x50272, 4096x768, 768x50272) 2025-09-07T10:39:12.2189810Z strides: [0, 1], [768, 1], [50304, 1] 2025-09-07T10:39:12.2190154Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:39:12.2190525Z bias_addmm 1.3343 ms 100.0% 2025-09-07T10:39:12.2191282Z triton_mm_1773 1.7439 ms 76.5% 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 2025-09-07T10:39:12.2192845Z triton_mm_1774 1.8760 ms 71.1% 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=3, num_warps=4 2025-09-07T10:39:12.2194037Z triton_mm_1767 1.9476 ms 68.5% 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 2025-09-07T10:39:12.2194784Z addmm 2.0890 ms 63.9% 2025-09-07T10:39:12.2195470Z triton_mm_1770 2.0951 ms 63.7% 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 2025-09-07T10:39:12.2196658Z triton_mm_1775 2.2026 ms 60.6% 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 2025-09-07T10:39:12.2197845Z triton_mm_1769 2.2180 ms 60.2% 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 2025-09-07T10:39:12.2199030Z triton_mm_1768 2.4228 ms 55.1% 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=4, num_warps=8 2025-09-07T10:39:12.2200215Z triton_mm_1771 2.5436 ms 52.5% 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 2025-09-07T10:39:12.2201236Z SingleProcess AUTOTUNE benchmarking takes 1.0246 seconds and 0.9311 seconds precompiling for 20 choices 2025-09-07T10:39:16.9593690Z Autotune Choices Stats: 2025-09-07T10:39:16.9595185Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 1.1048959493637085, "best_triton_pos": 1, "best_triton_time": 2.1626880168914795, "best_triton_kernel": "triton_mm_1810", "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"} 2025-09-07T10:39:16.9674174Z AUTOTUNE mm(50265x4096, 4096x768) 2025-09-07T10:39:16.9674925Z strides: [1, 50304], [768, 1] 2025-09-07T10:39:16.9675234Z dtypes: torch.float16, torch.float16 2025-09-07T10:39:16.9675526Z mm 1.1049 ms 100.0% 2025-09-07T10:39:16.9676251Z triton_mm_1810 2.1627 ms 51.1% 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=3, num_warps=4 2025-09-07T10:39:16.9677462Z triton_mm_1808 2.4484 ms 45.1% 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=2, num_warps=8 2025-09-07T10:39:16.9678651Z triton_mm_1803 2.4740 ms 44.7% 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 2025-09-07T10:39:16.9679849Z triton_mm_1809 2.5549 ms 43.2% 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 2025-09-07T10:39:16.9681037Z triton_mm_1805 2.7259 ms 40.5% 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 2025-09-07T10:39:16.9682221Z triton_mm_1811 3.1969 ms 34.6% 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 2025-09-07T10:39:16.9683646Z triton_mm_1800 3.3167 ms 33.3% 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=2, num_warps=4 2025-09-07T10:39:16.9684831Z triton_mm_1806 3.3311 ms 33.2% 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=3, num_warps=4 2025-09-07T10:39:16.9686189Z triton_mm_1804 3.5072 ms 31.5% 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 2025-09-07T10:39:16.9687209Z SingleProcess AUTOTUNE benchmarking takes 1.0518 seconds and 0.2133 seconds precompiling for 19 choices 2025-09-07T10:39:19.4646250Z Autotune Choices Stats: 2025-09-07T10:39:19.4647750Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 1.2769279479980469, "best_triton_pos": 1, "best_triton_time": 1.7469439506530762, "best_triton_kernel": "triton_mm_1791", "best_triton_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"} 2025-09-07T10:39:19.4689918Z AUTOTUNE mm(4096x50272, 50272x768) 2025-09-07T10:39:19.4690283Z strides: [50304, 1], [768, 1] 2025-09-07T10:39:19.4690631Z dtypes: torch.float16, torch.float16 2025-09-07T10:39:19.4690924Z mm 1.2769 ms 100.0% 2025-09-07T10:39:19.4691655Z triton_mm_1791 1.7469 ms 73.1% 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 2025-09-07T10:39:19.4692870Z triton_mm_1792 1.8115 ms 70.5% 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 2025-09-07T10:39:19.4694058Z triton_mm_1785 1.9876 ms 64.2% 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 2025-09-07T10:39:19.4695316Z triton_mm_1793 2.1115 ms 60.5% 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 2025-09-07T10:39:19.4696517Z triton_mm_1787 2.1125 ms 60.4% 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 2025-09-07T10:39:19.4698180Z triton_mm_1790 2.1586 ms 59.2% 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=2, num_warps=8 2025-09-07T10:39:19.4699370Z triton_mm_1783 2.5733 ms 49.6% 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 2025-09-07T10:39:19.4700557Z triton_mm_1786 2.5733 ms 49.6% 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 2025-09-07T10:39:19.4701738Z triton_mm_1788 2.6204 ms 48.7% 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 2025-09-07T10:39:19.4702763Z SingleProcess AUTOTUNE benchmarking takes 0.9982 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:39:44.6382000Z Autotune Choices Stats: 2025-09-07T10:39:44.6383256Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_1962", "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=2, num_warps=4", "best_time": 0.10751999914646149, "best_triton_pos": 0} 2025-09-07T10:39:44.6426419Z AUTOTUNE bmm(192x768x256, 192x256x64) 2025-09-07T10:39:44.6426767Z strides: [197120, 1, 769], [16384, 64, 1] 2025-09-07T10:39:44.6427083Z dtypes: torch.float16, torch.float16 2025-09-07T10:39:44.6427851Z triton_bmm_1962 0.1075 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=2, num_warps=4 2025-09-07T10:39:44.6429063Z triton_bmm_1969 0.1085 ms 99.1% 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=3, num_warps=4 2025-09-07T10:39:44.6430647Z triton_bmm_1970 0.1106 ms 97.2% 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 2025-09-07T10:39:44.6431840Z triton_bmm_1971 0.1106 ms 97.2% 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 2025-09-07T10:39:44.6433030Z triton_bmm_1965 0.1147 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=3, num_warps=4 2025-09-07T10:39:44.6434212Z triton_bmm_1966 0.1157 ms 92.9% 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 2025-09-07T10:39:44.6435386Z triton_bmm_1972 0.1157 ms 92.9% 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=3, num_warps=4 2025-09-07T10:39:44.6436579Z triton_bmm_1961 0.1167 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:39:44.6437761Z triton_bmm_1967 0.1198 ms 89.7% 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=4 2025-09-07T10:39:44.6438937Z triton_bmm_1958 0.1208 ms 89.0% 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 2025-09-07T10:39:44.6439964Z SingleProcess AUTOTUNE benchmarking takes 0.4646 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:39:45.0779647Z Autotune Choices Stats: 2025-09-07T10:39:45.0780811Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_1981", "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": 0.08499199897050858, "best_triton_pos": 0} 2025-09-07T10:39:45.0824175Z AUTOTUNE bmm(192x256x64, 192x64x768) 2025-09-07T10:39:45.0824574Z strides: [16384, 64, 1], [49152, 1, 64] 2025-09-07T10:39:45.0824893Z dtypes: torch.float16, torch.float16 2025-09-07T10:39:45.0825661Z triton_bmm_1981 0.0850 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 2025-09-07T10:39:45.0826875Z triton_bmm_1983 0.0850 ms 100.0% 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 2025-09-07T10:39:45.0828078Z triton_bmm_1984 0.0850 ms 100.0% 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 2025-09-07T10:39:45.0829310Z triton_bmm_1985 0.0850 ms 100.0% 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 2025-09-07T10:39:45.0830499Z triton_bmm_1982 0.0860 ms 98.8% 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 2025-09-07T10:39:45.0831689Z triton_bmm_1986 0.0860 ms 98.8% 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 2025-09-07T10:39:45.0832889Z triton_bmm_1987 0.0860 ms 98.8% 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 2025-09-07T10:39:45.0834088Z triton_bmm_1988 0.0860 ms 98.8% 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 2025-09-07T10:39:45.0835436Z triton_bmm_1990 0.0860 ms 98.8% 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 2025-09-07T10:39:45.0836648Z triton_bmm_1991 0.0860 ms 98.8% 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 2025-09-07T10:39:45.0837686Z SingleProcess AUTOTUNE benchmarking takes 0.4378 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:39:45.4394038Z Autotune Choices Stats: 2025-09-07T10:39:45.4395243Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_2004", "best_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", "best_time": 0.08806400001049042, "best_triton_pos": 0} 2025-09-07T10:39:45.4438276Z AUTOTUNE bmm(144x64x512, 144x512x512) 2025-09-07T10:39:45.4438627Z strides: [32768, 1, 64], [262144, 512, 1] 2025-09-07T10:39:45.4438947Z dtypes: torch.float16, torch.float16 2025-09-07T10:39:45.4439741Z triton_bmm_2004 0.0881 ms 100.0% 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 2025-09-07T10:39:45.4440956Z triton_bmm_2000 0.0891 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 2025-09-07T10:39:45.4442155Z triton_bmm_2002 0.0891 ms 98.9% 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 2025-09-07T10:39:45.4443555Z triton_bmm_2003 0.0891 ms 98.9% 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=4, num_warps=8 2025-09-07T10:39:45.4448297Z triton_bmm_2006 0.0901 ms 97.7% 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 2025-09-07T10:39:45.4449162Z bmm 0.0911 ms 96.6% 2025-09-07T10:39:45.4449846Z triton_bmm_1999 0.0911 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 2025-09-07T10:39:45.4451050Z triton_bmm_2008 0.0911 ms 96.6% 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=5, num_warps=8 2025-09-07T10:39:45.4452247Z triton_bmm_2001 0.0922 ms 95.6% 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 2025-09-07T10:39:45.4453446Z triton_bmm_2005 0.0932 ms 94.5% 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 2025-09-07T10:39:45.4454470Z SingleProcess AUTOTUNE benchmarking takes 0.3608 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T10:39:45.8763536Z Autotune Choices Stats: 2025-09-07T10:39:45.8764744Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_2020", "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": 0.08806400001049042, "best_triton_pos": 0} 2025-09-07T10:39:45.8809644Z AUTOTUNE bmm(144x512x512, 144x512x64) 2025-09-07T10:39:45.8809994Z strides: [262144, 512, 1], [32768, 1, 512] 2025-09-07T10:39:45.8810314Z dtypes: torch.float16, torch.float16 2025-09-07T10:39:45.8811087Z triton_bmm_2020 0.0881 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 2025-09-07T10:39:45.8812628Z triton_bmm_2025 0.0901 ms 97.7% 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=3, num_warps=4 2025-09-07T10:39:45.8813380Z bmm 0.0911 ms 96.6% 2025-09-07T10:39:45.8814071Z triton_bmm_2016 0.0911 ms 96.6% 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 2025-09-07T10:39:45.8815242Z triton_bmm_2017 0.0911 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=5, num_warps=4 2025-09-07T10:39:45.8816440Z triton_bmm_2021 0.0911 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 2025-09-07T10:39:45.8817703Z triton_bmm_2026 0.0911 ms 96.6% 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 2025-09-07T10:39:45.8818904Z triton_bmm_2010 0.0942 ms 93.5% 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 2025-09-07T10:39:45.8820112Z triton_bmm_2013 0.1055 ms 83.5% 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 2025-09-07T10:39:45.8821303Z triton_bmm_2019 0.1096 ms 80.4% 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 2025-09-07T10:39:45.8822326Z SingleProcess AUTOTUNE benchmarking takes 0.4352 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:39:57.1863985Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1259, in torch_dynamo_resume_in_forward_at_1244 2025-09-07T10:39:57.1865792Z layer_outputs = layer_module( 2025-09-07T10:39:57.1866421Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T10:39:57.1867067Z return super().__call__(*args, **kwargs) 2025-09-07T10:39:57.1867835Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1199, in forward 2025-09-07T10:39:57.1868615Z self_attn_outputs = self.attention( 2025-09-07T10:39:57.1869373Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1135, in forward 2025-09-07T10:39:57.1870128Z self_outputs = self.self( 2025-09-07T10:39:57.1870830Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 613, in forward 2025-09-07T10:39:57.1871673Z attn_output = self._sliding_chunks_matmul_attn_probs_value( 2025-09-07T10:39:57.1872648Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 874, in _sliding_chunks_matmul_attn_probs_value 2025-09-07T10:39:57.1873752Z chunked_value = padded_value.as_strided(size=chunked_value_size, stride=chunked_value_stride) 2025-09-07T10:39:57.1874182Z 2025-09-07T10:39:57.1874187Z 2025-09-07T10:39:59.1630323Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1596, in forward 2025-09-07T10:39:59.1631684Z embedding_output = self.embeddings( 2025-09-07T10:39:59.1632452Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 425, in forward 2025-09-07T10:39:59.1639349Z token_type_embeddings = self.token_type_embeddings(token_type_ids) 2025-09-07T10:39:59.1639684Z 2025-09-07T10:39:59.1639690Z 2025-09-07T10:39:59.2661569Z W0907 10:39:59.265000 38947 site-packages/torch/_logging/_internal.py:1199] [19/0] Profiler function will be ignored 2025-09-07T10:40:29.5160124Z pass 2025-09-07T10:40:35.9022536Z /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. 2025-09-07T10:40:35.9023949Z import pynvml # type: ignore[import] 2025-09-07T10:40:38.6079374Z 2025-09-07T10:40:40.7269709Z loading model: 0it [00:00, ?it/s]Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T10:40:40.7272024Z WARNING:transformers.models.reformer.modeling_reformer:Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T10:40:41.5471408Z 2025-09-07T10:40:41.5471862Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:40:41.5472248Z cuda train hf_Reformer 2025-09-07T10:40:47.1275218Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:40:47.1276904Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2095, in forward 2025-09-07T10:40:47.1278690Z least_common_mult_chunk_length = _get_least_common_mult_chunk_len(self.config) 2025-09-07T10:40:47.1280725Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 194, in _get_least_common_mult_chunk_len 2025-09-07T10:40:47.1283619Z return np.lcm(config.lsh_attn_chunk_length, config.local_attn_chunk_length) 2025-09-07T10:40:47.1284424Z 2025-09-07T10:40:47.1284760Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:40:47.1286354Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2099, in forward 2025-09-07T10:40:47.1287956Z input_shape[-1] % least_common_mult_chunk_length != 0 2025-09-07T10:40:47.1288504Z 2025-09-07T10:40:57.0114901Z Autotune Choices Stats: 2025-09-07T10:40:57.0116096Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_97", "best_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", "best_time": 0.04710400104522705, "best_triton_pos": 0} 2025-09-07T10:40:57.0160986Z AUTOTUNE mm(16384x768, 768x256) 2025-09-07T10:40:57.0161285Z strides: [768, 1], [1, 768] 2025-09-07T10:40:57.0161581Z dtypes: torch.float16, torch.float16 2025-09-07T10:40:57.0162359Z triton_mm_97 0.0471 ms 100.0% 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 2025-09-07T10:40:57.0163777Z triton_mm_102 0.0512 ms 92.0% 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 2025-09-07T10:40:57.0164514Z mm 0.0543 ms 86.8% 2025-09-07T10:40:57.0165206Z triton_mm_103 0.0543 ms 86.8% 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 2025-09-07T10:40:57.0166378Z triton_mm_96 0.0573 ms 82.1% 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=4, num_warps=8 2025-09-07T10:40:57.0167956Z triton_mm_95 0.0584 ms 80.7% 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 2025-09-07T10:40:57.0169132Z triton_mm_99 0.0584 ms 80.7% 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 2025-09-07T10:40:57.0170294Z triton_mm_93 0.0594 ms 79.3% 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 2025-09-07T10:40:57.0171461Z triton_mm_98 0.0594 ms 79.3% 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 2025-09-07T10:40:57.0172627Z triton_mm_101 0.0635 ms 74.2% 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 2025-09-07T10:40:57.0173653Z SingleProcess AUTOTUNE benchmarking takes 0.3686 seconds and 1.5490 seconds precompiling for 19 choices 2025-09-07T10:40:58.1400989Z Autotune Choices Stats: 2025-09-07T10:40:58.1402507Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.04710400104522705, "best_triton_pos": 1, "best_triton_time": 0.048128001391887665, "best_triton_kernel": "triton_mm_15", "best_triton_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"} 2025-09-07T10:40:58.1447279Z AUTOTUNE mm(16384x256, 256x768) 2025-09-07T10:40:58.1447639Z strides: [256, 1], [1, 256] 2025-09-07T10:40:58.1447931Z dtypes: torch.float16, torch.float16 2025-09-07T10:40:58.1448222Z mm 0.0471 ms 100.0% 2025-09-07T10:40:58.1448913Z triton_mm_15 0.0481 ms 97.9% 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 2025-09-07T10:40:58.1450457Z triton_mm_16 0.0481 ms 97.9% 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=3, num_warps=4 2025-09-07T10:40:58.1451650Z triton_mm_9 0.0492 ms 95.8% 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=3, num_warps=4 2025-09-07T10:40:58.1452819Z triton_mm_11 0.0492 ms 95.8% 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 2025-09-07T10:40:58.1453990Z triton_mm_12 0.0492 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=3, num_warps=4 2025-09-07T10:40:58.1455150Z triton_mm_10 0.0563 ms 83.6% 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 2025-09-07T10:40:58.1456323Z triton_mm_13 0.0573 ms 82.1% 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 2025-09-07T10:40:58.1457556Z triton_mm_17 0.0584 ms 80.7% 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 2025-09-07T10:40:58.1458736Z triton_mm_14 0.0594 ms 79.3% 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=2, num_warps=8 2025-09-07T10:40:58.1459764Z SingleProcess AUTOTUNE benchmarking takes 0.3817 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:40:58.5458180Z Autotune Choices Stats: 2025-09-07T10:40:58.5459641Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_47", "best_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", "best_time": 0.09932799637317657, "best_triton_pos": 0} 2025-09-07T10:40:58.5504169Z AUTOTUNE bmm(3072x64x64, 3072x64x128) 2025-09-07T10:40:58.5504540Z strides: [4096, 64, 1], [8192, 1, 64] 2025-09-07T10:40:58.5504858Z dtypes: torch.float16, torch.float16 2025-09-07T10:40:58.5505618Z triton_bmm_47 0.0993 ms 100.0% 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 2025-09-07T10:40:58.5506825Z triton_bmm_48 0.0993 ms 100.0% 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=4, num_warps=4 2025-09-07T10:40:58.5508005Z triton_bmm_43 0.1004 ms 99.0% 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 2025-09-07T10:40:58.5509196Z triton_bmm_44 0.1004 ms 99.0% 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 2025-09-07T10:40:58.5510367Z triton_bmm_52 0.1004 ms 99.0% 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=5, num_warps=8 2025-09-07T10:40:58.5511537Z triton_bmm_40 0.1034 ms 96.0% 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 2025-09-07T10:40:58.5512677Z triton_bmm_49 0.1034 ms 96.0% 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 2025-09-07T10:40:58.5513839Z triton_bmm_42 0.1044 ms 95.1% 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=2, num_warps=4 2025-09-07T10:40:58.5515310Z triton_bmm_45 0.1044 ms 95.1% 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 2025-09-07T10:40:58.5516498Z triton_bmm_46 0.1044 ms 95.1% 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=4, num_warps=8 2025-09-07T10:40:58.5517521Z SingleProcess AUTOTUNE benchmarking takes 0.4032 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:40:58.9136033Z Autotune Choices Stats: 2025-09-07T10:40:58.9137254Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_83", "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=4, num_warps=4", "best_time": 0.10751999914646149, "best_triton_pos": 0} 2025-09-07T10:40:58.9182930Z AUTOTUNE bmm(3072x64x128, 3072x128x64) 2025-09-07T10:40:58.9183267Z strides: [8192, 128, 1], [8192, 64, 1] 2025-09-07T10:40:58.9183587Z dtypes: torch.float16, torch.float16 2025-09-07T10:40:58.9184370Z triton_bmm_83 0.1075 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=4, num_warps=4 2025-09-07T10:40:58.9185550Z triton_bmm_77 0.1085 ms 99.1% 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=2, num_warps=4 2025-09-07T10:40:58.9186719Z triton_bmm_79 0.1085 ms 99.1% 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 2025-09-07T10:40:58.9187870Z triton_bmm_80 0.1085 ms 99.1% 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 2025-09-07T10:40:58.9189264Z triton_bmm_82 0.1085 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=3, num_warps=4 2025-09-07T10:40:58.9190430Z triton_bmm_84 0.1085 ms 99.1% 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=2, num_warps=8 2025-09-07T10:40:58.9191588Z triton_bmm_73 0.1096 ms 98.1% 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 2025-09-07T10:40:58.9192756Z triton_bmm_74 0.1096 ms 98.1% 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 2025-09-07T10:40:58.9193921Z triton_bmm_75 0.1096 ms 98.1% 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 2025-09-07T10:40:58.9195096Z triton_bmm_76 0.1096 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:40:58.9196089Z SingleProcess AUTOTUNE benchmarking takes 0.3656 seconds and 0.0003 seconds precompiling for 16 choices 2025-09-07T10:41:02.0587432Z Autotune Choices Stats: 2025-09-07T10:41:02.0589645Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_120", "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": 0.03891199827194214, "best_triton_pos": 0} 2025-09-07T10:41:02.0635079Z AUTOTUNE addmm(16384x512, 16384x256, 256x512) 2025-09-07T10:41:02.0635772Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:41:02.0636464Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:41:02.0637999Z triton_mm_120 0.0389 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 2025-09-07T10:41:02.0639924Z bias_addmm 0.0399 ms 97.4% 2025-09-07T10:41:02.0641290Z triton_mm_116 0.0410 ms 95.0% 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 2025-09-07T10:41:02.0643866Z triton_mm_119 0.0410 ms 95.0% 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 2025-09-07T10:41:02.0646066Z triton_mm_113 0.0430 ms 90.5% 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 2025-09-07T10:41:02.0648248Z triton_mm_114 0.0440 ms 88.4% 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=4, num_warps=8 2025-09-07T10:41:02.0650475Z triton_mm_115 0.0440 ms 88.4% 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 2025-09-07T10:41:02.0652699Z triton_mm_117 0.0440 ms 88.4% 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 2025-09-07T10:41:02.0654881Z triton_mm_121 0.0481 ms 80.9% 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 2025-09-07T10:41:02.0657175Z triton_mm_110 0.0502 ms 77.6% 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 2025-09-07T10:41:02.0659432Z SingleProcess AUTOTUNE benchmarking takes 0.3877 seconds and 0.7618 seconds precompiling for 20 choices 2025-09-07T10:41:02.8907816Z Autotune Choices Stats: 2025-09-07T10:41:02.8910070Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_138", "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": 0.03891199827194214, "best_triton_pos": 0} 2025-09-07T10:41:02.8956108Z AUTOTUNE addmm(16384x256, 16384x512, 512x256) 2025-09-07T10:41:02.8956753Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:41:02.8957359Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:41:02.8958802Z triton_mm_138 0.0389 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 2025-09-07T10:41:02.8960168Z bias_addmm 0.0399 ms 97.4% 2025-09-07T10:41:02.8961450Z triton_mm_131 0.0420 ms 92.7% 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 2025-09-07T10:41:02.8964095Z triton_mm_132 0.0420 ms 92.7% 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=4, num_warps=8 2025-09-07T10:41:02.8966166Z triton_mm_133 0.0420 ms 92.7% 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 2025-09-07T10:41:02.8968305Z triton_mm_134 0.0420 ms 92.7% 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 2025-09-07T10:41:02.8970536Z triton_mm_135 0.0440 ms 88.4% 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 2025-09-07T10:41:02.8972764Z triton_mm_139 0.0440 ms 88.4% 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 2025-09-07T10:41:02.8975380Z triton_mm_129 0.0461 ms 84.4% 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 2025-09-07T10:41:02.8977743Z triton_mm_137 0.0461 ms 84.4% 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 2025-09-07T10:41:02.8979648Z SingleProcess AUTOTUNE benchmarking takes 0.3615 seconds and 0.4702 seconds precompiling for 20 choices 2025-09-07T10:41:06.8240494Z Autotune Choices Stats: 2025-09-07T10:41:06.8241713Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_166", "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=5, num_warps=4", "best_time": 0.04505600035190582, "best_triton_pos": 0} 2025-09-07T10:41:06.8288000Z AUTOTUNE bmm(12x16384x64, 12x64x64) 2025-09-07T10:41:06.8288330Z strides: [64, 768, 1], [4096, 64, 1] 2025-09-07T10:41:06.8288663Z dtypes: torch.float16, torch.float16 2025-09-07T10:41:06.8289408Z triton_bmm_166 0.0451 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 2025-09-07T10:41:06.8290606Z triton_bmm_169 0.0451 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 2025-09-07T10:41:06.8291796Z triton_bmm_170 0.0451 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=4, num_warps=4 2025-09-07T10:41:06.8292984Z triton_bmm_174 0.0451 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 2025-09-07T10:41:06.8294539Z triton_bmm_175 0.0451 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=5, num_warps=8 2025-09-07T10:41:06.8295736Z triton_bmm_165 0.0471 ms 95.7% 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 2025-09-07T10:41:06.8296925Z triton_bmm_171 0.0502 ms 89.8% 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 2025-09-07T10:41:06.8298193Z triton_bmm_159 0.0512 ms 88.0% 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 2025-09-07T10:41:06.8299368Z triton_bmm_167 0.0512 ms 88.0% 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 2025-09-07T10:41:06.8300564Z triton_bmm_172 0.0512 ms 88.0% 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=4, num_warps=8 2025-09-07T10:41:06.8301597Z SingleProcess AUTOTUNE benchmarking takes 0.3211 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:41:07.2275443Z Autotune Choices Stats: 2025-09-07T10:41:07.2276620Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_187", "best_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", "best_time": 0.09932799637317657, "best_triton_pos": 0} 2025-09-07T10:41:07.2322598Z AUTOTUNE bmm(3072x64x64, 3072x64x128) 2025-09-07T10:41:07.2323024Z strides: [4096, 64, 1], [8192, 128, 1] 2025-09-07T10:41:07.2323368Z dtypes: torch.float16, torch.float16 2025-09-07T10:41:07.2324402Z triton_bmm_187 0.0993 ms 100.0% 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 2025-09-07T10:41:07.2325621Z triton_bmm_183 0.1004 ms 99.0% 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 2025-09-07T10:41:07.2326801Z triton_bmm_184 0.1004 ms 99.0% 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 2025-09-07T10:41:07.2327982Z triton_bmm_188 0.1004 ms 99.0% 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=4, num_warps=4 2025-09-07T10:41:07.2329163Z triton_bmm_192 0.1004 ms 99.0% 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=5, num_warps=8 2025-09-07T10:41:07.2330346Z triton_bmm_185 0.1014 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 2025-09-07T10:41:07.2331521Z triton_bmm_186 0.1034 ms 96.0% 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 2025-09-07T10:41:07.2332696Z triton_bmm_189 0.1034 ms 96.0% 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 2025-09-07T10:41:07.2333426Z bmm 0.1055 ms 94.2% 2025-09-07T10:41:07.2334107Z triton_bmm_180 0.1055 ms 94.2% 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 2025-09-07T10:41:07.2335253Z SingleProcess AUTOTUNE benchmarking takes 0.4029 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:41:08.3240284Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T10:41:08.3241639Z attn_outputs = self.attention( 2025-09-07T10:41:08.3242368Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T10:41:08.3243370Z self_attention_outputs = self.self_attention( 2025-09-07T10:41:08.3244138Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T10:41:08.3245081Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T10:41:08.3246219Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T10:41:08.3247217Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T10:41:08.3247541Z 2025-09-07T10:41:08.3247550Z 2025-09-07T10:41:12.0663066Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T10:41:12.0664423Z attn_outputs = self.attention( 2025-09-07T10:41:12.0665155Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T10:41:12.0665926Z self_attention_outputs = self.self_attention( 2025-09-07T10:41:12.0666675Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T10:41:12.0667656Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T10:41:12.0669198Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T10:41:12.0677931Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T10:41:12.0678357Z 2025-09-07T10:41:12.0678362Z 2025-09-07T10:41:13.2735139Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in torch_dynamo_resume_in_forward_at_1585 2025-09-07T10:41:13.2736491Z attn_outputs = self.attention( 2025-09-07T10:41:13.2737321Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T10:41:13.2738140Z self_attention_outputs = self.self_attention( 2025-09-07T10:41:13.2738908Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T10:41:13.2739868Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T10:41:13.2741003Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T10:41:13.2741999Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T10:41:13.2742307Z 2025-09-07T10:41:13.2742312Z 2025-09-07T10:41:15.9328506Z Autotune Choices Stats: 2025-09-07T10:41:15.9329685Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_396", "best_kernel_desc": "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", "best_time": 0.04403200000524521, "best_triton_pos": 0} 2025-09-07T10:41:15.9375917Z AUTOTUNE addmm(16384x320, 16384x512, 512x320) 2025-09-07T10:41:15.9376307Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:41:15.9376658Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:41:15.9377531Z triton_mm_396 0.0440 ms 100.0% 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 2025-09-07T10:41:15.9378742Z triton_mm_400 0.0451 ms 97.7% 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 2025-09-07T10:41:15.9379916Z triton_mm_399 0.0471 ms 93.5% 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 2025-09-07T10:41:15.9381108Z triton_mm_397 0.0492 ms 89.6% 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 2025-09-07T10:41:15.9382278Z triton_mm_391 0.0532 ms 82.7% 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 2025-09-07T10:41:15.9383446Z triton_mm_395 0.0532 ms 82.7% 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 2025-09-07T10:41:15.9384620Z triton_mm_401 0.0532 ms 82.7% 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 2025-09-07T10:41:15.9385377Z bias_addmm 0.0553 ms 79.6% 2025-09-07T10:41:15.9386081Z triton_mm_393 0.0563 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=3, num_warps=4 2025-09-07T10:41:15.9387553Z triton_mm_394 0.0584 ms 75.4% 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=4, num_warps=8 2025-09-07T10:41:15.9388586Z SingleProcess AUTOTUNE benchmarking takes 0.3904 seconds and 1.1936 seconds precompiling for 20 choices 2025-09-07T10:41:18.5290614Z Autotune Choices Stats: 2025-09-07T10:41:18.5292121Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.03891199827194214, "best_triton_pos": 1, "best_triton_time": 0.03993599861860275, "best_triton_kernel": "triton_mm_418", "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"} 2025-09-07T10:41:18.5341758Z AUTOTUNE mm(16384x320, 320x512) 2025-09-07T10:41:18.5342102Z strides: [320, 1], [512, 1] 2025-09-07T10:41:18.5342400Z dtypes: torch.float16, torch.float16 2025-09-07T10:41:18.5342695Z mm 0.0389 ms 100.0% 2025-09-07T10:41:18.5343418Z triton_mm_418 0.0399 ms 97.4% 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 2025-09-07T10:41:18.5344605Z triton_mm_413 0.0420 ms 92.7% 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 2025-09-07T10:41:18.5345779Z triton_mm_414 0.0420 ms 92.7% 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 2025-09-07T10:41:18.5346959Z triton_mm_417 0.0420 ms 92.7% 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 2025-09-07T10:41:18.5348542Z triton_mm_411 0.0451 ms 86.4% 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 2025-09-07T10:41:18.5349706Z triton_mm_412 0.0471 ms 82.6% 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 2025-09-07T10:41:18.5350876Z triton_mm_415 0.0492 ms 79.2% 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 2025-09-07T10:41:18.5352050Z triton_mm_419 0.0492 ms 79.2% 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=5, num_warps=8 2025-09-07T10:41:18.5353225Z triton_mm_409 0.0532 ms 73.1% 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 2025-09-07T10:41:18.5354242Z SingleProcess AUTOTUNE benchmarking takes 0.4113 seconds and 0.8262 seconds precompiling for 19 choices 2025-09-07T10:41:20.2052645Z Autotune Choices Stats: 2025-09-07T10:41:20.2054173Z {"num_choices": 24, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.050175998359918594, "best_triton_pos": 3, "best_triton_time": 0.09318400174379349, "best_triton_kernel": "triton_mm_428", "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"} 2025-09-07T10:41:20.2112528Z AUTOTUNE mm(320x16384, 16384x512) 2025-09-07T10:41:20.2112861Z strides: [1, 320], [512, 1] 2025-09-07T10:41:20.2113153Z dtypes: torch.float16, torch.float16 2025-09-07T10:41:20.2113465Z mm 0.0502 ms 100.0% 2025-09-07T10:41:20.2113769Z decompose_k_mm_4_split_1 0.0532 ms 94.2% k_split=4 2025-09-07T10:41:20.2114154Z decompose_k_mm_2_split_0 0.0553 ms 90.7% k_split=2 2025-09-07T10:41:20.2114967Z triton_mm_428 0.0932 ms 53.8% 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 2025-09-07T10:41:20.2116517Z triton_mm_424 0.1116 ms 45.0% 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 2025-09-07T10:41:20.2117703Z triton_mm_422 0.1270 ms 39.5% 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 2025-09-07T10:41:20.2118867Z triton_mm_423 0.1280 ms 39.2% 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 2025-09-07T10:41:20.2120044Z triton_mm_427 0.1536 ms 32.7% 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 2025-09-07T10:41:20.2121202Z triton_mm_421 0.1608 ms 31.2% 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 2025-09-07T10:41:20.2121997Z decompose_k_mm_8_split_2 0.1751 ms 28.7% k_split=8 2025-09-07T10:41:20.2122621Z SingleProcess AUTOTUNE benchmarking takes 1.4305 seconds and 0.0004 seconds precompiling for 24 choices 2025-09-07T10:41:22.7061994Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2132, in torch_dynamo_resume_in_forward_at_2104 2025-09-07T10:41:22.7063387Z embedding_output = self.embeddings( 2025-09-07T10:41:22.7064134Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 357, in forward 2025-09-07T10:41:22.7064916Z inputs_embeds = self.word_embeddings(input_ids) 2025-09-07T10:41:22.7065511Z 2025-09-07T10:41:22.7065517Z 2025-09-07T10:41:22.7707715Z W0907 10:41:22.770000 42425 site-packages/torch/_logging/_internal.py:1199] [35/0] Profiler function will be ignored 2025-09-07T10:41:33.5935734Z pass 2025-09-07T10:41:37.6639934Z /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. 2025-09-07T10:41:37.6641328Z import pynvml # type: ignore[import] 2025-09-07T10:41:40.3639160Z 2025-09-07T10:41:48.8331745Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:41:48.8332140Z loading model: 0it [00:08, ?it/s] 2025-09-07T10:41:48.8332469Z cuda train hf_Roberta_base 2025-09-07T10:42:14.0615464Z Autotune Choices Stats: 2025-09-07T10:42:14.0616730Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_1329", "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": 4.369408130645752, "best_triton_pos": 0} 2025-09-07T10:42:14.0667833Z AUTOTUNE addmm(2048x250002, 2048x768, 768x250002) 2025-09-07T10:42:14.0668206Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T10:42:14.0668558Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:42:14.0669385Z triton_mm_1329 4.3694 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 2025-09-07T10:42:14.0670587Z triton_mm_1330 4.9869 ms 87.6% 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=3, num_warps=4 2025-09-07T10:42:14.0671790Z triton_mm_1323 5.1651 ms 84.6% 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=3, num_warps=4 2025-09-07T10:42:14.0672558Z bias_addmm 5.3176 ms 82.2% 2025-09-07T10:42:14.0673671Z triton_mm_1326 5.8184 ms 75.1% 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=3, num_warps=4 2025-09-07T10:42:14.0674865Z triton_mm_1331 5.8706 ms 74.4% 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 2025-09-07T10:42:14.0676058Z triton_mm_1325 5.9791 ms 73.1% 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 2025-09-07T10:42:14.0677227Z triton_mm_1327 6.9345 ms 63.0% 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=4, num_warps=8 2025-09-07T10:42:14.0678426Z triton_mm_1324 7.1393 ms 61.2% 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 2025-09-07T10:42:14.0679610Z triton_mm_1320 7.4598 ms 58.6% 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 2025-09-07T10:42:14.0680628Z SingleProcess AUTOTUNE benchmarking takes 1.6826 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:42:28.6458143Z Autotune Choices Stats: 2025-09-07T10:42:28.6459625Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 2.756608009338379, "best_triton_pos": 1, "best_triton_time": 4.521984100341797, "best_triton_kernel": "triton_mm_1359", "best_triton_kernel_desc": "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"} 2025-09-07T10:42:28.6512168Z AUTOTUNE mm(250002x2048, 2048x768) 2025-09-07T10:42:28.6512497Z strides: [1, 250048], [768, 1] 2025-09-07T10:42:28.6512796Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:28.6513096Z mm 2.7566 ms 100.0% 2025-09-07T10:42:28.6513817Z triton_mm_1359 4.5220 ms 61.0% 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 2025-09-07T10:42:28.6515021Z triton_mm_1365 4.8108 ms 57.3% 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 2025-09-07T10:42:28.6516225Z triton_mm_1366 5.0422 ms 54.7% 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 2025-09-07T10:42:28.6517411Z triton_mm_1361 5.2593 ms 52.4% 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 2025-09-07T10:42:28.6518614Z triton_mm_1364 6.0017 ms 45.9% 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=2, num_warps=8 2025-09-07T10:42:28.6519801Z triton_mm_1367 6.1030 ms 45.2% 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=5, num_warps=8 2025-09-07T10:42:28.6520982Z triton_mm_1362 6.5393 ms 42.2% 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=3, num_warps=4 2025-09-07T10:42:28.6522161Z triton_mm_1356 6.8884 ms 40.0% 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 2025-09-07T10:42:28.6523534Z triton_mm_1360 7.0973 ms 38.8% 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 2025-09-07T10:42:28.6524565Z SingleProcess AUTOTUNE benchmarking takes 1.5914 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:42:34.7598564Z Autotune Choices Stats: 2025-09-07T10:42:34.7600086Z {"num_choices": 29, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 2.8436479568481445, "best_triton_pos": 1, "best_triton_time": 4.902912139892578, "best_triton_kernel": "triton_mm_1348", "best_triton_kernel_desc": "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"} 2025-09-07T10:42:34.7667762Z AUTOTUNE mm(2048x250008, 250008x768) 2025-09-07T10:42:34.7668095Z strides: [250048, 1], [768, 1] 2025-09-07T10:42:34.7668398Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:34.7668690Z mm 2.8436 ms 100.0% 2025-09-07T10:42:34.7669398Z triton_mm_1348 4.9029 ms 58.0% 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 2025-09-07T10:42:34.7670635Z triton_mm_1349 5.0719 ms 56.1% 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 2025-09-07T10:42:34.7671447Z decompose_k_mm_6_split_3 5.2183 ms 54.5% k_split=6 2025-09-07T10:42:34.7671835Z decompose_k_mm_4_split_2 5.2644 ms 54.0% k_split=4 2025-09-07T10:42:34.7672226Z decompose_k_mm_2_split_0 5.2685 ms 54.0% k_split=2 2025-09-07T10:42:34.7672616Z decompose_k_mm_3_split_1 5.3371 ms 53.3% k_split=3 2025-09-07T10:42:34.7673015Z decompose_k_mm_33_split_9 5.5747 ms 51.0% k_split=33 2025-09-07T10:42:34.7673820Z triton_mm_1347 5.6945 ms 49.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:34.7675224Z triton_mm_1343 5.6955 ms 49.9% 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 2025-09-07T10:42:34.7676251Z SingleProcess AUTOTUNE benchmarking takes 4.2367 seconds and 0.0002 seconds precompiling for 29 choices 2025-09-07T10:42:39.2729828Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:42:39.2731091Z pred = mod(**cloned_inputs) 2025-09-07T10:42:39.2731847Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 1094, in forward 2025-09-07T10:42:39.2732610Z outputs = self.roberta( 2025-09-07T10:42:39.2733319Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 817, in forward 2025-09-07T10:42:39.2734112Z embedding_output = self.embeddings( 2025-09-07T10:42:39.2734846Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 118, in forward 2025-09-07T10:42:39.2735689Z position_embeddings = self.position_embeddings(position_ids) 2025-09-07T10:42:39.2736010Z 2025-09-07T10:42:39.2736015Z 2025-09-07T10:42:40.3232728Z W0907 10:42:40.322000 45697 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:43:09.8879049Z pass 2025-09-07T10:43:15.3915590Z /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. 2025-09-07T10:43:15.3917007Z import pynvml # type: ignore[import] 2025-09-07T10:43:18.1018377Z 2025-09-07T10:43:21.7592350Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:43:21.7592749Z loading model: 0it [00:03, ?it/s] 2025-09-07T10:43:21.7593055Z cuda train hf_T5 2025-09-07T10:43:51.2516865Z Autotune Choices Stats: 2025-09-07T10:43:51.2519610Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.04915200173854828, "best_triton_pos": 1, "best_triton_time": 0.050175998359918594, "best_triton_kernel": "triton_mm_125", "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"} 2025-09-07T10:43:51.2573864Z AUTOTUNE mm(4096x512, 512x2048) 2025-09-07T10:43:51.2574240Z strides: [512, 1], [1, 512] 2025-09-07T10:43:51.2574539Z dtypes: torch.float16, torch.float16 2025-09-07T10:43:51.2574837Z mm 0.0492 ms 100.0% 2025-09-07T10:43:51.2575564Z triton_mm_125 0.0502 ms 98.0% 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 2025-09-07T10:43:51.2576822Z triton_mm_124 0.0512 ms 96.0% 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 2025-09-07T10:43:51.2578089Z triton_mm_118 0.0543 ms 90.6% 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=3, num_warps=4 2025-09-07T10:43:51.2579271Z triton_mm_121 0.0543 ms 90.6% 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 2025-09-07T10:43:51.2580447Z triton_mm_120 0.0553 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 2025-09-07T10:43:51.2581615Z triton_mm_126 0.0604 ms 81.4% 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 2025-09-07T10:43:51.2583186Z triton_mm_119 0.0635 ms 77.4% 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=4, num_warps=8 2025-09-07T10:43:51.2584355Z triton_mm_122 0.0635 ms 77.4% 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 2025-09-07T10:43:51.2585531Z triton_mm_123 0.0707 ms 69.6% 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=2, num_warps=8 2025-09-07T10:43:51.2586546Z SingleProcess AUTOTUNE benchmarking takes 0.4140 seconds and 0.0008 seconds precompiling for 19 choices 2025-09-07T10:43:53.2556473Z Autotune Choices Stats: 2025-09-07T10:43:53.2557984Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_mm_12", "best_triton_kernel_desc": "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"} 2025-09-07T10:43:53.2613005Z AUTOTUNE mm(4096x512, 512x512) 2025-09-07T10:43:53.2613557Z strides: [512, 1], [1, 512] 2025-09-07T10:43:53.2614088Z dtypes: torch.float16, torch.float16 2025-09-07T10:43:53.2614655Z mm 0.0215 ms 100.0% 2025-09-07T10:43:53.2615951Z triton_mm_12 0.0215 ms 100.0% 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 2025-09-07T10:43:53.2618322Z triton_mm_9 0.0225 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=3, num_warps=4 2025-09-07T10:43:53.2620713Z triton_mm_11 0.0225 ms 95.5% 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 2025-09-07T10:43:53.2623303Z triton_mm_10 0.0246 ms 87.5% 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 2025-09-07T10:43:53.2625594Z triton_mm_13 0.0246 ms 87.5% 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 2025-09-07T10:43:53.2627778Z triton_mm_15 0.0246 ms 87.5% 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 2025-09-07T10:43:53.2630108Z triton_mm_16 0.0246 ms 87.5% 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 2025-09-07T10:43:53.2632435Z triton_mm_6 0.0256 ms 84.0% 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 2025-09-07T10:43:53.2634688Z triton_mm_7 0.0256 ms 84.0% 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 2025-09-07T10:43:53.2636684Z SingleProcess AUTOTUNE benchmarking takes 0.2898 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:43:53.6631983Z Autotune Choices Stats: 2025-09-07T10:43:53.6634230Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_63", "best_kernel_desc": "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", "best_time": 0.06348799914121628, "best_triton_pos": 0} 2025-09-07T10:43:53.6687656Z AUTOTUNE bmm(32x1024x64, 32x64x1024) 2025-09-07T10:43:53.6688750Z strides: [65536, 64, 1], [65536, 1024, 1] 2025-09-07T10:43:53.6689362Z dtypes: torch.float16, torch.float16 2025-09-07T10:43:53.6690826Z triton_bmm_63 0.0635 ms 100.0% 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 2025-09-07T10:43:53.6693143Z triton_bmm_61 0.0645 ms 98.4% 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 2025-09-07T10:43:53.6695440Z triton_bmm_65 0.0645 ms 98.4% 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 2025-09-07T10:43:53.6697827Z triton_bmm_66 0.0645 ms 98.4% 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 2025-09-07T10:43:53.6700119Z triton_bmm_62 0.0655 ms 96.9% 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=5, num_warps=4 2025-09-07T10:43:53.6702413Z triton_bmm_67 0.0666 ms 95.4% 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 2025-09-07T10:43:53.6704710Z triton_bmm_70 0.0666 ms 95.4% 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 2025-09-07T10:43:53.6707026Z triton_bmm_68 0.0676 ms 93.9% 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 2025-09-07T10:43:53.6709328Z triton_bmm_71 0.0676 ms 93.9% 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=3, num_warps=4 2025-09-07T10:43:53.6711654Z triton_bmm_72 0.0676 ms 93.9% 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 2025-09-07T10:43:53.6713927Z SingleProcess AUTOTUNE benchmarking takes 0.4020 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:43:54.0615047Z Autotune Choices Stats: 2025-09-07T10:43:54.0616223Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_85", "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=4, num_warps=4", "best_time": 0.07680000364780426, "best_triton_pos": 0} 2025-09-07T10:43:54.0671270Z AUTOTUNE bmm(32x1024x1024, 32x1024x64) 2025-09-07T10:43:54.0671667Z strides: [1048576, 1024, 1], [65536, 64, 1] 2025-09-07T10:43:54.0671996Z dtypes: torch.float16, torch.float16 2025-09-07T10:43:54.0672747Z triton_bmm_85 0.0768 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=4, num_warps=4 2025-09-07T10:43:54.0673983Z triton_bmm_81 0.0778 ms 98.7% 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 2025-09-07T10:43:54.0674722Z bmm 0.0788 ms 97.4% 2025-09-07T10:43:54.0675404Z triton_bmm_89 0.0788 ms 97.4% 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=3, num_warps=4 2025-09-07T10:43:54.0676580Z triton_bmm_90 0.0788 ms 97.4% 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 2025-09-07T10:43:54.0677750Z triton_bmm_84 0.0819 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=3, num_warps=4 2025-09-07T10:43:54.0679245Z triton_bmm_74 0.0840 ms 91.5% 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 2025-09-07T10:43:54.0680417Z triton_bmm_77 0.0840 ms 91.5% 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 2025-09-07T10:43:54.0681590Z triton_bmm_80 0.0840 ms 91.5% 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=3, num_warps=8 2025-09-07T10:43:54.0682757Z triton_bmm_86 0.0932 ms 82.4% 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 2025-09-07T10:43:54.0683964Z SingleProcess AUTOTUNE benchmarking takes 0.3978 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:43:54.4643903Z Autotune Choices Stats: 2025-09-07T10:43:54.4646086Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_138", "best_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", "best_time": 0.05734400078654289, "best_triton_pos": 0} 2025-09-07T10:43:54.4699579Z AUTOTUNE mm(4096x2048, 2048x512) 2025-09-07T10:43:54.4700144Z strides: [2048, 1], [1, 2048] 2025-09-07T10:43:54.4700679Z dtypes: torch.float16, torch.float16 2025-09-07T10:43:54.4702017Z triton_mm_138 0.0573 ms 100.0% 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 2025-09-07T10:43:54.4703376Z mm 0.0614 ms 93.3% 2025-09-07T10:43:54.4704610Z triton_mm_139 0.0614 ms 93.3% 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 2025-09-07T10:43:54.4706831Z triton_mm_136 0.0666 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=3, num_warps=4 2025-09-07T10:43:54.4709493Z triton_mm_143 0.0666 ms 86.2% 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 2025-09-07T10:43:54.4711722Z triton_mm_134 0.0707 ms 81.2% 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 2025-09-07T10:43:54.4713827Z triton_mm_137 0.0727 ms 78.9% 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=4, num_warps=8 2025-09-07T10:43:54.4715901Z triton_mm_140 0.0727 ms 78.9% 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 2025-09-07T10:43:54.4717929Z triton_mm_142 0.0727 ms 78.9% 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 2025-09-07T10:43:54.4720116Z triton_mm_135 0.0748 ms 76.7% 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 2025-09-07T10:43:54.4722094Z SingleProcess AUTOTUNE benchmarking takes 0.3999 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:43:55.4879212Z Autotune Choices Stats: 2025-09-07T10:43:55.4880698Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.5826560258865356, "best_triton_pos": 1, "best_triton_time": 0.7454720139503479, "best_triton_kernel": "triton_mm_2409", "best_triton_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"} 2025-09-07T10:43:55.4985820Z AUTOTUNE mm(4096x512, 512x32128) 2025-09-07T10:43:55.4986172Z strides: [512, 1], [1, 512] 2025-09-07T10:43:55.4986453Z dtypes: torch.float16, torch.float16 2025-09-07T10:43:55.4986764Z mm 0.5827 ms 100.0% 2025-09-07T10:43:55.4987504Z triton_mm_2409 0.7455 ms 78.2% 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 2025-09-07T10:43:55.4988721Z triton_mm_2410 0.7690 ms 75.8% 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 2025-09-07T10:43:55.4989915Z triton_mm_2403 0.7997 ms 72.9% 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 2025-09-07T10:43:55.4991081Z triton_mm_2405 0.8960 ms 65.0% 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 2025-09-07T10:43:55.4992288Z triton_mm_2406 0.9042 ms 64.4% 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 2025-09-07T10:43:55.4993488Z triton_mm_2411 0.9523 ms 61.2% 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=5, num_warps=8 2025-09-07T10:43:55.4994684Z triton_mm_2408 1.0158 ms 57.4% 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=2, num_warps=8 2025-09-07T10:43:55.4995874Z triton_mm_2407 1.0588 ms 55.0% 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=4, num_warps=8 2025-09-07T10:43:55.4997048Z triton_mm_2400 1.1069 ms 52.6% 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 2025-09-07T10:43:55.4998074Z SingleProcess AUTOTUNE benchmarking takes 0.8056 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:44:16.2136612Z Autotune Choices Stats: 2025-09-07T10:44:16.2138246Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.5109760165214539, "best_triton_pos": 1, "best_triton_time": 0.7086079716682434, "best_triton_kernel": "triton_mm_2428", "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"} 2025-09-07T10:44:16.2198070Z AUTOTUNE mm(32128x4096, 4096x512) 2025-09-07T10:44:16.2198410Z strides: [1, 32128], [512, 1] 2025-09-07T10:44:16.2198707Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:16.2198999Z mm 0.5110 ms 100.0% 2025-09-07T10:44:16.2199715Z triton_mm_2428 0.7086 ms 72.1% 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=3, num_warps=4 2025-09-07T10:44:16.2200954Z triton_mm_2427 0.7342 ms 69.6% 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 2025-09-07T10:44:16.2202145Z triton_mm_2421 0.7516 ms 68.0% 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 2025-09-07T10:44:16.2203581Z triton_mm_2423 0.8038 ms 63.6% 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 2025-09-07T10:44:16.2204770Z triton_mm_2424 0.8233 ms 62.1% 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=3, num_warps=4 2025-09-07T10:44:16.2205945Z triton_mm_2429 0.8724 ms 58.6% 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 2025-09-07T10:44:16.2207417Z triton_mm_2426 0.9165 ms 55.8% 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=2, num_warps=8 2025-09-07T10:44:16.2208612Z triton_mm_2425 0.9431 ms 54.2% 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 2025-09-07T10:44:16.2209791Z triton_mm_2422 0.9748 ms 52.4% 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=4, num_warps=8 2025-09-07T10:44:16.2210818Z SingleProcess AUTOTUNE benchmarking takes 0.7673 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T10:44:16.8932148Z Autotune Choices Stats: 2025-09-07T10:44:16.8933667Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.048128001391887665, "best_triton_pos": 1, "best_triton_time": 0.04915200173854828, "best_triton_kernel": "triton_mm_2481", "best_triton_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"} 2025-09-07T10:44:16.8989531Z AUTOTUNE mm(4096x512, 512x2048) 2025-09-07T10:44:16.8989904Z strides: [512, 1], [2048, 1] 2025-09-07T10:44:16.8990209Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:16.8990502Z mm 0.0481 ms 100.0% 2025-09-07T10:44:16.8991209Z triton_mm_2481 0.0492 ms 97.9% 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 2025-09-07T10:44:16.8992409Z triton_mm_2482 0.0502 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=3, num_warps=4 2025-09-07T10:44:16.8993610Z triton_mm_2475 0.0543 ms 88.7% 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 2025-09-07T10:44:16.8995118Z triton_mm_2477 0.0543 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 2025-09-07T10:44:16.8996307Z triton_mm_2478 0.0543 ms 88.7% 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 2025-09-07T10:44:16.8997488Z triton_mm_2483 0.0604 ms 79.7% 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 2025-09-07T10:44:16.8998679Z triton_mm_2476 0.0625 ms 77.0% 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 2025-09-07T10:44:16.8999867Z triton_mm_2479 0.0666 ms 72.3% 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 2025-09-07T10:44:16.9001058Z triton_mm_2472 0.0717 ms 67.1% 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=2, num_warps=4 2025-09-07T10:44:16.9002079Z SingleProcess AUTOTUNE benchmarking takes 0.3910 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:44:17.7302079Z Autotune Choices Stats: 2025-09-07T10:44:17.7303575Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.06451199948787689, "best_triton_pos": 1, "best_triton_time": 0.07372800260782242, "best_triton_kernel": "triton_mm_2459", "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"} 2025-09-07T10:44:17.7361313Z AUTOTUNE mm(512x4096, 4096x2048) 2025-09-07T10:44:17.7361625Z strides: [1, 512], [2048, 1] 2025-09-07T10:44:17.7361935Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:17.7362237Z mm 0.0645 ms 100.0% 2025-09-07T10:44:17.7363048Z triton_mm_2459 0.0737 ms 87.5% 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 2025-09-07T10:44:17.7364263Z triton_mm_2464 0.0737 ms 87.5% 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 2025-09-07T10:44:17.7365459Z triton_mm_2455 0.0768 ms 84.0% 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 2025-09-07T10:44:17.7366640Z triton_mm_2456 0.0778 ms 82.9% 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 2025-09-07T10:44:17.7367843Z triton_mm_2465 0.0788 ms 81.8% 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 2025-09-07T10:44:17.7369022Z triton_mm_2457 0.0829 ms 77.8% 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=3, num_warps=4 2025-09-07T10:44:17.7370209Z triton_mm_2463 0.0870 ms 74.1% 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 2025-09-07T10:44:17.7371393Z triton_mm_2460 0.0901 ms 71.6% 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 2025-09-07T10:44:17.7372573Z triton_mm_2458 0.0932 ms 69.2% 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 2025-09-07T10:44:17.7373843Z SingleProcess AUTOTUNE benchmarking takes 0.4394 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:44:18.2179191Z Autotune Choices Stats: 2025-09-07T10:44:18.2180676Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.05222399905323982, "best_triton_pos": 1, "best_triton_time": 0.07372800260782242, "best_triton_kernel": "triton_mm_2500", "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"} 2025-09-07T10:44:18.2235703Z AUTOTUNE mm(2048x4096, 4096x512) 2025-09-07T10:44:18.2236011Z strides: [1, 2048], [512, 1] 2025-09-07T10:44:18.2236313Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:18.2236617Z mm 0.0522 ms 100.0% 2025-09-07T10:44:18.2237338Z triton_mm_2500 0.0737 ms 70.8% 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 2025-09-07T10:44:18.2238547Z triton_mm_2495 0.0748 ms 69.9% 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 2025-09-07T10:44:18.2239719Z triton_mm_2491 0.0778 ms 67.1% 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 2025-09-07T10:44:18.2240900Z triton_mm_2492 0.0778 ms 67.1% 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 2025-09-07T10:44:18.2242083Z triton_mm_2501 0.0788 ms 66.2% 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=5, num_warps=8 2025-09-07T10:44:18.2243778Z triton_mm_2493 0.0829 ms 63.0% 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 2025-09-07T10:44:18.2244962Z triton_mm_2496 0.0850 ms 61.4% 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 2025-09-07T10:44:18.2246142Z triton_mm_2499 0.0881 ms 59.3% 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 2025-09-07T10:44:18.2247311Z triton_mm_2494 0.0942 ms 55.4% 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=4, num_warps=8 2025-09-07T10:44:18.2248337Z SingleProcess AUTOTUNE benchmarking takes 0.4291 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:44:18.8179465Z Autotune Choices Stats: 2025-09-07T10:44:18.8180967Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.02969600073993206, "best_triton_kernel": "triton_mm_2528", "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"} 2025-09-07T10:44:18.8245262Z AUTOTUNE mm(512x4096, 4096x512) 2025-09-07T10:44:18.8245559Z strides: [1, 512], [512, 1] 2025-09-07T10:44:18.8245909Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:18.8246211Z mm 0.0276 ms 100.0% 2025-09-07T10:44:18.8246910Z triton_mm_2528 0.0297 ms 93.1% 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 2025-09-07T10:44:18.8248083Z triton_mm_2527 0.0461 ms 60.0% 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 2025-09-07T10:44:18.8249627Z triton_mm_2521 0.0502 ms 55.1% 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 2025-09-07T10:44:18.8250818Z triton_mm_2531 0.0522 ms 52.9% 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 2025-09-07T10:44:18.8251998Z triton_mm_2522 0.0553 ms 50.0% 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 2025-09-07T10:44:18.8253166Z triton_mm_2523 0.0563 ms 49.1% 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 2025-09-07T10:44:18.8254338Z triton_mm_2530 0.0573 ms 48.2% 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 2025-09-07T10:44:18.8255529Z triton_mm_2533 0.0594 ms 46.6% 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 2025-09-07T10:44:18.8256706Z triton_mm_2524 0.0604 ms 45.8% 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 2025-09-07T10:44:18.8257800Z SingleProcess AUTOTUNE benchmarking takes 0.3738 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:44:21.1011718Z Autotune Choices Stats: 2025-09-07T10:44:21.1013201Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.5242879986763, "best_triton_pos": 1, "best_triton_time": 0.8560640215873718, "best_triton_kernel": "triton_mm_2441", "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"} 2025-09-07T10:44:21.1070842Z AUTOTUNE mm(4096x32128, 32128x512) 2025-09-07T10:44:21.1071176Z strides: [32128, 1], [512, 1] 2025-09-07T10:44:21.1071485Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:21.1071793Z mm 0.5243 ms 100.0% 2025-09-07T10:44:21.1072484Z triton_mm_2441 0.8561 ms 61.2% 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 2025-09-07T10:44:21.1073671Z triton_mm_2439 0.9441 ms 55.5% 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 2025-09-07T10:44:21.1074861Z triton_mm_2446 0.9708 ms 54.0% 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 2025-09-07T10:44:21.1076053Z triton_mm_2438 1.0066 ms 52.1% 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 2025-09-07T10:44:21.1077237Z triton_mm_2442 1.0301 ms 50.9% 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=3, num_warps=4 2025-09-07T10:44:21.1078415Z triton_mm_2437 1.0568 ms 49.6% 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 2025-09-07T10:44:21.1079580Z triton_mm_2445 1.0568 ms 49.6% 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 2025-09-07T10:44:21.1080762Z triton_mm_2436 1.1008 ms 47.6% 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 2025-09-07T10:44:21.1081946Z triton_mm_2447 1.1233 ms 46.7% 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 2025-09-07T10:44:21.1083415Z SingleProcess AUTOTUNE benchmarking takes 0.7783 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:44:21.4939207Z Autotune Choices Stats: 2025-09-07T10:44:21.4940383Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_2513", "best_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", "best_time": 0.058368001133203506, "best_triton_pos": 0} 2025-09-07T10:44:21.5001079Z AUTOTUNE mm(4096x2048, 2048x512) 2025-09-07T10:44:21.5001393Z strides: [2048, 1], [512, 1] 2025-09-07T10:44:21.5001689Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:21.5002447Z triton_mm_2513 0.0584 ms 100.0% 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 2025-09-07T10:44:21.5003406Z mm 0.0614 ms 95.0% 2025-09-07T10:44:21.5004100Z triton_mm_2511 0.0614 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=3, num_warps=4 2025-09-07T10:44:21.5005296Z triton_mm_2514 0.0645 ms 90.5% 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=3, num_warps=4 2025-09-07T10:44:21.5006493Z triton_mm_2518 0.0676 ms 86.4% 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 2025-09-07T10:44:21.5007682Z triton_mm_2509 0.0707 ms 82.6% 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 2025-09-07T10:44:21.5009179Z triton_mm_2515 0.0717 ms 81.4% 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 2025-09-07T10:44:21.5010382Z triton_mm_2517 0.0727 ms 80.3% 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 2025-09-07T10:44:21.5011572Z triton_mm_2510 0.0737 ms 79.2% 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 2025-09-07T10:44:21.5012749Z triton_mm_2512 0.0768 ms 76.0% 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 2025-09-07T10:44:21.5013769Z SingleProcess AUTOTUNE benchmarking takes 0.3908 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:44:21.7730854Z Autotune Choices Stats: 2025-09-07T10:44:21.7732356Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_mm_2549", "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"} 2025-09-07T10:44:21.7789736Z AUTOTUNE mm(4096x512, 512x512) 2025-09-07T10:44:21.7790104Z strides: [512, 1], [512, 1] 2025-09-07T10:44:21.7790384Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:21.7790698Z mm 0.0215 ms 100.0% 2025-09-07T10:44:21.7791418Z triton_mm_2549 0.0225 ms 95.5% 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 2025-09-07T10:44:21.7792613Z triton_mm_2550 0.0225 ms 95.5% 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=3, num_warps=4 2025-09-07T10:44:21.7793833Z triton_mm_2553 0.0236 ms 91.3% 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 2025-09-07T10:44:21.7795329Z triton_mm_2547 0.0246 ms 87.5% 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 2025-09-07T10:44:21.7796505Z triton_mm_2554 0.0246 ms 87.5% 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 2025-09-07T10:44:21.7797693Z triton_mm_2548 0.0256 ms 84.0% 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 2025-09-07T10:44:21.7798872Z triton_mm_2551 0.0256 ms 84.0% 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=4, num_warps=8 2025-09-07T10:44:21.7800064Z triton_mm_2545 0.0266 ms 80.8% 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 2025-09-07T10:44:21.7801244Z triton_mm_2555 0.0266 ms 80.8% 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 2025-09-07T10:44:21.7802277Z SingleProcess AUTOTUNE benchmarking takes 0.2782 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:44:22.1469391Z Autotune Choices Stats: 2025-09-07T10:44:22.1470575Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_2565", "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": 0.07577600330114365, "best_triton_pos": 0} 2025-09-07T10:44:22.1528205Z AUTOTUNE bmm(32x1024x1024, 32x1024x64) 2025-09-07T10:44:22.1528559Z strides: [1048576, 1, 1024], [65536, 64, 1] 2025-09-07T10:44:22.1528895Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:22.1529655Z triton_bmm_2565 0.0758 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 2025-09-07T10:44:22.1530872Z triton_bmm_2569 0.0758 ms 100.0% 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 2025-09-07T10:44:22.1532079Z triton_bmm_2564 0.0778 ms 97.4% 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=5, num_warps=4 2025-09-07T10:44:22.1533270Z triton_bmm_2568 0.0778 ms 97.4% 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 2025-09-07T10:44:22.1534469Z triton_bmm_2573 0.0778 ms 97.4% 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 2025-09-07T10:44:22.1535664Z triton_bmm_2562 0.0788 ms 96.1% 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=2, num_warps=4 2025-09-07T10:44:22.1536855Z triton_bmm_2570 0.0788 ms 96.1% 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 2025-09-07T10:44:22.1538103Z triton_bmm_2571 0.0788 ms 96.1% 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=2, num_warps=8 2025-09-07T10:44:22.1539292Z triton_bmm_2572 0.0799 ms 94.9% 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=3, num_warps=4 2025-09-07T10:44:22.1540043Z bmm 0.0809 ms 93.7% 2025-09-07T10:44:22.1540569Z SingleProcess AUTOTUNE benchmarking takes 0.3726 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:44:22.5449417Z Autotune Choices Stats: 2025-09-07T10:44:22.5450570Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_2582", "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=5, num_warps=4", "best_time": 0.062463998794555664, "best_triton_pos": 0} 2025-09-07T10:44:22.5510883Z AUTOTUNE bmm(32x1024x64, 32x64x1024) 2025-09-07T10:44:22.5511223Z strides: [65536, 64, 1], [65536, 1, 64] 2025-09-07T10:44:22.5511551Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:22.5512305Z triton_bmm_2582 0.0625 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 2025-09-07T10:44:22.5513526Z triton_bmm_2585 0.0625 ms 100.0% 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 2025-09-07T10:44:22.5514731Z triton_bmm_2586 0.0625 ms 100.0% 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=4, num_warps=4 2025-09-07T10:44:22.5515934Z triton_bmm_2583 0.0635 ms 98.4% 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 2025-09-07T10:44:22.5517120Z triton_bmm_2581 0.0655 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=8 2025-09-07T10:44:22.5518304Z triton_bmm_2587 0.0655 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 2025-09-07T10:44:22.5519689Z triton_bmm_2590 0.0655 ms 95.3% 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 2025-09-07T10:44:22.5520878Z triton_bmm_2591 0.0655 ms 95.3% 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 2025-09-07T10:44:22.5522070Z triton_bmm_2592 0.0655 ms 95.3% 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 2025-09-07T10:44:22.5523680Z triton_bmm_2584 0.0676 ms 92.4% 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=4, num_warps=8 2025-09-07T10:44:22.5524707Z SingleProcess AUTOTUNE benchmarking takes 0.3977 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:44:22.8834648Z Autotune Choices Stats: 2025-09-07T10:44:22.8835880Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_2602", "best_kernel_desc": "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", "best_time": 0.07577600330114365, "best_triton_pos": 0} 2025-09-07T10:44:22.8896597Z AUTOTUNE bmm(32x64x1024, 32x1024x1024) 2025-09-07T10:44:22.8896945Z strides: [65536, 1, 64], [1048576, 1024, 1] 2025-09-07T10:44:22.8897288Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:22.8898131Z triton_bmm_2602 0.0758 ms 100.0% 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 2025-09-07T10:44:22.8899350Z triton_bmm_2605 0.0768 ms 98.7% 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=3, num_warps=4 2025-09-07T10:44:22.8900558Z triton_bmm_2599 0.0778 ms 97.4% 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=2, num_warps=4 2025-09-07T10:44:22.8902088Z triton_bmm_2604 0.0778 ms 97.4% 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 2025-09-07T10:44:22.8902842Z bmm 0.0788 ms 96.1% 2025-09-07T10:44:22.8903536Z triton_bmm_2601 0.0788 ms 96.1% 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 2025-09-07T10:44:22.8904732Z triton_bmm_2603 0.0788 ms 96.1% 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=4, num_warps=8 2025-09-07T10:44:22.8905922Z triton_bmm_2608 0.0788 ms 96.1% 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=5, num_warps=8 2025-09-07T10:44:22.8907122Z triton_bmm_2595 0.0840 ms 90.2% 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 2025-09-07T10:44:22.8908284Z triton_bmm_2596 0.0840 ms 90.2% 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 2025-09-07T10:44:22.8909309Z SingleProcess AUTOTUNE benchmarking takes 0.3379 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T10:44:23.2815785Z Autotune Choices Stats: 2025-09-07T10:44:23.2816970Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_2621", "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=4, num_warps=4", "best_time": 0.07782399654388428, "best_triton_pos": 0} 2025-09-07T10:44:23.2878233Z AUTOTUNE bmm(32x1024x1024, 32x1024x64) 2025-09-07T10:44:23.2878589Z strides: [1048576, 1024, 1], [65536, 1, 1024] 2025-09-07T10:44:23.2878935Z dtypes: torch.float16, torch.float16 2025-09-07T10:44:23.2879717Z triton_bmm_2621 0.0778 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=4, num_warps=4 2025-09-07T10:44:23.2880917Z triton_bmm_2626 0.0778 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=5, num_warps=8 2025-09-07T10:44:23.2881675Z bmm 0.0788 ms 98.7% 2025-09-07T10:44:23.2882373Z triton_bmm_2617 0.0788 ms 98.7% 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 2025-09-07T10:44:23.2883748Z triton_bmm_2625 0.0788 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=3, num_warps=4 2025-09-07T10:44:23.2884951Z triton_bmm_2610 0.0819 ms 95.0% 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 2025-09-07T10:44:23.2886136Z triton_bmm_2620 0.0819 ms 95.0% 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 2025-09-07T10:44:23.2887322Z triton_bmm_2616 0.0829 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=3, num_warps=8 2025-09-07T10:44:23.2888494Z triton_bmm_2613 0.0850 ms 91.6% 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 2025-09-07T10:44:23.2889684Z triton_bmm_2612 0.0983 ms 79.2% 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 2025-09-07T10:44:23.2890892Z SingleProcess AUTOTUNE benchmarking takes 0.3975 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:44:30.4875583Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:44:30.4876849Z pred = mod(**cloned_inputs) 2025-09-07T10:44:30.4877508Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T10:44:30.4878188Z decoder_outputs = self.decoder( 2025-09-07T10:44:30.4878833Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T10:44:30.4879532Z layer_outputs = layer_module( 2025-09-07T10:44:30.4880143Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T10:44:30.4880795Z return super().__call__(*args, **kwargs) 2025-09-07T10:44:30.4881469Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 681, in forward 2025-09-07T10:44:30.4882137Z self_attention_outputs = self.layer[0]( 2025-09-07T10:44:30.4882802Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 599, in forward 2025-09-07T10:44:30.4883697Z attention_output = self.SelfAttention( 2025-09-07T10:44:30.4884372Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 539, in forward 2025-09-07T10:44:30.4885049Z position_bias = self.compute_bias( 2025-09-07T10:44:30.4885715Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 463, in compute_bias 2025-09-07T10:44:30.4887083Z values = self.relative_attention_bias(relative_position_bucket) # shape (query_length, key_length, num_heads) 2025-09-07T10:44:30.4887597Z 2025-09-07T10:44:30.4887611Z 2025-09-07T10:44:32.5242531Z pass 2025-09-07T10:44:37.4164487Z /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. 2025-09-07T10:44:37.4167196Z import pynvml # type: ignore[import] 2025-09-07T10:44:40.1200007Z 2025-09-07T10:44:45.9541927Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:44:45.9542295Z loading model: 0it [00:05, ?it/s] 2025-09-07T10:44:45.9542624Z cuda train hf_T5_base 2025-09-07T10:44:47.2708147Z WARNING:common:fp64 golden ref were not generated for hf_T5_base. Setting accuracy check to cosine 2025-09-07T10:45:40.2609324Z Autotune Choices Stats: 2025-09-07T10:45:40.2610959Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.09728000313043594, "best_triton_pos": 1, "best_triton_time": 0.10751999914646149, "best_triton_kernel": "triton_mm_125", "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"} 2025-09-07T10:45:40.2686151Z AUTOTUNE mm(4096x768, 768x3072) 2025-09-07T10:45:40.2686473Z strides: [768, 1], [1, 768] 2025-09-07T10:45:40.2686758Z dtypes: torch.float16, torch.float16 2025-09-07T10:45:40.2687064Z mm 0.0973 ms 100.0% 2025-09-07T10:45:40.2687774Z triton_mm_125 0.1075 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=3, num_warps=4 2025-09-07T10:45:40.2688973Z triton_mm_120 0.1116 ms 87.2% 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 2025-09-07T10:45:40.2690616Z triton_mm_121 0.1137 ms 85.6% 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 2025-09-07T10:45:40.2691796Z triton_mm_118 0.1147 ms 84.8% 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=3, num_warps=4 2025-09-07T10:45:40.2692954Z triton_mm_126 0.1198 ms 81.2% 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=5, num_warps=8 2025-09-07T10:45:40.2694142Z triton_mm_124 0.1208 ms 80.5% 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 2025-09-07T10:45:40.2695333Z triton_mm_122 0.1362 ms 71.4% 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 2025-09-07T10:45:40.2696502Z triton_mm_119 0.1403 ms 69.3% 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 2025-09-07T10:45:40.2697767Z triton_mm_123 0.1403 ms 69.3% 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=2, num_warps=8 2025-09-07T10:45:40.2698791Z SingleProcess AUTOTUNE benchmarking takes 0.5641 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:45:42.3137984Z Autotune Choices Stats: 2025-09-07T10:45:42.3139192Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_63", "best_kernel_desc": "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", "best_time": 0.09216000139713287, "best_triton_pos": 0} 2025-09-07T10:45:42.3205654Z AUTOTUNE bmm(48x1024x64, 48x64x1024) 2025-09-07T10:45:42.3205994Z strides: [65536, 64, 1], [65536, 1024, 1] 2025-09-07T10:45:42.3206342Z dtypes: torch.float16, torch.float16 2025-09-07T10:45:42.3207101Z triton_bmm_63 0.0922 ms 100.0% 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 2025-09-07T10:45:42.3208276Z triton_bmm_61 0.0932 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 2025-09-07T10:45:42.3209446Z triton_bmm_65 0.0932 ms 98.9% 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 2025-09-07T10:45:42.3210629Z triton_bmm_66 0.0932 ms 98.9% 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 2025-09-07T10:45:42.3211805Z triton_bmm_62 0.0942 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 2025-09-07T10:45:42.3212977Z triton_bmm_70 0.0952 ms 96.8% 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 2025-09-07T10:45:42.3214156Z triton_bmm_71 0.0963 ms 95.7% 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 2025-09-07T10:45:42.3215338Z triton_bmm_72 0.0963 ms 95.7% 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 2025-09-07T10:45:42.3216507Z triton_bmm_67 0.0983 ms 93.7% 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 2025-09-07T10:45:42.3218017Z triton_bmm_69 0.1014 ms 90.9% 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=2, num_warps=8 2025-09-07T10:45:42.3219042Z SingleProcess AUTOTUNE benchmarking takes 0.4892 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:45:42.7930583Z Autotune Choices Stats: 2025-09-07T10:45:42.7931759Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_81", "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": 0.10444799810647964, "best_triton_pos": 0} 2025-09-07T10:45:42.7996637Z AUTOTUNE bmm(48x1024x1024, 48x1024x64) 2025-09-07T10:45:42.7997000Z strides: [1048576, 1024, 1], [65536, 64, 1] 2025-09-07T10:45:42.7997364Z dtypes: torch.float16, torch.float16 2025-09-07T10:45:42.7998141Z triton_bmm_81 0.1044 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 2025-09-07T10:45:42.7999358Z triton_bmm_85 0.1044 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=4, num_warps=4 2025-09-07T10:45:42.8000553Z triton_bmm_90 0.1044 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=5, num_warps=8 2025-09-07T10:45:42.8001282Z bmm 0.1055 ms 99.0% 2025-09-07T10:45:42.8001961Z triton_bmm_84 0.1055 ms 99.0% 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 2025-09-07T10:45:42.8003344Z triton_bmm_80 0.1075 ms 97.1% 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 2025-09-07T10:45:42.8004937Z triton_bmm_74 0.1126 ms 92.7% 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 2025-09-07T10:45:42.8006113Z triton_bmm_89 0.1126 ms 92.7% 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=3, num_warps=4 2025-09-07T10:45:42.8007286Z triton_bmm_77 0.1147 ms 91.1% 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 2025-09-07T10:45:42.8008438Z triton_bmm_83 0.1331 ms 78.5% 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=4, num_warps=8 2025-09-07T10:45:42.8009455Z SingleProcess AUTOTUNE benchmarking takes 0.4784 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:45:44.2362548Z Autotune Choices Stats: 2025-09-07T10:45:44.2364278Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.8243200182914734, "best_triton_pos": 1, "best_triton_time": 1.0444799661636353, "best_triton_kernel": "triton_mm_4804", "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"} 2025-09-07T10:45:44.2430025Z AUTOTUNE mm(4096x768, 768x32128) 2025-09-07T10:45:44.2430346Z strides: [768, 1], [1, 768] 2025-09-07T10:45:44.2430645Z dtypes: torch.float16, torch.float16 2025-09-07T10:45:44.2430950Z mm 0.8243 ms 100.0% 2025-09-07T10:45:44.2431642Z triton_mm_4804 1.0445 ms 78.9% 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=3, num_warps=4 2025-09-07T10:45:44.2432866Z triton_mm_4803 1.1479 ms 71.8% 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 2025-09-07T10:45:44.2434386Z triton_mm_4797 1.1704 ms 70.4% 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 2025-09-07T10:45:44.2435574Z triton_mm_4799 1.2401 ms 66.5% 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 2025-09-07T10:45:44.2436762Z triton_mm_4805 1.2995 ms 63.4% 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 2025-09-07T10:45:44.2437950Z triton_mm_4800 1.3076 ms 63.0% 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 2025-09-07T10:45:44.2439146Z triton_mm_4802 1.4756 ms 55.9% 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=2, num_warps=8 2025-09-07T10:45:44.2440317Z triton_mm_4798 1.5186 ms 54.3% 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 2025-09-07T10:45:44.2441490Z triton_mm_4801 1.5227 ms 54.1% 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 2025-09-07T10:45:44.2442511Z SingleProcess AUTOTUNE benchmarking takes 0.8511 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:46:21.2166486Z Autotune Choices Stats: 2025-09-07T10:46:21.2167974Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.7065600156784058, "best_triton_pos": 1, "best_triton_time": 1.022976040840149, "best_triton_kernel": "triton_mm_4821", "best_triton_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"} 2025-09-07T10:46:21.2237837Z AUTOTUNE mm(32128x4096, 4096x768) 2025-09-07T10:46:21.2238150Z strides: [1, 32128], [768, 1] 2025-09-07T10:46:21.2238434Z dtypes: torch.float16, torch.float16 2025-09-07T10:46:21.2238742Z mm 0.7066 ms 100.0% 2025-09-07T10:46:21.2239453Z triton_mm_4821 1.0230 ms 69.1% 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 2025-09-07T10:46:21.2240659Z triton_mm_4822 1.0455 ms 67.6% 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=3, num_warps=4 2025-09-07T10:46:21.2241850Z triton_mm_4815 1.1213 ms 63.0% 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 2025-09-07T10:46:21.2243271Z triton_mm_4817 1.1868 ms 59.5% 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 2025-09-07T10:46:21.2244445Z triton_mm_4818 1.2411 ms 56.9% 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=3, num_warps=4 2025-09-07T10:46:21.2245643Z triton_mm_4823 1.2974 ms 54.5% 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 2025-09-07T10:46:21.2246834Z triton_mm_4820 1.3240 ms 53.4% 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=2, num_warps=8 2025-09-07T10:46:21.2248015Z triton_mm_4816 1.3640 ms 51.8% 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 2025-09-07T10:46:21.2249463Z triton_mm_4819 1.4213 ms 49.7% 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 2025-09-07T10:46:21.2250492Z SingleProcess AUTOTUNE benchmarking takes 0.8132 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:46:25.2945785Z Autotune Choices Stats: 2025-09-07T10:46:25.2947275Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.7157760262489319, "best_triton_pos": 1, "best_triton_time": 1.0977280139923096, "best_triton_kernel": "triton_mm_4840", "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"} 2025-09-07T10:46:25.3010264Z AUTOTUNE mm(4096x32128, 32128x768) 2025-09-07T10:46:25.3010617Z strides: [32128, 1], [768, 1] 2025-09-07T10:46:25.3010923Z dtypes: torch.float16, torch.float16 2025-09-07T10:46:25.3011229Z mm 0.7158 ms 100.0% 2025-09-07T10:46:25.3011955Z triton_mm_4840 1.0977 ms 65.2% 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 2025-09-07T10:46:25.3013165Z triton_mm_4839 1.1622 ms 61.6% 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 2025-09-07T10:46:25.3014356Z triton_mm_4841 1.2810 ms 55.9% 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 2025-09-07T10:46:25.3015535Z triton_mm_4833 1.2943 ms 55.3% 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=3, num_warps=4 2025-09-07T10:46:25.3017058Z triton_mm_4835 1.3302 ms 53.8% 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 2025-09-07T10:46:25.3018322Z triton_mm_4836 1.3773 ms 52.0% 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 2025-09-07T10:46:25.3019514Z triton_mm_4838 1.3988 ms 51.2% 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=2, num_warps=8 2025-09-07T10:46:25.3020706Z triton_mm_4831 1.6282 ms 44.0% 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 2025-09-07T10:46:25.3021883Z triton_mm_4834 1.6302 ms 43.9% 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=4, num_warps=8 2025-09-07T10:46:25.3022907Z SingleProcess AUTOTUNE benchmarking takes 0.8520 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T10:46:25.7414668Z Autotune Choices Stats: 2025-09-07T10:46:25.7415902Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_4963", "best_kernel_desc": "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", "best_time": 0.10035199671983719, "best_triton_pos": 0} 2025-09-07T10:46:25.7479409Z AUTOTUNE bmm(48x1024x1024, 48x1024x64) 2025-09-07T10:46:25.7479761Z strides: [1048576, 1, 1024], [65536, 64, 1] 2025-09-07T10:46:25.7480094Z dtypes: torch.float16, torch.float16 2025-09-07T10:46:25.7480851Z triton_bmm_4963 0.1004 ms 100.0% 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 2025-09-07T10:46:25.7482058Z triton_bmm_4966 0.1014 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 2025-09-07T10:46:25.7483798Z triton_bmm_4961 0.1024 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 2025-09-07T10:46:25.7485007Z triton_bmm_4967 0.1024 ms 98.0% 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 2025-09-07T10:46:25.7485752Z bmm 0.1044 ms 96.1% 2025-09-07T10:46:25.7486440Z triton_bmm_4957 0.1044 ms 96.1% 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 2025-09-07T10:46:25.7487612Z triton_bmm_4964 0.1044 ms 96.1% 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 2025-09-07T10:46:25.7488811Z triton_bmm_4960 0.1055 ms 95.1% 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=4, num_warps=8 2025-09-07T10:46:25.7490003Z triton_bmm_4962 0.1055 ms 95.1% 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 2025-09-07T10:46:25.7491195Z triton_bmm_4958 0.1065 ms 94.2% 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 2025-09-07T10:46:25.7492223Z SingleProcess AUTOTUNE benchmarking takes 0.4383 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:46:26.2331916Z Autotune Choices Stats: 2025-09-07T10:46:26.2333136Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_4980", "best_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=4, num_warps=4", "best_time": 0.09011200070381165, "best_triton_pos": 0} 2025-09-07T10:46:26.2398470Z AUTOTUNE bmm(48x1024x64, 48x64x1024) 2025-09-07T10:46:26.2398843Z strides: [65536, 64, 1], [65536, 1, 64] 2025-09-07T10:46:26.2399168Z dtypes: torch.float16, torch.float16 2025-09-07T10:46:26.2399935Z triton_bmm_4980 0.0901 ms 100.0% 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=4, num_warps=4 2025-09-07T10:46:26.2401149Z triton_bmm_4979 0.0911 ms 98.9% 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 2025-09-07T10:46:26.2402338Z triton_bmm_4976 0.0922 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 2025-09-07T10:46:26.2403778Z triton_bmm_4985 0.0922 ms 97.8% 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 2025-09-07T10:46:26.2404989Z triton_bmm_4986 0.0932 ms 96.7% 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 2025-09-07T10:46:26.2406194Z triton_bmm_4984 0.0942 ms 95.7% 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 2025-09-07T10:46:26.2407391Z triton_bmm_4975 0.0963 ms 93.6% 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 2025-09-07T10:46:26.2408569Z triton_bmm_4981 0.0963 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=3, num_warps=4 2025-09-07T10:46:26.2409762Z triton_bmm_4977 0.0973 ms 92.6% 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=3, num_warps=4 2025-09-07T10:46:26.2411213Z triton_bmm_4983 0.0993 ms 90.7% 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=2, num_warps=8 2025-09-07T10:46:26.2412255Z SingleProcess AUTOTUNE benchmarking takes 0.4912 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:46:26.6331489Z Autotune Choices Stats: 2025-09-07T10:46:26.6332670Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_4996", "best_kernel_desc": "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", "best_time": 0.1013759970664978, "best_triton_pos": 0} 2025-09-07T10:46:26.6397456Z AUTOTUNE bmm(48x64x1024, 48x1024x1024) 2025-09-07T10:46:26.6397817Z strides: [65536, 1, 64], [1048576, 1024, 1] 2025-09-07T10:46:26.6398149Z dtypes: torch.float16, torch.float16 2025-09-07T10:46:26.6398932Z triton_bmm_4996 0.1014 ms 100.0% 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 2025-09-07T10:46:26.6400136Z triton_bmm_5002 0.1024 ms 99.0% 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=5, num_warps=8 2025-09-07T10:46:26.6401326Z triton_bmm_5000 0.1044 ms 97.1% 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=4, num_warps=8 2025-09-07T10:46:26.6402066Z bmm 0.1055 ms 96.1% 2025-09-07T10:46:26.6402745Z triton_bmm_4994 0.1055 ms 96.1% 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 2025-09-07T10:46:26.6404346Z triton_bmm_4997 0.1055 ms 96.1% 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=4, num_warps=8 2025-09-07T10:46:26.6405542Z triton_bmm_4995 0.1065 ms 95.2% 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 2025-09-07T10:46:26.6406733Z triton_bmm_4998 0.1075 ms 94.3% 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 2025-09-07T10:46:26.6407925Z triton_bmm_4999 0.1075 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 2025-09-07T10:46:26.6409109Z triton_bmm_5001 0.1126 ms 90.0% 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=2, num_warps=8 2025-09-07T10:46:26.6410135Z SingleProcess AUTOTUNE benchmarking takes 0.3992 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T10:46:27.1158265Z Autotune Choices Stats: 2025-09-07T10:46:27.1159457Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_5020", "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=5, num_warps=8", "best_time": 0.10342399775981903, "best_triton_pos": 0} 2025-09-07T10:46:27.1225190Z AUTOTUNE bmm(48x1024x1024, 48x1024x64) 2025-09-07T10:46:27.1225565Z strides: [1048576, 1024, 1], [65536, 1, 1024] 2025-09-07T10:46:27.1225908Z dtypes: torch.float16, torch.float16 2025-09-07T10:46:27.1226664Z triton_bmm_5020 0.1034 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=5, num_warps=8 2025-09-07T10:46:27.1227439Z bmm 0.1044 ms 99.0% 2025-09-07T10:46:27.1228138Z triton_bmm_5011 0.1044 ms 99.0% 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 2025-09-07T10:46:27.1229586Z triton_bmm_5014 0.1044 ms 99.0% 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 2025-09-07T10:46:27.1230786Z triton_bmm_5010 0.1065 ms 97.1% 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 2025-09-07T10:46:27.1231981Z triton_bmm_5015 0.1065 ms 97.1% 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 2025-09-07T10:46:27.1233165Z triton_bmm_5004 0.1096 ms 94.4% 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 2025-09-07T10:46:27.1234377Z triton_bmm_5019 0.1116 ms 92.7% 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=3, num_warps=4 2025-09-07T10:46:27.1235573Z triton_bmm_5007 0.1167 ms 88.6% 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 2025-09-07T10:46:27.1236756Z triton_bmm_5006 0.1372 ms 75.4% 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 2025-09-07T10:46:27.1237777Z SingleProcess AUTOTUNE benchmarking takes 0.4822 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:46:36.7397609Z 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 489, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:46:36.7399281Z pred = mod(**cloned_inputs) 2025-09-07T10:46:36.7399944Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T10:46:36.7400611Z decoder_outputs = self.decoder( 2025-09-07T10:46:36.7401266Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T10:46:36.7401934Z layer_outputs = layer_module( 2025-09-07T10:46:36.7402547Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T10:46:36.7403445Z return super().__call__(*args, **kwargs) 2025-09-07T10:46:36.7404124Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 681, in forward 2025-09-07T10:46:36.7404814Z self_attention_outputs = self.layer[0]( 2025-09-07T10:46:36.7405494Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 599, in forward 2025-09-07T10:46:36.7406179Z attention_output = self.SelfAttention( 2025-09-07T10:46:36.7406844Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 539, in forward 2025-09-07T10:46:36.7407523Z position_bias = self.compute_bias( 2025-09-07T10:46:36.7408210Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 463, in compute_bias 2025-09-07T10:46:36.7409176Z values = self.relative_attention_bias(relative_position_bucket) # shape (query_length, key_length, num_heads) 2025-09-07T10:46:36.7409671Z 2025-09-07T10:46:36.7409676Z 2025-09-07T10:46:38.2110194Z W0907 10:46:38.210000 51106 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:47:21.7734770Z pass 2025-09-07T10:47:29.3063611Z /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. 2025-09-07T10:47:29.3065058Z import pynvml # type: ignore[import] 2025-09-07T10:47:32.1585748Z 2025-09-07T10:47:44.9447122Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:47:44.9447506Z loading model: 0it [00:12, ?it/s] 2025-09-07T10:47:44.9447818Z cuda train hf_T5_large 2025-09-07T10:47:44.9853757Z pass_due_to_skip 2025-09-07T10:47:47.1050490Z /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. 2025-09-07T10:47:47.1051939Z import pynvml # type: ignore[import] 2025-09-07T10:47:49.9410104Z 2025-09-07T10:47:52.6469281Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:47:52.6469662Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:47:52.6470005Z cuda train hf_Whisper 2025-09-07T10:48:06.0182817Z Autotune Choices Stats: 2025-09-07T10:48:06.0185049Z {"num_choices": 20, "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=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.05119999870657921, "best_triton_pos": 0} 2025-09-07T10:48:06.0255038Z AUTOTUNE addmm(6000x1536, 6000x384, 384x1536) 2025-09-07T10:48:06.0255715Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T10:48:06.0256341Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:48:06.0258024Z triton_mm_88 0.0512 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 2025-09-07T10:48:06.0260910Z triton_mm_87 0.0522 ms 98.0% 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 2025-09-07T10:48:06.0263386Z triton_mm_81 0.0543 ms 94.3% 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=3, num_warps=4 2025-09-07T10:48:06.0265706Z triton_mm_84 0.0543 ms 94.3% 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 2025-09-07T10:48:06.0268032Z triton_mm_83 0.0584 ms 87.7% 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 2025-09-07T10:48:06.0270313Z triton_mm_82 0.0645 ms 79.4% 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=4, num_warps=8 2025-09-07T10:48:06.0272635Z triton_mm_85 0.0645 ms 79.4% 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 2025-09-07T10:48:06.0274971Z triton_mm_89 0.0645 ms 79.4% 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 2025-09-07T10:48:06.0277286Z triton_mm_78 0.0717 ms 71.4% 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=2, num_warps=4 2025-09-07T10:48:06.0279505Z triton_mm_79 0.0717 ms 71.4% 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 2025-09-07T10:48:06.0281399Z SingleProcess AUTOTUNE benchmarking takes 0.5258 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T10:48:06.9926146Z Autotune Choices Stats: 2025-09-07T10:48:06.9928954Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_9", "best_kernel_desc": "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", "best_time": 0.020479999482631683, "best_triton_pos": 0} 2025-09-07T10:48:07.0052897Z AUTOTUNE mm(6000x384, 384x384) 2025-09-07T10:48:07.0053473Z strides: [384, 1], [1, 384] 2025-09-07T10:48:07.0053965Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:07.0055351Z triton_mm_9 0.0205 ms 100.0% 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 2025-09-07T10:48:07.0057698Z triton_mm_12 0.0205 ms 100.0% 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 2025-09-07T10:48:07.0060013Z triton_mm_15 0.0246 ms 83.3% 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 2025-09-07T10:48:07.0062278Z triton_mm_13 0.0256 ms 80.0% 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=4, num_warps=8 2025-09-07T10:48:07.0064491Z triton_mm_17 0.0256 ms 80.0% 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 2025-09-07T10:48:07.0066760Z triton_mm_10 0.0266 ms 76.9% 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=4, num_warps=8 2025-09-07T10:48:07.0069027Z triton_mm_14 0.0266 ms 76.9% 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=2, num_warps=8 2025-09-07T10:48:07.0071777Z triton_mm_7 0.0276 ms 74.1% 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 2025-09-07T10:48:07.0074006Z triton_mm_16 0.0297 ms 69.0% 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 2025-09-07T10:48:07.0076206Z triton_mm_6 0.0307 ms 66.7% 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=2, num_warps=4 2025-09-07T10:48:07.0078161Z SingleProcess AUTOTUNE benchmarking takes 0.4421 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T10:48:10.6657562Z Autotune Choices Stats: 2025-09-07T10:48:10.6658768Z {"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=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.04915200173854828, "best_triton_pos": 0} 2025-09-07T10:48:10.6725697Z AUTOTUNE mm(6000x1536, 1536x384) 2025-09-07T10:48:10.6726026Z strides: [1536, 1], [1, 1536] 2025-09-07T10:48:10.6726326Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:10.6727107Z triton_mm_101 0.0492 ms 100.0% 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 2025-09-07T10:48:10.6727850Z mm 0.0532 ms 92.3% 2025-09-07T10:48:10.6728548Z triton_mm_106 0.0543 ms 90.6% 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=3, num_warps=4 2025-09-07T10:48:10.6729733Z triton_mm_102 0.0553 ms 88.9% 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=3, num_warps=4 2025-09-07T10:48:10.6730920Z triton_mm_99 0.0563 ms 87.3% 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=3, num_warps=4 2025-09-07T10:48:10.6732441Z triton_mm_100 0.0594 ms 82.8% 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 2025-09-07T10:48:10.6733620Z triton_mm_103 0.0604 ms 81.4% 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 2025-09-07T10:48:10.6734790Z triton_mm_105 0.0614 ms 80.0% 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 2025-09-07T10:48:10.6735966Z triton_mm_97 0.0645 ms 76.2% 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 2025-09-07T10:48:10.6737144Z triton_mm_98 0.0666 ms 73.8% 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 2025-09-07T10:48:10.6738234Z SingleProcess AUTOTUNE benchmarking takes 0.3783 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:48:10.9797309Z Autotune Choices Stats: 2025-09-07T10:48:10.9798469Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_448", "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": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T10:48:10.9863623Z AUTOTUNE addmm(6000x256, 6000x384, 384x256) 2025-09-07T10:48:10.9863973Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T10:48:10.9864334Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:48:10.9865401Z triton_mm_448 0.0174 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 2025-09-07T10:48:10.9866171Z bias_addmm 0.0184 ms 94.4% 2025-09-07T10:48:10.9866908Z triton_mm_441 0.0184 ms 94.4% 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 2025-09-07T10:48:10.9868071Z triton_mm_442 0.0184 ms 94.4% 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=4, num_warps=8 2025-09-07T10:48:10.9869244Z triton_mm_443 0.0184 ms 94.4% 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 2025-09-07T10:48:10.9870416Z triton_mm_444 0.0184 ms 94.4% 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 2025-09-07T10:48:10.9871604Z triton_mm_449 0.0184 ms 94.4% 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 2025-09-07T10:48:10.9872779Z triton_mm_445 0.0195 ms 89.5% 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 2025-09-07T10:48:10.9873958Z triton_mm_447 0.0195 ms 89.5% 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 2025-09-07T10:48:10.9875133Z triton_mm_439 0.0205 ms 85.0% 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 2025-09-07T10:48:10.9876132Z SingleProcess AUTOTUNE benchmarking takes 0.3014 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:48:11.1715322Z Autotune Choices Stats: 2025-09-07T10:48:11.1716822Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_460", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T10:48:11.1780532Z AUTOTUNE addmm(4x2, 4x256, 256x2) 2025-09-07T10:48:11.1780867Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:48:11.1781275Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:48:11.1782091Z triton_mm_460 0.0072 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 2025-09-07T10:48:11.1783275Z triton_mm_451 0.0082 ms 87.5% 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=2, num_warps=1 2025-09-07T10:48:11.1784464Z triton_mm_452 0.0082 ms 87.5% 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 2025-09-07T10:48:11.1785646Z triton_mm_453 0.0082 ms 87.5% 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=5, num_warps=1 2025-09-07T10:48:11.1786812Z triton_mm_456 0.0082 ms 87.5% 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 2025-09-07T10:48:11.1787989Z triton_mm_457 0.0082 ms 87.5% 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=3, num_warps=1 2025-09-07T10:48:11.1789152Z triton_mm_458 0.0082 ms 87.5% 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 2025-09-07T10:48:11.1790503Z triton_mm_459 0.0082 ms 87.5% 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 2025-09-07T10:48:11.1791659Z triton_mm_455 0.0102 ms 70.0% 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=2, num_warps=1 2025-09-07T10:48:11.1792825Z triton_mm_450 0.0123 ms 58.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=1 2025-09-07T10:48:11.1793846Z SingleProcess AUTOTUNE benchmarking takes 0.1912 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T10:48:22.6754783Z Autotune Choices Stats: 2025-09-07T10:48:22.6756013Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_536", "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": 0.04608000069856644, "best_triton_pos": 0} 2025-09-07T10:48:22.6828812Z AUTOTUNE mm(6000x384, 384x1536) 2025-09-07T10:48:22.6829149Z strides: [384, 1], [1536, 1] 2025-09-07T10:48:22.6829445Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:22.6830215Z triton_mm_536 0.0461 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 2025-09-07T10:48:22.6831405Z triton_mm_537 0.0471 ms 97.8% 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 2025-09-07T10:48:22.6832596Z triton_mm_532 0.0481 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=3, num_warps=4 2025-09-07T10:48:22.6833777Z triton_mm_530 0.0492 ms 93.7% 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 2025-09-07T10:48:22.6835313Z triton_mm_533 0.0492 ms 93.7% 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 2025-09-07T10:48:22.6836061Z mm 0.0532 ms 86.5% 2025-09-07T10:48:22.6836745Z triton_mm_531 0.0563 ms 81.8% 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 2025-09-07T10:48:22.6837912Z triton_mm_534 0.0584 ms 78.9% 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 2025-09-07T10:48:22.6839096Z triton_mm_538 0.0584 ms 78.9% 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 2025-09-07T10:48:22.6840288Z triton_mm_535 0.0604 ms 76.3% 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=2, num_warps=8 2025-09-07T10:48:22.6841315Z SingleProcess AUTOTUNE benchmarking takes 0.3778 seconds and 0.0006 seconds precompiling for 19 choices 2025-09-07T10:48:23.5532378Z Autotune Choices Stats: 2025-09-07T10:48:23.5533883Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.048128001391887665, "best_triton_pos": 1, "best_triton_time": 0.07577600330114365, "best_triton_kernel": "triton_mm_550", "best_triton_kernel_desc": "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"} 2025-09-07T10:48:23.5604151Z AUTOTUNE mm(384x6000, 6000x1536) 2025-09-07T10:48:23.5604473Z strides: [1, 384], [1536, 1] 2025-09-07T10:48:23.5605149Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:23.5605453Z mm 0.0481 ms 100.0% 2025-09-07T10:48:23.5606172Z triton_mm_550 0.0758 ms 63.5% 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 2025-09-07T10:48:23.5607359Z triton_mm_546 0.0809 ms 59.5% 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 2025-09-07T10:48:23.5608537Z triton_mm_549 0.0819 ms 58.8% 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 2025-09-07T10:48:23.5609717Z triton_mm_543 0.0850 ms 56.6% 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 2025-09-07T10:48:23.5610891Z triton_mm_547 0.0870 ms 55.3% 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 2025-09-07T10:48:23.5612071Z triton_mm_552 0.0881 ms 54.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:48:23.5613241Z triton_mm_540 0.1055 ms 45.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:48:23.5614425Z triton_mm_555 0.1085 ms 44.3% 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 2025-09-07T10:48:23.5615615Z triton_mm_551 0.1106 ms 43.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:48:23.5616632Z SingleProcess AUTOTUNE benchmarking takes 0.4608 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:24.0523388Z Autotune Choices Stats: 2025-09-07T10:48:24.0525178Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.06656000018119812, "best_triton_pos": 1, "best_triton_time": 0.07680000364780426, "best_triton_kernel": "triton_mm_586", "best_triton_kernel_desc": "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"} 2025-09-07T10:48:24.0592611Z AUTOTUNE mm(1536x6000, 6000x384) 2025-09-07T10:48:24.0592938Z strides: [1, 1536], [384, 1] 2025-09-07T10:48:24.0593219Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:24.0593525Z mm 0.0666 ms 100.0% 2025-09-07T10:48:24.0594223Z triton_mm_586 0.0768 ms 86.7% 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 2025-09-07T10:48:24.0595423Z triton_mm_582 0.0799 ms 83.3% 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 2025-09-07T10:48:24.0596607Z triton_mm_585 0.0829 ms 80.2% 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 2025-09-07T10:48:24.0597789Z triton_mm_579 0.0860 ms 77.4% 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 2025-09-07T10:48:24.0598969Z triton_mm_588 0.0870 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:48:24.0600157Z triton_mm_583 0.0881 ms 75.6% 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 2025-09-07T10:48:24.0601545Z triton_mm_576 0.1034 ms 64.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:48:24.0602727Z triton_mm_587 0.1075 ms 61.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:48:24.0604039Z triton_mm_591 0.1075 ms 61.9% 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 2025-09-07T10:48:24.0605072Z SingleProcess AUTOTUNE benchmarking takes 0.4581 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:24.5571197Z Autotune Choices Stats: 2025-09-07T10:48:24.5572662Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.043007999658584595, "best_triton_kernel": "triton_mm_673", "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"} 2025-09-07T10:48:24.5641571Z AUTOTUNE mm(384x6000, 6000x384) 2025-09-07T10:48:24.5641880Z strides: [1, 384], [384, 1] 2025-09-07T10:48:24.5642169Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:24.5642460Z mm 0.0276 ms 100.0% 2025-09-07T10:48:24.5643362Z triton_mm_673 0.0430 ms 64.3% 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 2025-09-07T10:48:24.5644551Z triton_mm_669 0.0451 ms 61.4% 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 2025-09-07T10:48:24.5645733Z triton_mm_667 0.0512 ms 54.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:48:24.5647161Z triton_mm_668 0.0522 ms 52.9% 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 2025-09-07T10:48:24.5648341Z triton_mm_672 0.0604 ms 45.8% 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 2025-09-07T10:48:24.5649502Z triton_mm_666 0.0635 ms 43.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:48:24.5650694Z triton_mm_676 0.0707 ms 39.1% 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 2025-09-07T10:48:24.5651886Z triton_mm_675 0.0840 ms 32.9% 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 2025-09-07T10:48:24.5653081Z triton_mm_678 0.0850 ms 32.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:48:24.5654126Z SingleProcess AUTOTUNE benchmarking takes 0.4286 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:25.2786079Z Autotune Choices Stats: 2025-09-07T10:48:25.2787561Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.02457600086927414, "best_triton_pos": 1, "best_triton_time": 0.030719999223947525, "best_triton_kernel": "triton_mm_507", "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"} 2025-09-07T10:48:25.2856009Z AUTOTUNE mm(256x6000, 6000x384) 2025-09-07T10:48:25.2856718Z strides: [1, 256], [384, 1] 2025-09-07T10:48:25.2857022Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:25.2857432Z mm 0.0246 ms 100.0% 2025-09-07T10:48:25.2858145Z triton_mm_507 0.0307 ms 80.0% 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 2025-09-07T10:48:25.2859348Z triton_mm_511 0.0461 ms 53.3% 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 2025-09-07T10:48:25.2860530Z triton_mm_505 0.0502 ms 49.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:48:25.2861699Z triton_mm_506 0.0512 ms 48.0% 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 2025-09-07T10:48:25.2862870Z triton_mm_510 0.0604 ms 40.7% 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 2025-09-07T10:48:25.2864054Z triton_mm_504 0.0625 ms 39.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:48:25.2865226Z triton_mm_514 0.0696 ms 35.3% 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 2025-09-07T10:48:25.2866409Z triton_mm_513 0.0788 ms 31.2% 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 2025-09-07T10:48:25.2867594Z triton_mm_516 0.0870 ms 28.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:48:25.2868627Z SingleProcess AUTOTUNE benchmarking takes 0.4276 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:25.6640252Z Autotune Choices Stats: 2025-09-07T10:48:25.6641787Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_473", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T10:48:25.6710704Z AUTOTUNE mm(2x4, 4x256) 2025-09-07T10:48:25.6711011Z strides: [1, 2], [256, 1] 2025-09-07T10:48:25.6711300Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:25.6712064Z triton_mm_473 0.0072 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 2025-09-07T10:48:25.6713251Z triton_mm_474 0.0072 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=2, num_warps=2 2025-09-07T10:48:25.6714450Z triton_mm_475 0.0072 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 2025-09-07T10:48:25.6715635Z triton_mm_476 0.0072 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 2025-09-07T10:48:25.6716814Z triton_mm_477 0.0072 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 2025-09-07T10:48:25.6717993Z triton_mm_478 0.0072 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 2025-09-07T10:48:25.6719185Z triton_mm_479 0.0072 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 2025-09-07T10:48:25.6720601Z triton_mm_480 0.0072 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 2025-09-07T10:48:25.6721796Z triton_mm_481 0.0072 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 2025-09-07T10:48:25.6723060Z triton_mm_482 0.0072 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=4, num_warps=4 2025-09-07T10:48:25.6724084Z SingleProcess AUTOTUNE benchmarking takes 0.1683 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T10:48:26.4384996Z Autotune Choices Stats: 2025-09-07T10:48:26.4386206Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_461", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T10:48:26.4457529Z AUTOTUNE mm(4x2, 2x256) 2025-09-07T10:48:26.4457802Z strides: [2, 1], [256, 1] 2025-09-07T10:48:26.4458090Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:26.4458865Z triton_mm_461 0.0072 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 2025-09-07T10:48:26.4460058Z triton_mm_462 0.0072 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=2, num_warps=2 2025-09-07T10:48:26.4461246Z triton_mm_463 0.0072 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 2025-09-07T10:48:26.4462432Z triton_mm_464 0.0072 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 2025-09-07T10:48:26.4463938Z triton_mm_465 0.0072 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 2025-09-07T10:48:26.4465128Z triton_mm_466 0.0072 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 2025-09-07T10:48:26.4466320Z triton_mm_467 0.0072 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 2025-09-07T10:48:26.4467518Z triton_mm_468 0.0072 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 2025-09-07T10:48:26.4468721Z triton_mm_469 0.0072 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 2025-09-07T10:48:26.4469911Z triton_mm_470 0.0072 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=4, num_warps=4 2025-09-07T10:48:26.4470934Z SingleProcess AUTOTUNE benchmarking takes 0.1652 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T10:48:26.7025237Z Autotune Choices Stats: 2025-09-07T10:48:26.7026435Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_497", "best_kernel_desc": "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", "best_time": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T10:48:26.7096006Z AUTOTUNE mm(6000x256, 256x384) 2025-09-07T10:48:26.7096361Z strides: [256, 1], [384, 1] 2025-09-07T10:48:26.7096655Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:26.7097502Z triton_mm_497 0.0174 ms 100.0% 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 2025-09-07T10:48:26.7098711Z triton_mm_500 0.0174 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 2025-09-07T10:48:26.7099464Z mm 0.0184 ms 94.4% 2025-09-07T10:48:26.7100149Z triton_mm_494 0.0184 ms 94.4% 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 2025-09-07T10:48:26.7101340Z triton_mm_501 0.0184 ms 94.4% 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 2025-09-07T10:48:26.7102529Z triton_mm_496 0.0195 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 2025-09-07T10:48:26.7103687Z triton_mm_498 0.0195 ms 89.5% 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 2025-09-07T10:48:26.7104857Z triton_mm_495 0.0205 ms 85.0% 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 2025-09-07T10:48:26.7106031Z triton_mm_499 0.0205 ms 85.0% 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=2, num_warps=8 2025-09-07T10:48:26.7107201Z triton_mm_491 0.0215 ms 81.0% 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 2025-09-07T10:48:26.7108220Z SingleProcess AUTOTUNE benchmarking takes 0.2632 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:27.0653776Z Autotune Choices Stats: 2025-09-07T10:48:27.0656576Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_568", "best_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", "best_time": 0.04915200173854828, "best_triton_pos": 0} 2025-09-07T10:48:27.0724761Z AUTOTUNE mm(6000x1536, 1536x384) 2025-09-07T10:48:27.0725443Z strides: [1536, 1], [384, 1] 2025-09-07T10:48:27.0726125Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:27.0727940Z triton_mm_568 0.0492 ms 100.0% 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 2025-09-07T10:48:27.0729786Z mm 0.0522 ms 94.1% 2025-09-07T10:48:27.0731418Z triton_mm_566 0.0543 ms 90.6% 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=3, num_warps=4 2025-09-07T10:48:27.0734326Z triton_mm_573 0.0543 ms 90.6% 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=3, num_warps=4 2025-09-07T10:48:27.0737221Z triton_mm_567 0.0553 ms 88.9% 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=4, num_warps=8 2025-09-07T10:48:27.0740150Z triton_mm_569 0.0553 ms 88.9% 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=3, num_warps=4 2025-09-07T10:48:27.0743031Z triton_mm_572 0.0573 ms 85.7% 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 2025-09-07T10:48:27.0746290Z triton_mm_570 0.0604 ms 81.4% 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 2025-09-07T10:48:27.0749187Z triton_mm_574 0.0625 ms 78.7% 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 2025-09-07T10:48:27.0752044Z triton_mm_564 0.0635 ms 77.4% 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 2025-09-07T10:48:27.0754496Z SingleProcess AUTOTUNE benchmarking takes 0.3613 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:27.3420546Z Autotune Choices Stats: 2025-09-07T10:48:27.3421682Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_605", "best_kernel_desc": "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", "best_time": 0.020479999482631683, "best_triton_pos": 0} 2025-09-07T10:48:27.3492809Z AUTOTUNE mm(6000x384, 384x384) 2025-09-07T10:48:27.3493108Z strides: [384, 1], [384, 1] 2025-09-07T10:48:27.3493401Z dtypes: torch.float16, torch.float16 2025-09-07T10:48:27.3494161Z triton_mm_605 0.0205 ms 100.0% 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 2025-09-07T10:48:27.3495358Z triton_mm_608 0.0215 ms 95.2% 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 2025-09-07T10:48:27.3496086Z mm 0.0225 ms 90.9% 2025-09-07T10:48:27.3496768Z triton_mm_602 0.0225 ms 90.9% 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 2025-09-07T10:48:27.3498001Z triton_mm_604 0.0225 ms 90.9% 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 2025-09-07T10:48:27.3499439Z triton_mm_606 0.0225 ms 90.9% 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 2025-09-07T10:48:27.3500625Z triton_mm_609 0.0225 ms 90.9% 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=3, num_warps=4 2025-09-07T10:48:27.3501805Z triton_mm_603 0.0236 ms 87.0% 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 2025-09-07T10:48:27.3502956Z triton_mm_600 0.0256 ms 80.0% 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 2025-09-07T10:48:27.3504138Z triton_mm_607 0.0256 ms 80.0% 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=2, num_warps=8 2025-09-07T10:48:27.3505161Z SingleProcess AUTOTUNE benchmarking takes 0.2758 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:48:32.7129705Z W0907 10:48:32.711000 52893 site-packages/torch/_logging/_internal.py:1199] [5/0] Profiler function will be ignored 2025-09-07T10:48:42.7985582Z pass 2025-09-07T10:48:46.9180479Z /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. 2025-09-07T10:48:46.9182331Z import pynvml # type: ignore[import] 2025-09-07T10:48:49.8061797Z 2025-09-07T10:48:50.3376904Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:50.3377742Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:50.3378510Z cuda train hf_distil_whisper 2025-09-07T10:48:50.3386688Z Traceback (most recent call last): 2025-09-07T10:48:50.3387895Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:48:50.3389112Z ) = runner.load_model( 2025-09-07T10:48:50.3390315Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 325, in load_model 2025-09-07T10:48:50.3391629Z benchmark = benchmark_cls( 2025-09-07T10:48:50.3392597Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T10:48:50.3393704Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T10:48:50.3394998Z File "/torchbench/torchbenchmark/models/hf_distil_whisper/__init__.py", line 13, in __init__ 2025-09-07T10:48:50.3396491Z raise NotImplementedError("Training is not implemented.") 2025-09-07T10:48:50.3397553Z NotImplementedError: Training is not implemented. 2025-09-07T10:48:50.3398190Z 2025-09-07T10:48:50.3398393Z model_fail_to_load 2025-09-07T10:48:51.4102184Z accuracy pass_rate=80.00% 2025-09-07T10:48:51.4109679Z calls_captured gmean=0.00x mean=1418.067x 2025-09-07T10:48:51.4113967Z unique_graphs gmean=0.00x mean=3.867x 2025-09-07T10:48:51.4118198Z graph_breaks gmean=0.00x mean=6.400x 2025-09-07T10:48:51.4122236Z unique_graph_breaks gmean=0.00x mean=4.467x 2025-09-07T10:48:51.4126917Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:48:51.4131109Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:48:51.4135289Z cudagraph_skips gmean=0.00x mean=1.067x 2025-09-07T10:48:51.4136212Z compilation_latency mean=76.369 seconds 2025-09-07T10:48:52.3729640Z + [[ 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* ]] 2025-09-07T10:48:52.3732699Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:48:52.3733273Z + for target in "${targets[@]}" 2025-09-07T10:48:52.3734387Z + target_flag=('--performance') 2025-09-07T10:48:52.3734926Z + local target_flag 2025-09-07T10:48:52.3735414Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T10:48:52.3736050Z + target_flag+=(--cold-start-latency) 2025-09-07T10:48:52.3738828Z + [[ 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* ]] 2025-09-07T10:48:52.3743661Z + [[ 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* ]] 2025-09-07T10:48:52.3748784Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.csv 2025-09-07T10:48:52.9688595Z /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. 2025-09-07T10:48:52.9691276Z import pynvml # type: ignore[import] 2025-09-07T10:48:56.8585789Z /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. 2025-09-07T10:48:56.8587674Z import pynvml # type: ignore[import] 2025-09-07T10:48:59.9207785Z 2025-09-07T10:49:05.9883039Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:49:05.9883388Z loading model: 0it [00:06, ?it/s] 2025-09-07T10:49:05.9883732Z cuda train hf_Bart 2025-09-07T10:49:24.8765222Z W0907 10:49:24.875000 57590 site-packages/torch/_logging/_internal.py:1199] [27/0] Profiler function will be ignored 2025-09-07T10:50:05.2231084Z 2025-09-07T10:50:05.3581487Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:51:23.3453379Z 2025-09-07T10:51:23.4645566Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:53:47.9265796Z 2025-09-07T10:53:48.1135022Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:55:27.7389002Z 2025-09-07T10:55:28.1690483Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:56:26.8709541Z 2025-09-07T10:56:26.9797434Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:57:32.0701720Z 2025-09-07T10:57:32.1721117Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:00:28.1973660Z 2025-09-07T11:00:28.5615160Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:02:38.4904512Z 2025-09-07T11:02:38.6748612Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:03:34.9325411Z 2025-09-07T11:03:35.1721043Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:04:53.4977339Z 2025-09-07T11:04:53.6932489Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:08:06.7626297Z 2025-09-07T11:08:07.3062096Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:12:26.0647929Z 2025-09-07T11:12:26.4873294Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:13:15.0318978Z 2025-09-07T11:13:15.1565641Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:14:38.2464783Z 2025-09-07T11:14:38.4097703Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:15:52.8466718Z 2025-09-07T11:15:52.9994887Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:18:10.1263949Z 2025-09-07T11:18:10.4325356Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:19:53.6875944Z 2025-09-07T11:19:56.2076382Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:21:56.5732834Z 2025-09-07T11:21:56.7052395Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:23:02.2409370Z 2025-09-07T11:23:02.3901764Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:26:04.8869344Z 2025-09-07T11:26:05.4893863Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:28:17.1397993Z 2025-09-07T11:28:17.3562945Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:29:11.3620362Z 2025-09-07T11:29:11.6125002Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:30:31.4693024Z 2025-09-07T11:30:31.7293936Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:33:48.7394244Z 2025-09-07T11:33:49.5881811Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:38:22.4185153Z 2025-09-07T11:38:23.1089805Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:39:11.5472058Z 2025-09-07T11:39:11.6595542Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:40:40.8415243Z 2025-09-07T11:40:41.0049334Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:41:58.8113137Z 2025-09-07T11:41:58.9630993Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:44:19.8763424Z 2025-09-07T11:44:20.1812514Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:46:00.7531363Z 2025-09-07T11:46:03.2971811Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:48:07.8756781Z 2025-09-07T11:48:08.0077127Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:49:16.9550073Z 2025-09-07T11:49:17.1027895Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:52:21.0346624Z 2025-09-07T11:52:21.6446756Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:54:36.9969124Z 2025-09-07T11:54:37.2133777Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:55:30.4976815Z 2025-09-07T11:55:30.7474395Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:56:53.5051540Z 2025-09-07T11:56:53.7655487Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:00:17.0846743Z 2025-09-07T12:00:17.9332114Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:04:54.1559988Z 2025-09-07T12:04:54.8498333Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:05:47.3484740Z 2025-09-07T12:05:47.4605193Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:07:57.6720974Z 2025-09-07T12:07:57.7985797Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:09:58.1505121Z 2025-09-07T12:09:58.2699794Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:14:08.0136366Z 2025-09-07T12:14:08.2081628Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:16:18.3604177Z 2025-09-07T12:16:18.6993736Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:17:35.5761420Z 2025-09-07T12:17:35.6939205Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:19:14.2559779Z 2025-09-07T12:19:14.3769327Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:24:31.5613901Z 2025-09-07T12:24:31.9331898Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:27:45.2528295Z 2025-09-07T12:27:45.4626612Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:29:03.8136703Z 2025-09-07T12:29:04.0496967Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:31:08.0216620Z 2025-09-07T12:31:08.2191401Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:36:55.4151074Z 2025-09-07T12:36:55.9565145Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:48:28.7442214Z 2025-09-07T12:48:29.1737559Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:49:34.9226247Z 2025-09-07T12:49:35.0493496Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:51:32.5945177Z 2025-09-07T12:51:32.7562952Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:53:07.9846974Z 2025-09-07T12:53:08.1349005Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:55:59.6899349Z 2025-09-07T12:55:59.9958260Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:58:19.8193214Z 2025-09-07T12:58:22.4505951Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:00:48.1341027Z 2025-09-07T13:00:48.2700751Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:02:15.0310631Z 2025-09-07T13:02:15.1752612Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:05:58.8761746Z 2025-09-07T13:05:59.4814581Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:08:43.3911386Z 2025-09-07T13:08:43.6035298Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:10:09.2979063Z 2025-09-07T13:10:09.5491081Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:11:55.0205361Z 2025-09-07T13:11:55.2763713Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:17:10.1778071Z 2025-09-07T13:17:11.0272388Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:23:09.5528840Z 2025-09-07T13:23:10.2330246Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T13:24:23.4037338Z 2025-09-07T13:24:23.5165527Z running benchmark: 0% 0/30 [00:00 0:`). Dynamo does not support tracing dynamic control flow. 2025-09-07T14:24:34.9618296Z Hint: This graph break is fundamental - it is unlikely that Dynamo will ever be able to trace through your code. Consider finding a workaround. 2025-09-07T14:24:34.9619072Z Hint: Use `torch.cond` to express dynamic control flow. 2025-09-07T14:24:34.9619364Z 2025-09-07T14:24:34.9619602Z Developer debug context: attempted to jump with NumpyNdarrayVariable() 2025-09-07T14:24:34.9619956Z 2025-09-07T14:24:34.9620438Z For more details about this graph break, please visit: https://meta-pytorch.github.io/compile-graph-break-site/gb/gb0170.html 2025-09-07T14:24:34.9621011Z 2025-09-07T14:24:34.9621113Z from user code: 2025-09-07T14:24:34.9621912Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2481, in forward 2025-09-07T14:24:34.9622668Z reformer_outputs = self.reformer( 2025-09-07T14:24:34.9623298Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:24:34.9623942Z return forward_call(*args, **kwargs) 2025-09-07T14:24:34.9624678Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2099, in forward 2025-09-07T14:24:34.9625457Z input_shape[-1] % least_common_mult_chunk_length != 0 2025-09-07T14:24:34.9625738Z 2025-09-07T14:24:34.9626351Z 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" 2025-09-07T14:24:34.9627096Z 2025-09-07T14:24:34.9627318Z TorchDynamo optimized model failed to run because of following error 2025-09-07T14:24:34.9814136Z fail_to_run 2025-09-07T14:24:36.6371792Z /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. 2025-09-07T14:24:36.6373190Z import pynvml # type: ignore[import] 2025-09-07T14:24:39.2356448Z 2025-09-07T14:24:47.2048548Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:24:47.2048919Z loading model: 0it [00:07, ?it/s] 2025-09-07T14:24:47.2109108Z cuda eval hf_Roberta_base 2025-09-07T14:24:53.9862231Z pass 2025-09-07T14:24:55.8231339Z /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. 2025-09-07T14:24:55.8233145Z import pynvml # type: ignore[import] 2025-09-07T14:24:58.4227262Z 2025-09-07T14:25:01.8504556Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:25:01.8504947Z loading model: 0it [00:03, ?it/s] 2025-09-07T14:25:01.8544393Z cuda eval hf_T5 2025-09-07T14:25:11.5387207Z pass 2025-09-07T14:25:13.4559278Z /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. 2025-09-07T14:25:13.4560699Z import pynvml # type: ignore[import] 2025-09-07T14:25:16.0476404Z 2025-09-07T14:25:21.5901116Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:25:21.5901505Z loading model: 0it [00:05, ?it/s] 2025-09-07T14:25:21.5901812Z cuda eval hf_T5_base 2025-09-07T14:25:21.5916884Z Traceback (most recent call last): 2025-09-07T14:25:21.5917495Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T14:25:21.5918094Z self.model_iter_fn(model, example_inputs) 2025-09-07T14:25:21.5918666Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 480, in forward_pass 2025-09-07T14:25:21.5919230Z return mod(**inputs) 2025-09-07T14:25:21.5919863Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:25:21.5920553Z return self._call_impl(*args, **kwargs) 2025-09-07T14:25:21.5921184Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:25:21.5921820Z return forward_call(*args, **kwargs) 2025-09-07T14:25:21.5922491Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T14:25:21.5923800Z decoder_outputs = self.decoder( 2025-09-07T14:25:21.5924799Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:25:21.5925487Z return self._call_impl(*args, **kwargs) 2025-09-07T14:25:21.5926108Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:25:21.5926753Z return forward_call(*args, **kwargs) 2025-09-07T14:25:21.5927435Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T14:25:21.5928104Z layer_outputs = layer_module( 2025-09-07T14:25:21.5928715Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T14:25:21.5929356Z return super().__call__(*args, **kwargs) 2025-09-07T14:25:21.5930026Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:25:21.5930720Z return self._call_impl(*args, **kwargs) 2025-09-07T14:25:21.5931348Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:25:21.5931983Z return forward_call(*args, **kwargs) 2025-09-07T14:25:21.5932647Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 705, in forward 2025-09-07T14:25:21.5933330Z cross_attention_outputs = self.layer[1]( 2025-09-07T14:25:21.5934015Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:25:21.5934696Z return self._call_impl(*args, **kwargs) 2025-09-07T14:25:21.5935415Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:25:21.5936055Z return forward_call(*args, **kwargs) 2025-09-07T14:25:21.5936725Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 635, in forward 2025-09-07T14:25:21.5937524Z attention_output = self.EncDecAttention( 2025-09-07T14:25:21.5938199Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:25:21.5938887Z return self._call_impl(*args, **kwargs) 2025-09-07T14:25:21.5939522Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:25:21.5940164Z return forward_call(*args, **kwargs) 2025-09-07T14:25:21.5940826Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 558, in forward 2025-09-07T14:25:21.5941627Z attn_weights = nn.functional.softmax(scores.float(), dim=-1).type_as(scores) 2025-09-07T14:25:21.5942370Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py", line 2133, in softmax 2025-09-07T14:25:21.5943048Z ret = input.softmax(dim) 2025-09-07T14:25:21.5945361Z torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 768.00 MiB. GPU 0 has a total capacity of 39.38 GiB of which 13.38 MiB is free. Including non-PyTorch memory, this process has 0 bytes memory in use. Of the allocated memory 38.27 GiB is allocated by PyTorch, and 583.88 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) 2025-09-07T14:25:21.5947611Z 2025-09-07T14:25:21.5947829Z The above exception was the direct cause of the following exception: 2025-09-07T14:25:21.5948176Z 2025-09-07T14:25:21.5948287Z Traceback (most recent call last): 2025-09-07T14:25:21.5948783Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T14:25:21.5949281Z ) = runner.load_model( 2025-09-07T14:25:21.5949904Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T14:25:21.5950493Z self.validate_model(model, example_inputs) 2025-09-07T14:25:21.5951067Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T14:25:21.5951660Z raise RuntimeError("Eager run failed") from e 2025-09-07T14:25:21.5952001Z RuntimeError: Eager run failed 2025-09-07T14:25:21.5952200Z 2025-09-07T14:25:21.5952288Z eager_fail_to_run 2025-09-07T14:25:23.3340029Z /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. 2025-09-07T14:25:23.3341530Z import pynvml # type: ignore[import] 2025-09-07T14:25:25.9262823Z 2025-09-07T14:25:28.9123128Z loading model: 0it [00:00, ?it/s]`generation_config` default values have been modified to match model-specific defaults: {'eos_token_id': 1}. If this is not desired, please set these values explicitly. 2025-09-07T14:25:28.9124756Z WARNING:transformers.generation.utils:`generation_config` default values have been modified to match model-specific defaults: {'eos_token_id': 1}. If this is not desired, please set these values explicitly. 2025-09-07T14:25:33.1633649Z 2025-09-07T14:25:33.1634022Z loading model: 0it [00:07, ?it/s] 2025-09-07T14:25:33.1675141Z cuda eval hf_T5_generate 2025-09-07T14:25:59.6713979Z ERROR:common: 2025-09-07T14:25:59.6714292Z Traceback (most recent call last): 2025-09-07T14:25:59.6714853Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2320, in check_accuracy 2025-09-07T14:25:59.6715738Z optimized_model_iter_fn = optimize_ctx( 2025-09-07T14:25:59.6716268Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1523, in export 2025-09-07T14:25:59.6716811Z ep = torch.export.export( 2025-09-07T14:25:59.6717392Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py", line 311, in export 2025-09-07T14:25:59.6717959Z raise e 2025-09-07T14:25:59.6718450Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py", line 277, in export 2025-09-07T14:25:59.6719025Z return _export( 2025-09-07T14:25:59.6719536Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1163, in wrapper 2025-09-07T14:25:59.6720092Z raise e 2025-09-07T14:25:59.6720578Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1129, in wrapper 2025-09-07T14:25:59.6721161Z ep = fn(*args, **kwargs) 2025-09-07T14:25:59.6721759Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/exported_program.py", line 124, in wrapper 2025-09-07T14:25:59.6722411Z return fn(*args, **kwargs) 2025-09-07T14:25:59.6723470Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 2255, in _export 2025-09-07T14:25:59.6724081Z ep = _export_for_training( 2025-09-07T14:25:59.6724634Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1163, in wrapper 2025-09-07T14:25:59.6725210Z raise e 2025-09-07T14:25:59.6725693Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1129, in wrapper 2025-09-07T14:25:59.6726282Z ep = fn(*args, **kwargs) 2025-09-07T14:25:59.6726872Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/exported_program.py", line 124, in wrapper 2025-09-07T14:25:59.6727502Z return fn(*args, **kwargs) 2025-09-07T14:25:59.6728113Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 2071, in _export_for_training 2025-09-07T14:25:59.6728755Z export_artifact = export_func( 2025-09-07T14:25:59.6729593Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1415, in _strict_export 2025-09-07T14:25:59.6730233Z gm_torch_level = _export_to_torch_ir( 2025-09-07T14:25:59.6730870Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 812, in _export_to_torch_ir 2025-09-07T14:25:59.6731536Z gm_torch_level, _ = torch._dynamo.export( 2025-09-07T14:25:59.6732136Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 2002, in inner 2025-09-07T14:25:59.6732755Z result_traced = opt_f(*args, **kwargs) 2025-09-07T14:25:59.6733367Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 414, in __call__ 2025-09-07T14:25:59.6733992Z return super().__call__(*args, **kwargs) 2025-09-07T14:25:59.6734652Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:25:59.6735336Z return self._call_impl(*args, **kwargs) 2025-09-07T14:25:59.6743288Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:25:59.6744026Z return forward_call(*args, **kwargs) 2025-09-07T14:25:59.6744691Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 841, in compile_wrapper 2025-09-07T14:25:59.6745457Z raise e.with_traceback(None) from e.__cause__ # User compiler error 2025-09-07T14:25:59.6745945Z torch._dynamo.exc.Unsupported: copy.deepcopy() 2025-09-07T14:25:59.6746372Z Explanation: Dynamo does not support copy.deepcopy() 2025-09-07T14:25:59.6746757Z Hint: Avoid calling copy.deepcopy() 2025-09-07T14:25:59.6747608Z Hint: It may be possible to write Dynamo tracing rules for this code. Please report an issue to PyTorch if you encounter this graph break often and it is causing performance issues. 2025-09-07T14:25:59.6748545Z 2025-09-07T14:25:59.6748842Z Developer debug context: copy.deepcopy(UserDefinedObjectVariable(GenerationConfig)) 2025-09-07T14:25:59.6749261Z 2025-09-07T14:25:59.6749746Z For more details about this graph break, please visit: https://meta-pytorch.github.io/compile-graph-break-site/gb/gb0179.html 2025-09-07T14:25:59.6750313Z 2025-09-07T14:25:59.6750420Z from user code: 2025-09-07T14:25:59.6750940Z File "/torchbench/torchbenchmark/util/framework/huggingface/model_factory.py", line 194, in forward 2025-09-07T14:25:59.6751637Z return self.model.generate(inputs, self.generation_config) 2025-09-07T14:25:59.6752381Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context 2025-09-07T14:25:59.6753039Z return func(*args, **kwargs) 2025-09-07T14:25:59.6753654Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/generation/utils.py", line 2380, in generate 2025-09-07T14:25:59.6754418Z generation_config, model_kwargs = self._prepare_generation_config( 2025-09-07T14:25:59.6755371Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/generation/utils.py", line 1751, in _prepare_generation_config 2025-09-07T14:25:59.6756176Z generation_config = copy.deepcopy(generation_config) 2025-09-07T14:25:59.6756451Z 2025-09-07T14:25:59.6757082Z 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" 2025-09-07T14:25:59.6757818Z 2025-09-07T14:25:59.6758056Z TorchDynamo optimized model failed to run because of following error 2025-09-07T14:25:59.6951123Z fail_to_run 2025-09-07T14:26:01.4986517Z /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. 2025-09-07T14:26:01.4988026Z import pynvml # type: ignore[import] 2025-09-07T14:26:04.1062079Z 2025-09-07T14:26:15.8164803Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:26:15.8165206Z loading model: 0it [00:11, ?it/s] 2025-09-07T14:26:15.8309319Z cuda eval hf_T5_large 2025-09-07T14:26:15.9006788Z pass_due_to_skip 2025-09-07T14:26:17.6815569Z /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. 2025-09-07T14:26:17.6817056Z import pynvml # type: ignore[import] 2025-09-07T14:26:20.2950270Z 2025-09-07T14:26:22.8034069Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:26:22.8034464Z loading model: 0it [00:02, ?it/s] 2025-09-07T14:26:22.8054352Z cuda eval hf_Whisper 2025-09-07T14:26:28.1030691Z pass 2025-09-07T14:26:29.9140069Z /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. 2025-09-07T14:26:29.9141493Z import pynvml # type: ignore[import] 2025-09-07T14:26:32.5276759Z 2025-09-07T14:26:38.6999205Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:26:38.6999583Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:26:38.7098744Z cuda eval hf_distil_whisper 2025-09-07T14:26:47.6820154Z pass 2025-09-07T14:26:49.0038066Z accuracy pass_rate=62.50% 2025-09-07T14:26:49.0044328Z calls_captured gmean=0.00x mean=465.438x 2025-09-07T14:26:49.0048827Z unique_graphs gmean=0.00x mean=0.625x 2025-09-07T14:26:49.0053167Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T14:26:49.0057175Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T14:26:49.0061671Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T14:26:49.0065846Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T14:26:49.0069932Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T14:26:49.0071198Z compilation_latency mean=3.577 seconds 2025-09-07T14:26:49.8162038Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T14:26:50.3744483Z /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. 2025-09-07T14:26:50.3745913Z import pynvml # type: ignore[import] 2025-09-07T14:26:53.8910135Z /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. 2025-09-07T14:26:53.8911904Z import pynvml # type: ignore[import] 2025-09-07T14:26:56.4961790Z 2025-09-07T14:27:01.8893212Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:27:01.8893572Z loading model: 0it [00:05, ?it/s] 2025-09-07T14:27:01.8963030Z cuda eval hf_Bart 2025-09-07T14:27:32.9930684Z pass 2025-09-07T14:27:36.2114833Z /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. 2025-09-07T14:27:36.2116266Z import pynvml # type: ignore[import] 2025-09-07T14:27:38.8266847Z 2025-09-07T14:27:42.9033331Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:27:42.9033739Z loading model: 0it [00:04, ?it/s] 2025-09-07T14:27:42.9090769Z cuda eval hf_Bert 2025-09-07T14:28:05.5655503Z pass 2025-09-07T14:28:08.5670037Z /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. 2025-09-07T14:28:08.5671463Z import pynvml # type: ignore[import] 2025-09-07T14:28:11.1616159Z 2025-09-07T14:28:17.3489036Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:28:17.3489418Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:28:17.3595595Z cuda eval hf_Bert_large 2025-09-07T14:28:52.1210247Z pass 2025-09-07T14:28:55.4374726Z /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. 2025-09-07T14:28:55.4376166Z import pynvml # type: ignore[import] 2025-09-07T14:28:58.0326823Z 2025-09-07T14:28:59.7520921Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T14:28:59.7523403Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T14:28:59.7525292Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T14:28:59.7526473Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T14:28:59.7528707Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T14:28:59.7530915Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T14:28:59.7532384Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T14:28:59.7533655Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T14:29:02.5976983Z 2025-09-07T14:29:02.5977397Z loading model: 0it [00:04, ?it/s] 2025-09-07T14:29:02.6033555Z cuda eval hf_BigBird 2025-09-07T14:30:09.4146728Z pass 2025-09-07T14:30:13.6629921Z /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. 2025-09-07T14:30:13.6631338Z import pynvml # type: ignore[import] 2025-09-07T14:30:16.2558757Z 2025-09-07T14:30:19.7176325Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:30:19.7176729Z loading model: 0it [00:03, ?it/s] 2025-09-07T14:30:19.7205919Z cuda eval hf_DistilBert 2025-09-07T14:30:37.1804823Z pass 2025-09-07T14:30:40.3112111Z /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. 2025-09-07T14:30:40.3113551Z import pynvml # type: ignore[import] 2025-09-07T14:30:42.9154809Z 2025-09-07T14:30:48.9226041Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:30:48.9226421Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:30:48.9268557Z cuda eval hf_GPT2 2025-09-07T14:31:12.0890602Z pass 2025-09-07T14:31:15.2175252Z /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. 2025-09-07T14:31:15.2176674Z import pynvml # type: ignore[import] 2025-09-07T14:31:17.8111765Z 2025-09-07T14:31:33.8026818Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:31:33.8027192Z loading model: 0it [00:15, ?it/s] 2025-09-07T14:31:33.8148993Z cuda eval hf_GPT2_large 2025-09-07T14:31:33.8391198Z pass_due_to_skip 2025-09-07T14:31:35.7079422Z /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. 2025-09-07T14:31:35.7080903Z import pynvml # type: ignore[import] 2025-09-07T14:31:38.2930059Z 2025-09-07T14:31:46.2306244Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:31:46.2306608Z loading model: 0it [00:07, ?it/s] 2025-09-07T14:31:46.2362710Z cuda eval hf_Roberta_base 2025-09-07T14:32:12.1205833Z pass 2025-09-07T14:32:15.2256983Z /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. 2025-09-07T14:32:15.2258465Z import pynvml # type: ignore[import] 2025-09-07T14:32:17.8191357Z 2025-09-07T14:32:21.2597168Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:32:21.2597561Z loading model: 0it [00:03, ?it/s] 2025-09-07T14:32:21.2638110Z cuda eval hf_T5 2025-09-07T14:32:49.4050781Z pass 2025-09-07T14:32:52.6338720Z /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. 2025-09-07T14:32:52.6340145Z import pynvml # type: ignore[import] 2025-09-07T14:32:55.2249803Z 2025-09-07T14:33:00.7532305Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:33:00.7532720Z loading model: 0it [00:05, ?it/s] 2025-09-07T14:33:00.7533053Z cuda eval hf_T5_base 2025-09-07T14:33:00.7548878Z Traceback (most recent call last): 2025-09-07T14:33:00.7549497Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T14:33:00.7550092Z self.model_iter_fn(model, example_inputs) 2025-09-07T14:33:00.7550682Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 480, in forward_pass 2025-09-07T14:33:00.7551245Z return mod(**inputs) 2025-09-07T14:33:00.7551858Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:33:00.7552548Z return self._call_impl(*args, **kwargs) 2025-09-07T14:33:00.7553204Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:33:00.7553838Z return forward_call(*args, **kwargs) 2025-09-07T14:33:00.7554906Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T14:33:00.7555580Z decoder_outputs = self.decoder( 2025-09-07T14:33:00.7556239Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:33:00.7556932Z return self._call_impl(*args, **kwargs) 2025-09-07T14:33:00.7557568Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:33:00.7558195Z return forward_call(*args, **kwargs) 2025-09-07T14:33:00.7558862Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T14:33:00.7559537Z layer_outputs = layer_module( 2025-09-07T14:33:00.7560166Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T14:33:00.7560818Z return super().__call__(*args, **kwargs) 2025-09-07T14:33:00.7561494Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:33:00.7562169Z return self._call_impl(*args, **kwargs) 2025-09-07T14:33:00.7562800Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:33:00.7563660Z return forward_call(*args, **kwargs) 2025-09-07T14:33:00.7564326Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 705, in forward 2025-09-07T14:33:00.7564999Z cross_attention_outputs = self.layer[1]( 2025-09-07T14:33:00.7565681Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:33:00.7566492Z return self._call_impl(*args, **kwargs) 2025-09-07T14:33:00.7567132Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:33:00.7567774Z return forward_call(*args, **kwargs) 2025-09-07T14:33:00.7568419Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 635, in forward 2025-09-07T14:33:00.7569114Z attention_output = self.EncDecAttention( 2025-09-07T14:33:00.7569788Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:33:00.7570460Z return self._call_impl(*args, **kwargs) 2025-09-07T14:33:00.7571070Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:33:00.7571703Z return forward_call(*args, **kwargs) 2025-09-07T14:33:00.7572362Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 558, in forward 2025-09-07T14:33:00.7573261Z attn_weights = nn.functional.softmax(scores.float(), dim=-1).type_as(scores) 2025-09-07T14:33:00.7573999Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py", line 2133, in softmax 2025-09-07T14:33:00.7574575Z ret = input.softmax(dim) 2025-09-07T14:33:00.7576891Z torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 768.00 MiB. GPU 0 has a total capacity of 39.38 GiB of which 13.38 MiB is free. Including non-PyTorch memory, this process has 0 bytes memory in use. Of the allocated memory 38.27 GiB is allocated by PyTorch, and 583.88 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) 2025-09-07T14:33:00.7579308Z 2025-09-07T14:33:00.7579525Z The above exception was the direct cause of the following exception: 2025-09-07T14:33:00.7579872Z 2025-09-07T14:33:00.7579982Z Traceback (most recent call last): 2025-09-07T14:33:00.7580691Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T14:33:00.7581206Z ) = runner.load_model( 2025-09-07T14:33:00.7581715Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T14:33:00.7582291Z self.validate_model(model, example_inputs) 2025-09-07T14:33:00.7582864Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T14:33:00.7583455Z raise RuntimeError("Eager run failed") from e 2025-09-07T14:33:00.7583808Z RuntimeError: Eager run failed 2025-09-07T14:33:00.7583995Z 2025-09-07T14:33:00.7584082Z eager_fail_to_run 2025-09-07T14:33:02.5105733Z /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. 2025-09-07T14:33:02.5107195Z import pynvml # type: ignore[import] 2025-09-07T14:33:05.0989233Z 2025-09-07T14:33:16.8516533Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:33:16.8516894Z loading model: 0it [00:11, ?it/s] 2025-09-07T14:33:16.8664983Z cuda eval hf_T5_large 2025-09-07T14:33:16.8899679Z pass_due_to_skip 2025-09-07T14:33:18.6944165Z /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. 2025-09-07T14:33:18.6945569Z import pynvml # type: ignore[import] 2025-09-07T14:33:21.2870833Z 2025-09-07T14:33:23.9208593Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:33:23.9208971Z loading model: 0it [00:02, ?it/s] 2025-09-07T14:33:23.9228510Z cuda eval hf_Whisper 2025-09-07T14:33:39.7534953Z pass 2025-09-07T14:33:42.6948264Z /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. 2025-09-07T14:33:42.6949660Z import pynvml # type: ignore[import] 2025-09-07T14:33:45.2942593Z 2025-09-07T14:33:51.4587817Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:33:51.4588186Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:33:51.4685611Z cuda eval hf_distil_whisper 2025-09-07T14:34:29.7672377Z pass 2025-09-07T14:34:32.6711816Z accuracy pass_rate=76.92% 2025-09-07T14:34:32.6717860Z calls_captured gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6722361Z unique_graphs gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6727174Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6731197Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6735249Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6739549Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6743640Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T14:34:32.6744911Z compilation_latency mean=0.000 seconds 2025-09-07T14:34:33.4780621Z + [[ 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* ]] 2025-09-07T14:34:33.4782068Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T14:34:33.4783515Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T14:34:34.0360676Z /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. 2025-09-07T14:34:34.0362103Z import pynvml # type: ignore[import] 2025-09-07T14:34:37.5593126Z /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. 2025-09-07T14:34:37.5594548Z import pynvml # type: ignore[import] 2025-09-07T14:34:40.1537032Z 2025-09-07T14:34:45.5547090Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:34:45.5547491Z loading model: 0it [00:05, ?it/s] 2025-09-07T14:34:45.5615337Z cuda eval hf_Bart 2025-09-07T14:35:02.7691092Z Autotune Choices Stats: 2025-09-07T14:35:02.7692618Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.634880006313324, "best_triton_pos": 1, "best_triton_time": 0.8038399815559387, "best_triton_kernel": "triton_mm_1744", "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"} 2025-09-07T14:35:02.7835627Z AUTOTUNE mm(2048x768, 768x50272) 2025-09-07T14:35:02.7835939Z strides: [768, 1], [50304, 1] 2025-09-07T14:35:02.7836244Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T14:35:02.7836570Z mm 0.6349 ms 100.0% 2025-09-07T14:35:02.7837281Z triton_mm_1744 0.8038 ms 79.0% 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 2025-09-07T14:35:02.7838729Z triton_mm_1737 0.8509 ms 74.6% 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=3, num_warps=4 2025-09-07T14:35:02.7839924Z triton_mm_1743 0.9052 ms 70.1% 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 2025-09-07T14:35:02.7841116Z triton_mm_1740 0.9677 ms 65.6% 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 2025-09-07T14:35:02.7842300Z triton_mm_1739 0.9933 ms 63.9% 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 2025-09-07T14:35:02.7843739Z triton_mm_1745 1.0035 ms 63.3% 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 2025-09-07T14:35:02.7844942Z triton_mm_1738 1.1418 ms 55.6% 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 2025-09-07T14:35:02.7846241Z triton_mm_1742 1.1766 ms 54.0% 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=2, num_warps=8 2025-09-07T14:35:02.7847438Z triton_mm_1741 1.1909 ms 53.3% 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 2025-09-07T14:35:02.7848457Z SingleProcess AUTOTUNE benchmarking takes 0.7925 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T14:35:06.6166147Z pass 2025-09-07T14:35:09.8164669Z /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. 2025-09-07T14:35:09.8166160Z import pynvml # type: ignore[import] 2025-09-07T14:35:12.4214720Z 2025-09-07T14:35:16.4011614Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:35:16.4011986Z loading model: 0it [00:03, ?it/s] 2025-09-07T14:35:16.4067942Z cuda eval hf_Bert 2025-09-07T14:35:31.3269114Z Autotune Choices Stats: 2025-09-07T14:35:31.3270631Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_mm_11", "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"} 2025-09-07T14:35:31.3381797Z AUTOTUNE addmm(2048x768, 2048x768, 768x768) 2025-09-07T14:35:31.3382172Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T14:35:31.3382542Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T14:35:31.3382929Z bias_addmm 0.0215 ms 100.0% 2025-09-07T14:35:31.3383666Z triton_mm_11 0.0225 ms 95.5% 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 2025-09-07T14:35:31.3384855Z triton_mm_17 0.0225 ms 95.5% 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 2025-09-07T14:35:31.3386019Z triton_mm_9 0.0236 ms 91.3% 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=3, num_warps=4 2025-09-07T14:35:31.3387178Z triton_mm_12 0.0236 ms 91.3% 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 2025-09-07T14:35:31.3388601Z triton_mm_16 0.0236 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=3, num_warps=4 2025-09-07T14:35:31.3389791Z triton_mm_10 0.0256 ms 84.0% 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 2025-09-07T14:35:31.3390962Z triton_mm_13 0.0256 ms 84.0% 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=4, num_warps=8 2025-09-07T14:35:31.3392125Z triton_mm_15 0.0256 ms 84.0% 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 2025-09-07T14:35:31.3392870Z addmm 0.0287 ms 75.0% 2025-09-07T14:35:31.3393402Z SingleProcess AUTOTUNE benchmarking takes 0.3363 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T14:35:34.1277080Z pass 2025-09-07T14:35:37.2316379Z /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. 2025-09-07T14:35:37.2318142Z import pynvml # type: ignore[import] 2025-09-07T14:35:39.8291915Z 2025-09-07T14:35:46.0115280Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:35:46.0115614Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:35:46.0223227Z cuda eval hf_Bert_large 2025-09-07T14:36:09.9222331Z Autotune Choices Stats: 2025-09-07T14:36:09.9223558Z {"num_choices": 20, "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=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.03481600061058998, "best_triton_pos": 0} 2025-09-07T14:36:09.9329632Z AUTOTUNE addmm(2048x1024, 2048x1024, 1024x1024) 2025-09-07T14:36:09.9330029Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T14:36:09.9330423Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T14:36:09.9331625Z triton_mm_11 0.0348 ms 100.0% 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 2025-09-07T14:36:09.9332825Z triton_mm_12 0.0358 ms 97.1% 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=3, num_warps=4 2025-09-07T14:36:09.9333579Z bias_addmm 0.0379 ms 91.9% 2025-09-07T14:36:09.9334279Z triton_mm_9 0.0379 ms 91.9% 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 2025-09-07T14:36:09.9335433Z triton_mm_6 0.0399 ms 87.2% 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 2025-09-07T14:36:09.9336610Z triton_mm_16 0.0399 ms 87.2% 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 2025-09-07T14:36:09.9337879Z triton_mm_7 0.0410 ms 85.0% 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 2025-09-07T14:36:09.9339044Z triton_mm_10 0.0410 ms 85.0% 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 2025-09-07T14:36:09.9340212Z triton_mm_13 0.0430 ms 81.0% 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=4, num_warps=8 2025-09-07T14:36:09.9341380Z triton_mm_15 0.0430 ms 81.0% 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 2025-09-07T14:36:09.9342497Z SingleProcess AUTOTUNE benchmarking takes 0.3666 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T14:36:14.7247554Z pass 2025-09-07T14:36:18.1966706Z /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. 2025-09-07T14:36:18.1968128Z import pynvml # type: ignore[import] 2025-09-07T14:36:20.7896500Z 2025-09-07T14:36:22.5127958Z loading model: 0it [00:00, ?it/s]BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T14:36:22.5130252Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T14:36:22.5132083Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T14:36:22.5133241Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T14:36:22.5135457Z WARNING:transformers.modeling_utils:BigBirdForMaskedLM has generative capabilities, as `prepare_inputs_for_generation` is explicitly defined. However, it doesn't directly inherit from `GenerationMixin`. From 👉v4.50👈 onwards, `PreTrainedModel` will NOT inherit from `GenerationMixin`, and this model will lose the ability to call `generate` and other related functions. 2025-09-07T14:36:22.5137970Z - If you're using `trust_remote_code=True`, you can get rid of this warning by loading the model with an auto class. See https://huggingface.co/docs/transformers/en/model_doc/auto#auto-classes 2025-09-07T14:36:22.5139434Z - If you are the owner of the model architecture code, please modify your model class such that it inherits from `GenerationMixin` (after `PreTrainedModel`, otherwise you'll get an exception). 2025-09-07T14:36:22.5140579Z - If you are not the owner of the model architecture class, please contact the model code owner to update it. 2025-09-07T14:36:25.3632375Z 2025-09-07T14:36:25.3632757Z loading model: 0it [00:04, ?it/s] 2025-09-07T14:36:25.3689131Z cuda eval hf_BigBird 2025-09-07T14:37:14.7268114Z Autotune Choices Stats: 2025-09-07T14:37:14.7269642Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.1013759970664978, "best_triton_pos": 1, "best_triton_time": 0.11776000261306763, "best_triton_kernel": "triton_mm_34", "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"} 2025-09-07T14:37:14.7380011Z AUTOTUNE addmm(16384x768, 16384x768, 768x768) 2025-09-07T14:37:14.7380393Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T14:37:14.7380749Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T14:37:14.7381133Z bias_addmm 0.1014 ms 100.0% 2025-09-07T14:37:14.7381869Z triton_mm_34 0.1178 ms 86.1% 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=3, num_warps=4 2025-09-07T14:37:14.7383052Z triton_mm_27 0.1229 ms 82.5% 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 2025-09-07T14:37:14.7384216Z triton_mm_30 0.1229 ms 82.5% 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=3, num_warps=4 2025-09-07T14:37:14.7385656Z triton_mm_33 0.1229 ms 82.5% 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 2025-09-07T14:37:14.7386826Z triton_mm_29 0.1290 ms 78.6% 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 2025-09-07T14:37:14.7388002Z triton_mm_35 0.1311 ms 77.3% 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 2025-09-07T14:37:14.7389170Z triton_mm_31 0.1475 ms 68.7% 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 2025-09-07T14:37:14.7389908Z addmm 0.1546 ms 65.6% 2025-09-07T14:37:14.7390598Z triton_mm_28 0.1546 ms 65.6% 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 2025-09-07T14:37:14.7391693Z SingleProcess AUTOTUNE benchmarking takes 0.6122 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T14:37:17.7174809Z Autotune Choices Stats: 2025-09-07T14:37:17.7176303Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 5.223423957824707, "best_triton_pos": 1, "best_triton_time": 6.558720111846924, "best_triton_kernel": "triton_mm_4497", "best_triton_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"} 2025-09-07T14:37:17.7288075Z AUTOTUNE addmm(16384x50360, 16384x768, 768x50360) 2025-09-07T14:37:17.7288469Z strides: [0, 1], [768, 1], [50368, 1] 2025-09-07T14:37:17.7288869Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T14:37:17.7289240Z bias_addmm 5.2234 ms 100.0% 2025-09-07T14:37:17.7290296Z triton_mm_4497 6.5587 ms 79.6% 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 2025-09-07T14:37:17.7291516Z triton_mm_4491 7.3994 ms 70.6% 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=3, num_warps=4 2025-09-07T14:37:17.7292714Z triton_mm_4498 7.7076 ms 67.8% 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 2025-09-07T14:37:17.7293919Z triton_mm_4494 8.4716 ms 61.7% 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 2025-09-07T14:37:17.7295105Z triton_mm_4499 8.8801 ms 58.8% 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 2025-09-07T14:37:17.7296305Z triton_mm_4493 8.9375 ms 58.4% 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 2025-09-07T14:37:17.7297040Z addmm 9.3102 ms 56.1% 2025-09-07T14:37:17.7297816Z triton_mm_4492 10.4376 ms 50.0% 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 2025-09-07T14:37:17.7299011Z triton_mm_4495 10.8524 ms 48.1% 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 2025-09-07T14:37:17.7300045Z SingleProcess AUTOTUNE benchmarking takes 2.2247 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T14:37:31.1074745Z pass 2025-09-07T14:37:36.1130727Z /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. 2025-09-07T14:37:36.1132313Z import pynvml # type: ignore[import] 2025-09-07T14:37:38.7051200Z 2025-09-07T14:37:42.1901897Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:37:42.1902281Z loading model: 0it [00:03, ?it/s] 2025-09-07T14:37:42.1932403Z cuda eval hf_DistilBert 2025-09-07T14:37:53.7526325Z pass 2025-09-07T14:37:56.6503165Z /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. 2025-09-07T14:37:56.6504579Z import pynvml # type: ignore[import] 2025-09-07T14:37:59.2521078Z 2025-09-07T14:38:05.2622781Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:38:05.2623159Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:38:05.2666463Z cuda eval hf_GPT2 2025-09-07T14:38:19.1871423Z Autotune Choices Stats: 2025-09-07T14:38:19.1872897Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.638975977897644, "best_triton_pos": 1, "best_triton_time": 0.8427519798278809, "best_triton_kernel": "triton_mm_880", "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"} 2025-09-07T14:38:19.1983459Z AUTOTUNE mm(2048x768, 768x50264) 2025-09-07T14:38:19.1983776Z strides: [768, 1], [50304, 1] 2025-09-07T14:38:19.1984098Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T14:38:19.1984412Z mm 0.6390 ms 100.0% 2025-09-07T14:38:19.1985128Z triton_mm_880 0.8428 ms 75.8% 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 2025-09-07T14:38:19.1986694Z triton_mm_873 0.8632 ms 74.0% 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 2025-09-07T14:38:19.1987883Z triton_mm_879 0.8899 ms 71.8% 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 2025-09-07T14:38:19.1989068Z triton_mm_875 0.9748 ms 65.5% 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 2025-09-07T14:38:19.1990245Z triton_mm_881 1.0076 ms 63.4% 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 2025-09-07T14:38:19.1991432Z triton_mm_876 1.0127 ms 63.1% 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=3, num_warps=4 2025-09-07T14:38:19.1992615Z triton_mm_874 1.1418 ms 56.0% 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 2025-09-07T14:38:19.1993795Z triton_mm_878 1.1776 ms 54.3% 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=2, num_warps=8 2025-09-07T14:38:19.1994973Z triton_mm_877 1.2124 ms 52.7% 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 2025-09-07T14:38:19.1995982Z SingleProcess AUTOTUNE benchmarking takes 0.7990 seconds and 0.0169 seconds precompiling for 19 choices 2025-09-07T14:38:22.0754069Z pass 2025-09-07T14:38:25.3049550Z /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. 2025-09-07T14:38:25.3053155Z import pynvml # type: ignore[import] 2025-09-07T14:38:27.8960890Z 2025-09-07T14:38:43.8130858Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:38:43.8131228Z loading model: 0it [00:15, ?it/s] 2025-09-07T14:38:43.8252821Z cuda eval hf_GPT2_large 2025-09-07T14:38:43.8489569Z pass_due_to_skip 2025-09-07T14:38:45.7392437Z /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. 2025-09-07T14:38:45.7393847Z import pynvml # type: ignore[import] 2025-09-07T14:38:48.3406391Z 2025-09-07T14:38:53.1993369Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:38:53.1993752Z loading model: 0it [00:04, ?it/s] 2025-09-07T14:38:53.2421479Z cuda eval hf_Longformer 2025-09-07T14:38:55.5917728Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T14:38:55.5918856Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T14:38:55.5919748Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] or: 2025-09-07T14:38:55.5920605Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T14:38:55.5921636Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] to include these operations in the captured graph. 2025-09-07T14:38:55.5922482Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] 2025-09-07T14:38:55.5923533Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] Graph break: from user code at: 2025-09-07T14:38:55.5925193Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 480, in forward_pass 2025-09-07T14:38:55.5926372Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] return mod(**inputs) 2025-09-07T14:38:55.5927740Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1703, in forward 2025-09-07T14:38:55.5929154Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] outputs = self.longformer( 2025-09-07T14:38:55.5930529Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1600, in forward 2025-09-07T14:38:55.5931933Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] encoder_outputs = self.encoder( 2025-09-07T14:38:55.5933338Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/longformer/modeling_longformer.py", line 1244, in forward 2025-09-07T14:38:55.5934822Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] is_global_attn = is_index_global_attn.flatten().any().item() 2025-09-07T14:38:55.5935712Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] 2025-09-07T14:38:55.5936370Z W0907 14:38:55.591000 235103 site-packages/torch/_dynamo/variables/tensor.py:1048] [0/0] 2025-09-07T14:39:54.0931645Z Autotune Choices Stats: 2025-09-07T14:39:54.0933194Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 4.989952087402344, "best_triton_pos": 1, "best_triton_time": 6.445055961608887, "best_triton_kernel": "triton_mm_1773", "best_triton_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"} 2025-09-07T14:39:54.1045395Z AUTOTUNE addmm(16384x50272, 16384x768, 768x50272) 2025-09-07T14:39:54.1045755Z strides: [0, 1], [768, 1], [50304, 1] 2025-09-07T14:39:54.1046125Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T14:39:54.1046507Z bias_addmm 4.9900 ms 100.0% 2025-09-07T14:39:54.1047256Z triton_mm_1773 6.4451 ms 77.4% 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 2025-09-07T14:39:54.1048456Z triton_mm_1774 7.4598 ms 66.9% 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=3, num_warps=4 2025-09-07T14:39:54.1049914Z triton_mm_1767 7.5090 ms 66.5% 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 2025-09-07T14:39:54.1051096Z triton_mm_1770 8.2186 ms 60.7% 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 2025-09-07T14:39:54.1052289Z triton_mm_1775 8.5688 ms 58.2% 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=5, num_warps=8 2025-09-07T14:39:54.1053486Z triton_mm_1769 8.8525 ms 56.4% 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 2025-09-07T14:39:54.1054234Z addmm 9.4689 ms 52.7% 2025-09-07T14:39:54.1055141Z triton_mm_1768 10.1059 ms 49.4% 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=4, num_warps=8 2025-09-07T14:39:54.1056331Z triton_mm_1771 10.4131 ms 47.9% 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 2025-09-07T14:39:54.1057450Z SingleProcess AUTOTUNE benchmarking takes 2.2171 seconds and 0.7876 seconds precompiling for 20 choices 2025-09-07T14:39:55.3705252Z pass 2025-09-07T14:39:59.5027117Z /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. 2025-09-07T14:39:59.5028547Z import pynvml # type: ignore[import] 2025-09-07T14:40:02.0941401Z 2025-09-07T14:40:03.9981063Z loading model: 0it [00:00, ?it/s]Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T14:40:03.9983334Z WARNING:transformers.models.reformer.modeling_reformer:Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.58.0. You should pass an instance of `ReformerDynamicCache` instead, e.g. `past_key_values=ReformerDynamicCache.from_legacy_cache(past_key_values)`. 2025-09-07T14:40:04.4999865Z 2025-09-07T14:40:04.5000237Z loading model: 0it [00:02, ?it/s] 2025-09-07T14:40:04.5028046Z cuda eval hf_Reformer 2025-09-07T14:40:12.3161143Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T14:40:12.3164936Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T14:40:12.3165854Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] or: 2025-09-07T14:40:12.3166706Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T14:40:12.3167736Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] to include these operations in the captured graph. 2025-09-07T14:40:12.3168593Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] 2025-09-07T14:40:12.3169387Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] Graph break: from user code at: 2025-09-07T14:40:12.3170897Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 2132, in torch_dynamo_resume_in_forward_at_2104 2025-09-07T14:40:12.3172595Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] embedding_output = self.embeddings( 2025-09-07T14:40:12.3173987Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 369, in forward 2025-09-07T14:40:12.3175462Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] position_embeddings = self.position_embeddings(position_ids) 2025-09-07T14:40:12.3176947Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 293, in forward 2025-09-07T14:40:12.3178454Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] max_position_id = position_ids.max().item() 2025-09-07T14:40:12.3179503Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] 2025-09-07T14:40:12.3180177Z W0907 14:40:12.315000 235673 site-packages/torch/_dynamo/variables/tensor.py:1048] [4/0] 2025-09-07T14:40:23.4340509Z Autotune Choices Stats: 2025-09-07T14:40:23.4342019Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.048128001391887665, "best_triton_pos": 1, "best_triton_time": 0.048128001391887665, "best_triton_kernel": "triton_mm_15", "best_triton_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"} 2025-09-07T14:40:23.4456007Z AUTOTUNE mm(16384x256, 256x768) 2025-09-07T14:40:23.4456378Z strides: [256, 1], [1, 256] 2025-09-07T14:40:23.4456695Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T14:40:23.4457034Z mm 0.0481 ms 100.0% 2025-09-07T14:40:23.4457810Z triton_mm_15 0.0481 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 2025-09-07T14:40:23.4459001Z triton_mm_16 0.0481 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 2025-09-07T14:40:23.4460182Z triton_mm_9 0.0492 ms 97.9% 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 2025-09-07T14:40:23.4461362Z triton_mm_11 0.0492 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 2025-09-07T14:40:23.4462525Z triton_mm_12 0.0492 ms 97.9% 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=3, num_warps=4 2025-09-07T14:40:23.4463975Z triton_mm_10 0.0553 ms 87.0% 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 2025-09-07T14:40:23.4465150Z triton_mm_13 0.0573 ms 83.9% 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 2025-09-07T14:40:23.4466324Z triton_mm_14 0.0594 ms 81.0% 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=2, num_warps=8 2025-09-07T14:40:23.4467496Z triton_mm_17 0.0594 ms 81.0% 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 2025-09-07T14:40:23.4468510Z SingleProcess AUTOTUNE benchmarking takes 0.3910 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T14:40:23.7817570Z Autotune Choices Stats: 2025-09-07T14:40:23.7818800Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_174", "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": 0.04505600035190582, "best_triton_pos": 0} 2025-09-07T14:40:23.7927838Z AUTOTUNE bmm(12x16384x64, 12x64x64) 2025-09-07T14:40:23.7928169Z strides: [64, 768, 1], [4096, 64, 1] 2025-09-07T14:40:23.7928480Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T14:40:23.7929255Z triton_bmm_174 0.0451 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 2025-09-07T14:40:23.7930470Z triton_bmm_175 0.0451 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=5, num_warps=8 2025-09-07T14:40:23.7931672Z triton_bmm_166 0.0461 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 2025-09-07T14:40:23.7933087Z triton_bmm_169 0.0461 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=3, num_warps=4 2025-09-07T14:40:23.7934267Z triton_bmm_170 0.0461 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=4, num_warps=4 2025-09-07T14:40:23.7935429Z triton_bmm_165 0.0471 ms 95.7% 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 2025-09-07T14:40:23.7936604Z triton_bmm_171 0.0502 ms 89.8% 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 2025-09-07T14:40:23.7937877Z triton_bmm_167 0.0512 ms 88.0% 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 2025-09-07T14:40:23.7939063Z triton_bmm_172 0.0512 ms 88.0% 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=4, num_warps=8 2025-09-07T14:40:23.7940240Z triton_bmm_159 0.0522 ms 86.3% 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 2025-09-07T14:40:23.7941254Z SingleProcess AUTOTUNE benchmarking takes 0.3279 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T14:40:26.1916671Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter.src Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1841, in torch_dynamo_resume_in_forward_at_1837 2025-09-07T14:40:26.1918486Z hidden_states = _ReversibleFunction.apply( 2025-09-07T14:40:26.1919271Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1722, in forward 2025-09-07T14:40:26.1920015Z layer_outputs = layer( 2025-09-07T14:40:26.1920706Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1587, in forward 2025-09-07T14:40:26.1921446Z attn_outputs = self.attention( 2025-09-07T14:40:26.1922159Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 1417, in forward 2025-09-07T14:40:26.1923165Z self_attention_outputs = self.self_attention( 2025-09-07T14:40:26.1923927Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 587, in forward 2025-09-07T14:40:26.1924875Z sorted_bucket_idx, undo_sorted_bucket_idx = self._get_sorted_bucket_idx_and_undo_sorted_bucket_idx( 2025-09-07T14:40:26.1926128Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/reformer/modeling_reformer.py", line 807, in _get_sorted_bucket_idx_and_undo_sorted_bucket_idx 2025-09-07T14:40:26.1927116Z undo_sorted_bucket_idx.scatter_(-1, sorted_bucket_idx, indices) 2025-09-07T14:40:26.1927429Z 2025-09-07T14:40:26.1927434Z 2025-09-07T14:40:27.8350380Z pass 2025-09-07T14:40:30.9041651Z /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. 2025-09-07T14:40:30.9043274Z import pynvml # type: ignore[import] 2025-09-07T14:40:33.4889444Z 2025-09-07T14:40:41.4496363Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:40:41.4496767Z loading model: 0it [00:07, ?it/s] 2025-09-07T14:40:41.4555896Z cuda eval hf_Roberta_base 2025-09-07T14:40:58.9855085Z pass 2025-09-07T14:41:02.1135281Z /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. 2025-09-07T14:41:02.1136740Z import pynvml # type: ignore[import] 2025-09-07T14:41:04.7136734Z 2025-09-07T14:41:08.1488942Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:41:08.1489314Z loading model: 0it [00:03, ?it/s] 2025-09-07T14:41:08.1528447Z cuda eval hf_T5 2025-09-07T14:41:32.5810331Z pass 2025-09-07T14:41:35.8784441Z /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. 2025-09-07T14:41:35.8785844Z import pynvml # type: ignore[import] 2025-09-07T14:41:38.4703695Z 2025-09-07T14:41:44.0886080Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:41:44.0886471Z loading model: 0it [00:05, ?it/s] 2025-09-07T14:41:44.0886797Z cuda eval hf_T5_base 2025-09-07T14:41:44.0901730Z Traceback (most recent call last): 2025-09-07T14:41:44.0902309Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T14:41:44.0902905Z self.model_iter_fn(model, example_inputs) 2025-09-07T14:41:44.0903494Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 480, in forward_pass 2025-09-07T14:41:44.0904088Z return mod(**inputs) 2025-09-07T14:41:44.0904722Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:41:44.0905718Z return self._call_impl(*args, **kwargs) 2025-09-07T14:41:44.0906339Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:41:44.0906996Z return forward_call(*args, **kwargs) 2025-09-07T14:41:44.0907667Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1762, in forward 2025-09-07T14:41:44.0908349Z decoder_outputs = self.decoder( 2025-09-07T14:41:44.0908992Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:41:44.0909675Z return self._call_impl(*args, **kwargs) 2025-09-07T14:41:44.0910302Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:41:44.0910941Z return forward_call(*args, **kwargs) 2025-09-07T14:41:44.0911606Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 1092, in forward 2025-09-07T14:41:44.0912263Z layer_outputs = layer_module( 2025-09-07T14:41:44.0912883Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/modeling_layers.py", line 94, in __call__ 2025-09-07T14:41:44.0913643Z return super().__call__(*args, **kwargs) 2025-09-07T14:41:44.0914318Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:41:44.0914995Z return self._call_impl(*args, **kwargs) 2025-09-07T14:41:44.0915612Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:41:44.0916248Z return forward_call(*args, **kwargs) 2025-09-07T14:41:44.0916910Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 705, in forward 2025-09-07T14:41:44.0917600Z cross_attention_outputs = self.layer[1]( 2025-09-07T14:41:44.0918268Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:41:44.0918952Z return self._call_impl(*args, **kwargs) 2025-09-07T14:41:44.0919787Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:41:44.0920425Z return forward_call(*args, **kwargs) 2025-09-07T14:41:44.0921090Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 635, in forward 2025-09-07T14:41:44.0921768Z attention_output = self.EncDecAttention( 2025-09-07T14:41:44.0922454Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:41:44.0923418Z return self._call_impl(*args, **kwargs) 2025-09-07T14:41:44.0924057Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:41:44.0924689Z return forward_call(*args, **kwargs) 2025-09-07T14:41:44.0925353Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/transformers/models/t5/modeling_t5.py", line 558, in forward 2025-09-07T14:41:44.0926177Z attn_weights = nn.functional.softmax(scores.float(), dim=-1).type_as(scores) 2025-09-07T14:41:44.0926914Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py", line 2133, in softmax 2025-09-07T14:41:44.0927513Z ret = input.softmax(dim) 2025-09-07T14:41:44.0929831Z torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 768.00 MiB. GPU 0 has a total capacity of 39.38 GiB of which 13.38 MiB is free. Including non-PyTorch memory, this process has 0 bytes memory in use. Of the allocated memory 38.27 GiB is allocated by PyTorch, and 583.88 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) 2025-09-07T14:41:44.0932230Z 2025-09-07T14:41:44.0932447Z The above exception was the direct cause of the following exception: 2025-09-07T14:41:44.0932783Z 2025-09-07T14:41:44.0932915Z Traceback (most recent call last): 2025-09-07T14:41:44.0933400Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T14:41:44.0933913Z ) = runner.load_model( 2025-09-07T14:41:44.0934422Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T14:41:44.0935013Z self.validate_model(model, example_inputs) 2025-09-07T14:41:44.0935586Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T14:41:44.0936170Z raise RuntimeError("Eager run failed") from e 2025-09-07T14:41:44.0936532Z RuntimeError: Eager run failed 2025-09-07T14:41:44.0936734Z 2025-09-07T14:41:44.0936826Z eager_fail_to_run 2025-09-07T14:41:45.8555000Z /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. 2025-09-07T14:41:45.8556631Z import pynvml # type: ignore[import] 2025-09-07T14:41:48.4504056Z 2025-09-07T14:41:51.4488941Z loading model: 0it [00:00, ?it/s]`generation_config` default values have been modified to match model-specific defaults: {'eos_token_id': 1}. If this is not desired, please set these values explicitly. 2025-09-07T14:41:51.4490555Z WARNING:transformers.generation.utils:`generation_config` default values have been modified to match model-specific defaults: {'eos_token_id': 1}. If this is not desired, please set these values explicitly. 2025-09-07T14:41:55.7277792Z 2025-09-07T14:41:55.7278165Z loading model: 0it [00:07, ?it/s] 2025-09-07T14:41:55.7319691Z cuda eval hf_T5_generate 2025-09-07T14:43:15.6762013Z CUDAGraph supports dynamic shapes by recording a new graph for each distinct input size. Recording too many CUDAGraphs may lead to extra overhead. We have observed 51 distinct sizes. Please consider the following options for better performance: a) padding inputs to a few fixed number of shapes; or b) set torch._inductor.config.triton.cudagraph_skip_dynamic_graphs=True. Set torch._inductor.config.triton.cudagraph_dynamic_shape_warn_limit=None to silence this warning. 2025-09-07T14:43:15.6911541Z CUDAGraph supports dynamic shapes by recording a new graph for each distinct input size. Recording too many CUDAGraphs may lead to extra overhead. We have observed 51 distinct sizes. Please consider the following options for better performance: a) padding inputs to a few fixed number of shapes; or b) set torch._inductor.config.triton.cudagraph_skip_dynamic_graphs=True. Set torch._inductor.config.triton.cudagraph_dynamic_shape_warn_limit=None to silence this warning. 2025-09-07T14:43:15.7013919Z CUDAGraph supports dynamic shapes by recording a new graph for each distinct input size. Recording too many CUDAGraphs may lead to extra overhead. We have observed 51 distinct sizes. Please consider the following options for better performance: a) padding inputs to a few fixed number of shapes; or b) set torch._inductor.config.triton.cudagraph_skip_dynamic_graphs=True. Set torch._inductor.config.triton.cudagraph_dynamic_shape_warn_limit=None to silence this warning. 2025-09-07T14:43:27.8243377Z pass 2025-09-07T14:43:31.5045460Z /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. 2025-09-07T14:43:31.5047098Z import pynvml # type: ignore[import] 2025-09-07T14:43:34.1391968Z 2025-09-07T14:43:45.8638302Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:43:45.8638920Z loading model: 0it [00:11, ?it/s] 2025-09-07T14:43:45.8787838Z cuda eval hf_T5_large 2025-09-07T14:43:45.9026215Z pass_due_to_skip 2025-09-07T14:43:47.6886008Z /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. 2025-09-07T14:43:47.6887495Z import pynvml # type: ignore[import] 2025-09-07T14:43:50.2892386Z 2025-09-07T14:43:52.7986038Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:43:52.7986408Z loading model: 0it [00:02, ?it/s] 2025-09-07T14:43:52.8006367Z cuda eval hf_Whisper 2025-09-07T14:44:03.6764996Z pass 2025-09-07T14:44:06.5765309Z /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. 2025-09-07T14:44:06.5766998Z import pynvml # type: ignore[import] 2025-09-07T14:44:09.1676583Z 2025-09-07T14:44:15.3157241Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:44:15.3157625Z loading model: 0it [00:06, ?it/s] 2025-09-07T14:44:15.3254075Z cuda eval hf_distil_whisper 2025-09-07T14:44:43.7476590Z pass 2025-09-07T14:44:46.7405244Z accuracy pass_rate=81.25% 2025-09-07T14:44:46.7412066Z calls_captured gmean=0.00x mean=722.000x 2025-09-07T14:44:46.7416386Z unique_graphs gmean=0.00x mean=2.062x 2025-09-07T14:44:46.7420989Z graph_breaks gmean=0.00x mean=1.438x 2025-09-07T14:44:46.7425142Z unique_graph_breaks gmean=0.00x mean=0.562x 2025-09-07T14:44:46.7429304Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T14:44:46.7433415Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T14:44:46.7437486Z cudagraph_skips gmean=0.00x mean=0.125x 2025-09-07T14:44:46.7438999Z compilation_latency mean=23.079 seconds 2025-09-07T14:44:47.5865001Z + [[ 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* ]] 2025-09-07T14:44:47.5866547Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T14:44:47.5868065Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --quant --backend inductor --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv 2025-09-07T14:44:48.1459348Z /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. 2025-09-07T14:44:48.1460763Z import pynvml # type: ignore[import] 2025-09-07T14:44:50.6823021Z usage: torchbench.py 2025-09-07T14:44:50.6823360Z [-h] 2025-09-07T14:44:50.6823597Z [--filter FILTER] 2025-09-07T14:44:50.6823848Z [--exclude EXCLUDE] 2025-09-07T14:44:50.6824131Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T14:44:50.6824515Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T14:44:50.6824916Z [--partition-id PARTITION_ID] 2025-09-07T14:44:50.6825210Z [--devices DEVICES] 2025-09-07T14:44:50.6825485Z [--device-index DEVICE_INDEX] 2025-09-07T14:44:50.6825788Z [--repeat REPEAT] 2025-09-07T14:44:50.6826085Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T14:44:50.6826419Z [--randomize-input] 2025-09-07T14:44:50.6826684Z [--threads THREADS] 2025-09-07T14:44:50.6826938Z [--nopython] 2025-09-07T14:44:50.6827490Z [--no-skip] 2025-09-07T14:44:50.6827716Z [--prims-nvfuser] 2025-09-07T14:44:50.6828007Z [--dump-raw-metrics] 2025-09-07T14:44:50.6828274Z [--log-operator-inputs] 2025-09-07T14:44:50.6828565Z [--channels-last] 2025-09-07T14:44:50.6828842Z [--batch-size BATCH_SIZE] 2025-09-07T14:44:50.6829136Z [--iterations ITERATIONS] 2025-09-07T14:44:50.6829431Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T14:44:50.6829742Z [--cosine] 2025-09-07T14:44:50.6829971Z [--freezing] 2025-09-07T14:44:50.6830230Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T14:44:50.6830523Z [--ci] 2025-09-07T14:44:50.6830739Z [--dashboard] 2025-09-07T14:44:50.6830988Z [--skip-fp64-check] 2025-09-07T14:44:50.6831246Z [--fast] 2025-09-07T14:44:50.6831454Z [--only ONLY] 2025-09-07T14:44:50.6831699Z [--multiprocess] 2025-09-07T14:44:50.6831942Z [--ddp] 2025-09-07T14:44:50.6832165Z [--fsdp] 2025-09-07T14:44:50.6832413Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T14:44:50.6832817Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T14:44:50.6833194Z [--dynamic-shapes] 2025-09-07T14:44:50.6833586Z [--propagate-real-tensors] 2025-09-07T14:44:50.6833885Z [--dynamic-batch-only] 2025-09-07T14:44:50.6834167Z [--specialize-int] 2025-09-07T14:44:50.6834430Z [--use-eval-mode] 2025-09-07T14:44:50.6834696Z [--skip-accuracy-check] 2025-09-07T14:44:50.6834985Z [--generate-aot-autograd-stats] 2025-09-07T14:44:50.6835302Z [--inductor-settings] 2025-09-07T14:44:50.6835575Z [--suppress-errors] 2025-09-07T14:44:50.6835835Z [--output OUTPUT] 2025-09-07T14:44:50.6836106Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T14:44:50.6836425Z [--disable-output] 2025-09-07T14:44:50.6836688Z [--baseline BASELINE] 2025-09-07T14:44:50.6836953Z [--part PART] 2025-09-07T14:44:50.6837197Z [--export-profiler-trace] 2025-09-07T14:44:50.6837533Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T14:44:50.6837880Z [--profile-details] 2025-09-07T14:44:50.6838157Z [--export-perfdoctor] 2025-09-07T14:44:50.6838431Z [--diff-branch DIFF_BRANCH] 2025-09-07T14:44:50.6838918Z [--tag TAG] 2025-09-07T14:44:50.6839146Z [--explain] 2025-09-07T14:44:50.6839370Z [--stats] 2025-09-07T14:44:50.6839598Z [--use-warm-peak-memory] 2025-09-07T14:44:50.6839881Z [--print-memory] 2025-09-07T14:44:50.6840148Z [--print-compilation-time] 2025-09-07T14:44:50.6840459Z [--print-dataframe-summary] 2025-09-07T14:44:50.6840747Z [--disable-cudagraphs] 2025-09-07T14:44:50.6841040Z [--disable-split-reductions] 2025-09-07T14:44:50.6841368Z [--disable-persistent-reductions] 2025-09-07T14:44:50.6841702Z [--disable-divisible-by-16] 2025-09-07T14:44:50.6842042Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T14:44:50.6842404Z [--print-graph-breaks] 2025-09-07T14:44:50.6842693Z [--log-graph-breaks] 2025-09-07T14:44:50.6843244Z [--trace-on-xla] 2025-09-07T14:44:50.6843507Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T14:44:50.6843826Z [--collect-outputs] 2025-09-07T14:44:50.6844128Z [--enable-activation-checkpointing] 2025-09-07T14:44:50.6844447Z [--timing] 2025-09-07T14:44:50.6844659Z [--progress] 2025-09-07T14:44:50.6844914Z [--timeout TIMEOUT] 2025-09-07T14:44:50.6845259Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T14:44:50.6845666Z [--no-translation-validation] 2025-09-07T14:44:50.6845949Z [--minify] 2025-09-07T14:44:50.6846194Z [--compiled-autograd] 2025-09-07T14:44:50.6846485Z [--profile_dynamo_cache_lookup] 2025-09-07T14:44:50.6846790Z [--snapshot-memory] 2025-09-07T14:44:50.6847041Z [--retain-output] 2025-09-07T14:44:50.6847307Z [--caching-precompile] 2025-09-07T14:44:50.6847641Z [--cold-start-latency | --warm-start-latency] 2025-09-07T14:44:50.6848068Z [--nnc] 2025-09-07T14:44:50.6848314Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T14:44:50.6848670Z [--amp-dtype {bfloat16,float16}] 2025-09-07T14:44:50.6848985Z [--verbose | --quiet] 2025-09-07T14:44:50.6852496Z [--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] 2025-09-07T14:44:50.6856083Z (--accuracy | --performance | --tolerance) 2025-09-07T14:44:50.6856503Z (--training | --inference) 2025-09-07T14:44:50.6856916Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T14:44:51.3386901Z + true 2025-09-07T14:44:51.3388206Z + cp /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv 2025-09-07T14:44:51.3405266Z + for target in "${targets[@]}" 2025-09-07T14:44:51.3405596Z + target_flag=('--performance') 2025-09-07T14:44:51.3405886Z + local target_flag 2025-09-07T14:44:51.3406145Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T14:44:51.3406499Z + target_flag+=(--cold-start-latency) 2025-09-07T14:44:51.3407884Z + [[ 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* ]] 2025-09-07T14:44:51.3410600Z + [[ 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* ]] 2025-09-07T14:44:51.3413199Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 2 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv 2025-09-07T14:44:51.8941271Z /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. 2025-09-07T14:44:51.8942683Z import pynvml # type: ignore[import] 2025-09-07T14:44:55.4150177Z /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. 2025-09-07T14:44:55.4151588Z import pynvml # type: ignore[import] 2025-09-07T14:44:58.0053735Z 2025-09-07T14:45:03.7818939Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:45:03.7819305Z loading model: 0it [00:05, ?it/s] 2025-09-07T14:45:03.7873755Z cuda eval hf_Bart 2025-09-07T14:45:19.1813817Z 2025-09-07T14:45:19.2842584Z running benchmark: 0% 0/30 [00:00> $GITHUB_ENV 2025-09-07T16:44:49.2636832Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-09-07T16:44:49.2649897Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:44:49.2650277Z env: 2025-09-07T16:44:49.2650506Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:44:49.2650844Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:44:49.2651307Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:44:49.2651892Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:44:49.2652406Z ##[endgroup] 2025-09-07T16:44:49.2681948Z + [[ -n '' ]] 2025-09-07T16:44:49.2682311Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T16:44:49.5735855Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T16:44:50.4182322Z Collecting boto3==1.35.33 2025-09-07T16:44:50.4709168Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-09-07T16:44:50.5023535Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 4.5 MB/s eta 0:00:00 2025-09-07T16:44:50.6604892Z Collecting psutil==7.0.0 2025-09-07T16:44:50.6640228Z 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) 2025-09-07T16:44:50.6774333Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 23.4 MB/s eta 0:00:00 2025-09-07T16:44:50.6974521Z Collecting pynvml==12.0.0 2025-09-07T16:44:50.7020103Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-09-07T16:44:50.7408842Z Collecting s3transfer<0.11.0,>=0.10.0 2025-09-07T16:44:50.7439889Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-09-07T16:44:50.7507007Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 14.5 MB/s eta 0:00:00 2025-09-07T16:44:50.7708666Z Collecting jmespath<2.0.0,>=0.7.1 2025-09-07T16:44:50.7742223Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-09-07T16:44:51.5132953Z Collecting botocore<1.36.0,>=1.35.33 2025-09-07T16:44:51.5179361Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-09-07T16:44:51.6630210Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 91.1 MB/s eta 0:00:00 2025-09-07T16:44:51.7472946Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-09-07T16:44:51.7600707Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-09-07T16:44:51.7668521Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 7.4 MB/s eta 0:00:00 2025-09-07T16:44:51.7739861Z 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) 2025-09-07T16:44:51.7747429Z 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) 2025-09-07T16:44:52.0429058Z Installing collected packages: nvidia-ml-py, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-09-07T16:44:52.0429854Z Attempting uninstall: nvidia-ml-py 2025-09-07T16:44:52.0435514Z Found existing installation: nvidia-ml-py 11.525.84 2025-09-07T16:44:52.0472939Z Uninstalling nvidia-ml-py-11.525.84: 2025-09-07T16:44:52.0497651Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-09-07T16:44:52.1201481Z Attempting uninstall: psutil 2025-09-07T16:44:52.1209129Z Found existing installation: psutil 5.9.8 2025-09-07T16:44:52.1356110Z Uninstalling psutil-5.9.8: 2025-09-07T16:44:52.1365295Z Successfully uninstalled psutil-5.9.8 2025-09-07T16:44:52.9469650Z 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 2025-09-07T16:44:53.0538171Z + DEVICE_NAME= 2025-09-07T16:44:53.0538431Z + DEVICE_TYPE= 2025-09-07T16:44:53.0538678Z + command -v nvidia-smi 2025-09-07T16:44:53.0539161Z + python3 -mpip install torch==2.7.1 2025-09-07T16:44:53.0539463Z /usr/bin/nvidia-smi 2025-09-07T16:44:53.3579726Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T16:44:53.6057380Z Collecting torch==2.7.1 2025-09-07T16:44:53.6733543Z Downloading torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) 2025-09-07T16:45:10.7595127Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 1.4 MB/s eta 0:00:00 2025-09-07T16:45:12.9338325Z Collecting nvidia-cusparse-cu12==12.5.4.2 2025-09-07T16:45:12.9449087Z Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) 2025-09-07T16:45:16.0490087Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 7.8 MB/s eta 0:00:00 2025-09-07T16:45:16.6208281Z Collecting triton==3.3.1 2025-09-07T16:45:16.6324480Z Downloading triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) 2025-09-07T16:45:19.3342210Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 13.1 MB/s eta 0:00:00 2025-09-07T16:45:19.7464622Z Collecting nvidia-nccl-cu12==2.26.2 2025-09-07T16:45:19.7604190Z Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) 2025-09-07T16:45:22.2010404Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 9.4 MB/s eta 0:00:00 2025-09-07T16:45:22.7348525Z Collecting sympy>=1.13.3 2025-09-07T16:45:22.7437757Z Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB) 2025-09-07T16:45:22.7934677Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 131.6 MB/s eta 0:00:00 2025-09-07T16:45:22.8419904Z Collecting nvidia-curand-cu12==10.3.7.77 2025-09-07T16:45:22.8547069Z Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) 2025-09-07T16:45:23.7817753Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 43.8 MB/s eta 0:00:00 2025-09-07T16:45:23.9456234Z Collecting nvidia-cublas-cu12==12.6.4.1 2025-09-07T16:45:23.9552968Z Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) 2025-09-07T16:45:31.5096190Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 2.2 MB/s eta 0:00:00 2025-09-07T16:45:32.5888640Z Collecting nvidia-cufile-cu12==1.11.1.6 2025-09-07T16:45:32.5979290Z Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) 2025-09-07T16:45:32.7197305Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 9.4 MB/s eta 0:00:00 2025-09-07T16:45:32.8528905Z Collecting nvidia-cusparselt-cu12==0.6.3 2025-09-07T16:45:32.8666349Z Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) 2025-09-07T16:45:35.3545291Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 7.2 MB/s eta 0:00:00 2025-09-07T16:45:35.7880454Z Collecting fsspec 2025-09-07T16:45:35.7967670Z Downloading fsspec-2025.9.0-py3-none-any.whl (199 kB) 2025-09-07T16:45:35.8063506Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.3/199.3 KB 24.5 MB/s eta 0:00:00 2025-09-07T16:45:35.8453689Z Collecting filelock 2025-09-07T16:45:35.8553297Z Downloading filelock-3.19.1-py3-none-any.whl (15 kB) 2025-09-07T16:45:35.8838175Z Collecting nvidia-cuda-cupti-cu12==12.6.80 2025-09-07T16:45:35.8938141Z Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) 2025-09-07T16:45:35.9725420Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 115.9 MB/s eta 0:00:00 2025-09-07T16:45:36.0183967Z Collecting nvidia-cuda-runtime-cu12==12.6.77 2025-09-07T16:45:36.0271358Z Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) 2025-09-07T16:45:36.0410386Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 KB 74.6 MB/s eta 0:00:00 2025-09-07T16:45:36.0664686Z Collecting nvidia-cusolver-cu12==11.7.1.2 2025-09-07T16:45:36.0761382Z Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) 2025-09-07T16:45:37.7837625Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 16.0 MB/s eta 0:00:00 2025-09-07T16:45:38.2045134Z Collecting nvidia-cudnn-cu12==9.5.1.17 2025-09-07T16:45:38.2139324Z Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) 2025-09-07T16:45:49.7207400Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.6 MB/s eta 0:00:00 2025-09-07T16:45:51.1303510Z Requirement already satisfied: typing-extensions>=4.10.0 in /home/frank/.local/lib/python3.10/site-packages (from torch==2.7.1) (4.15.0) 2025-09-07T16:45:51.3040850Z Collecting nvidia-cuda-nvrtc-cu12==12.6.77 2025-09-07T16:45:51.3964442Z Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) 2025-09-07T16:45:52.3318845Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 21.6 MB/s eta 0:00:00 2025-09-07T16:45:52.4152573Z Collecting nvidia-nvjitlink-cu12==12.6.85 2025-09-07T16:45:52.4282975Z Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) 2025-09-07T16:45:52.7675982Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 39.1 MB/s eta 0:00:00 2025-09-07T16:45:52.8459036Z Collecting jinja2 2025-09-07T16:45:52.8561766Z Downloading jinja2-3.1.6-py3-none-any.whl (134 kB) 2025-09-07T16:45:52.8619712Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.9/134.9 KB 31.8 MB/s eta 0:00:00 2025-09-07T16:45:52.8841609Z Collecting nvidia-cufft-cu12==11.3.0.4 2025-09-07T16:45:52.8934262Z Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) 2025-09-07T16:45:55.3619729Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 9.5 MB/s eta 0:00:00 2025-09-07T16:45:55.9006543Z Collecting networkx 2025-09-07T16:45:55.9093157Z Downloading networkx-3.4.2-py3-none-any.whl (1.7 MB) 2025-09-07T16:45:55.9281659Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 100.3 MB/s eta 0:00:00 2025-09-07T16:45:55.9601374Z Collecting nvidia-nvtx-cu12==12.6.77 2025-09-07T16:45:55.9694448Z Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) 2025-09-07T16:45:55.9777023Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.3/89.3 KB 11.9 MB/s eta 0:00:00 2025-09-07T16:45:56.0062647Z 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) 2025-09-07T16:45:56.0326225Z Collecting mpmath<1.4,>=1.1.0 2025-09-07T16:45:56.0412183Z Downloading mpmath-1.3.0-py3-none-any.whl (536 kB) 2025-09-07T16:45:56.0534442Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 50.4 MB/s eta 0:00:00 2025-09-07T16:45:56.2586793Z Collecting MarkupSafe>=2.0 2025-09-07T16:45:56.2720746Z Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) 2025-09-07T16:45:56.6388396Z 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 2025-09-07T16:46:01.6202968Z WARNING: The scripts proton and proton-viewer are installed in '/home/frank/.local/bin' which is not on PATH. 2025-09-07T16:46:01.6203940Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T16:46:05.6207484Z WARNING: The script isympy is installed in '/home/frank/.local/bin' which is not on PATH. 2025-09-07T16:46:05.6208341Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T16:46:41.5839401Z WARNING: The scripts torchfrtrace and torchrun are installed in '/home/frank/.local/bin' which is not on PATH. 2025-09-07T16:46:41.5840357Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T16:46:41.9427934Z 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 2025-09-07T16:46:42.4239924Z + echo DEVICE_NAME= 2025-09-07T16:46:42.4240236Z + echo DEVICE_TYPE= 2025-09-07T16:46:42.4373652Z ##[group]Run set -eux 2025-09-07T16:46:42.4373932Z set -eux 2025-09-07T16:46:42.4374148Z  2025-09-07T16:46:42.4374393Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-09-07T16:46:42.4374756Z  echo "Missing github-token input" 2025-09-07T16:46:42.4375081Z  exit 1 2025-09-07T16:46:42.4375293Z fi 2025-09-07T16:46:42.4388173Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:42.4388581Z env: 2025-09-07T16:46:42.4388807Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:42.4389142Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:42.4389601Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:42.4390333Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:42.4390839Z DEVICE_NAME: 2025-09-07T16:46:42.4391067Z DEVICE_TYPE: 2025-09-07T16:46:42.4391529Z GITHUB_TOKEN: *** 2025-09-07T16:46:42.4391750Z ##[endgroup] 2025-09-07T16:46:42.4501297Z + [[ -z *** ]] 2025-09-07T16:46:42.4828338Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-09-07T16:46:42.4828795Z with: 2025-09-07T16:46:42.4829207Z github-token: *** 2025-09-07T16:46:42.4829428Z env: 2025-09-07T16:46:42.4829644Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:42.4829987Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:42.4830448Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:42.4831034Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:42.4831543Z DEVICE_NAME: 2025-09-07T16:46:42.4831773Z DEVICE_TYPE: 2025-09-07T16:46:42.4831996Z ##[endgroup] 2025-09-07T16:46:42.5149581Z ##[group]Run set -eux 2025-09-07T16:46:42.5149866Z set -eux 2025-09-07T16:46:42.5150093Z  2025-09-07T16:46:42.5150570Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T16:46:42.5163005Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:42.5163395Z env: 2025-09-07T16:46:42.5163614Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:42.5163946Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:42.5164412Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:42.5164996Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:42.5165522Z DEVICE_NAME: 2025-09-07T16:46:42.5165751Z DEVICE_TYPE: 2025-09-07T16:46:42.5166248Z GITHUB_TOKEN: *** 2025-09-07T16:46:42.5166477Z ##[endgroup] 2025-09-07T16:46:42.5278174Z + python3 /home/frank/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525309334 i-03028b1668c838483-1006 2025-09-07T16:46:43.7938250Z setting job-id=49775768420 2025-09-07T16:46:43.7938822Z setting job-name=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T16:46:43.8048929Z ##[group]Run set -eux 2025-09-07T16:46:43.8049217Z set -eux 2025-09-07T16:46:43.8049448Z  2025-09-07T16:46:43.8049669Z if [[ -n "" ]]; then 2025-09-07T16:46:43.8049947Z  source "" 2025-09-07T16:46:43.8050172Z fi 2025-09-07T16:46:43.8050378Z  2025-09-07T16:46:43.8050763Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-09-07T16:46:43.8051445Z  --schema-version "${SCHEMA_VERSION}" \ 2025-09-07T16:46:43.8051786Z  --repo "${REPO}" \ 2025-09-07T16:46:43.8052095Z  --head-branch "${HEAD_BRANCH}" \ 2025-09-07T16:46:43.8052439Z  --head-sha "${HEAD_SHA}" \ 2025-09-07T16:46:43.8052930Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-09-07T16:46:43.8053285Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-09-07T16:46:43.8053615Z  --job-id "${JOB_ID}" \ 2025-09-07T16:46:43.8054100Z  --job-name "${JOB_NAME}" 2025-09-07T16:46:43.8066899Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:43.8067293Z env: 2025-09-07T16:46:43.8067502Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:43.8067839Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:43.8068302Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:43.8068900Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:43.8069402Z DEVICE_NAME: 2025-09-07T16:46:43.8069632Z DEVICE_TYPE: 2025-09-07T16:46:43.8069855Z SCHEMA_VERSION: v3 2025-09-07T16:46:43.8070105Z REPO: pytorch/pytorch 2025-09-07T16:46:43.8070473Z HEAD_BRANCH: refs/heads/main 2025-09-07T16:46:43.8070810Z HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T16:46:43.8071168Z WORKFLOW_RUN_ID: 17525309334 2025-09-07T16:46:43.8071443Z RUN_ATTEMPT: 1 2025-09-07T16:46:43.8071662Z JOB_ID: 49775768420 2025-09-07T16:46:43.8072106Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T16:46:43.8072607Z ##[endgroup] 2025-09-07T16:46:43.8175850Z + [[ -n '' ]] 2025-09-07T16:46:43.8179618Z + python3 /home/frank/_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 17525309334 --run-attempt 1 --job-id 49775768420 --job-name 'cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)' 2025-09-07T16:46:43.8506232Z ##[group]Run set -eux 2025-09-07T16:46:43.8506513Z set -eux 2025-09-07T16:46:43.8506726Z  2025-09-07T16:46:43.8506953Z if [[ -n "" ]]; then 2025-09-07T16:46:43.8507226Z  source "" 2025-09-07T16:46:43.8507462Z fi 2025-09-07T16:46:43.8507658Z  2025-09-07T16:46:43.8508053Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-09-07T16:46:43.8519871Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:43.8520262Z env: 2025-09-07T16:46:43.8520470Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:43.8520810Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:43.8521274Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:43.8521873Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:43.8522388Z DEVICE_NAME: 2025-09-07T16:46:43.8522603Z DEVICE_TYPE: 2025-09-07T16:46:43.8522995Z ##[endgroup] 2025-09-07T16:46:43.8636826Z + [[ -n '' ]] 2025-09-07T16:46:43.8637601Z + python3 /home/frank/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-09-07T16:46:44.6915087Z /home/frank/.local/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:276: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:81.) 2025-09-07T16:46:44.6916433Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-09-07T16:46:45.9726846Z ##[group]Run set -eux 2025-09-07T16:46:45.9727138Z set -eux 2025-09-07T16:46:45.9727368Z  2025-09-07T16:46:45.9727611Z # TODO (huydhn): Implement this part 2025-09-07T16:46:45.9728003Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-09-07T16:46:45.9741191Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:45.9741586Z env: 2025-09-07T16:46:45.9741819Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:45.9742142Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:45.9742791Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:45.9743393Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:45.9743899Z DEVICE_NAME: 2025-09-07T16:46:45.9744120Z DEVICE_TYPE: 2025-09-07T16:46:45.9744348Z ##[endgroup] 2025-09-07T16:46:45.9856133Z + echo 'dependencies={}' 2025-09-07T16:46:46.0038669Z ##[group]Run set -eux 2025-09-07T16:46:46.0038959Z set -eux 2025-09-07T16:46:46.0039175Z  2025-09-07T16:46:46.0039396Z if [[ -n "" ]]; then 2025-09-07T16:46:46.0039675Z  source "" 2025-09-07T16:46:46.0039920Z fi 2025-09-07T16:46:46.0040130Z  2025-09-07T16:46:46.0040397Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-09-07T16:46:46.0040856Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-09-07T16:46:46.0041462Z  # We don't want the job to fail if the directory doesn't exist 2025-09-07T16:46:46.0041886Z  exit 0 2025-09-07T16:46:46.0042103Z fi 2025-09-07T16:46:46.0042321Z  2025-09-07T16:46:46.0042573Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-09-07T16:46:46.0043248Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T16:46:46.0043811Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T16:46:46.0044257Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T16:46:46.0044625Z  --runners "${RUNNER_INFO}" \ 2025-09-07T16:46:46.0044985Z  --dependencies "${DEPENDENCIES}" \ 2025-09-07T16:46:46.0045310Z  --dry-run 2025-09-07T16:46:46.0045573Z else 2025-09-07T16:46:46.0045961Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T16:46:46.0046526Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T16:46:46.0046965Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T16:46:46.0047314Z  --runners "${RUNNER_INFO}" \ 2025-09-07T16:46:46.0047664Z  --dependencies "${DEPENDENCIES}" 2025-09-07T16:46:46.0047992Z fi 2025-09-07T16:46:46.0059844Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:46.0060234Z env: 2025-09-07T16:46:46.0060441Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:46.0060782Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:46.0061239Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:46.0061836Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:46.0062345Z DEVICE_NAME: 2025-09-07T16:46:46.0062577Z DEVICE_TYPE: 2025-09-07T16:46:46.0062835Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-09-07T16:46:46.0063154Z DRY_RUN: false 2025-09-07T16:46:46.0064526Z BENCHMARK_METADATA: {"timestamp": 1757263603, "schema_version": "v3", "name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525309334, "run_attempt": 1, "job_id": 49775768420} 2025-09-07T16:46:46.0066495Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 1121, "extra_info": {"hostname": "4325a60d1947"}, "name": "cuda", "type": "NVIDIA A100-SXM4-40GB", "gpu_count": 1, "avail_gpu_mem_in_gb": 39}] 2025-09-07T16:46:46.0067325Z DEPENDENCIES: {} 2025-09-07T16:46:46.0067563Z ##[endgroup] 2025-09-07T16:46:46.0172259Z + [[ -n '' ]] 2025-09-07T16:46:46.0172517Z + [[ ! -d test/test-reports ]] 2025-09-07T16:46:46.0172955Z + [[ false == \t\r\u\e ]] 2025-09-07T16:46:46.0176024Z + python3 /home/frank/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757263603, "schema_version": "v3", "name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525309334, "run_attempt": 1, "job_id": 49775768420}' --runners '[{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 1121, "extra_info": {"hostname": "4325a60d1947"}, "name": "cuda", "type": "NVIDIA A100-SXM4-40GB", "gpu_count": 1, "avail_gpu_mem_in_gb": 39}]' --dependencies '{}' 2025-09-07T16:46:46.1518343Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:46.1905342Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role 2025-09-07T16:46:46.4156708Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:46.6256231Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:46.7643789Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:46.9781316Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:47.1369938Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T16:46:47.3100969Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:47.4868496Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:47.6466016Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:47.7836537Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:47.9332275Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:48.0853213Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:48.2225424Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json 2025-09-07T16:46:48.3573288Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json 2025-09-07T16:46:48.4669093Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:48.5886229Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:48.6960836Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json 2025-09-07T16:46:48.8199607Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:48.9787354Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T16:46:49.1432831Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:49.3120825Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_dynamic_torchbench_amp_training_cuda_performance.json 2025-09-07T16:46:49.4429840Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:49.5588334Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:49.6680994Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json 2025-09-07T16:46:49.7789935Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json 2025-09-07T16:46:49.9077331Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json 2025-09-07T16:46:50.0388302Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:50.1635250Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:50.2819749Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json 2025-09-07T16:46:50.3713802Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:50.4968283Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_max_autotune_torchbench_amp_training_cuda_performance.json 2025-09-07T16:46:50.6450729Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T16:46:50.8179405Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T16:46:50.9846835Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T16:46:51.1331257Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:51.2709067Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:51.3909727Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json 2025-09-07T16:46:51.5066453Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T16:46:51.6452154Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T16:46:51.7727781Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768420/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T16:46:51.9789489Z ##[group]Run cat test/**/*_toprint.log || true 2025-09-07T16:46:51.9789902Z cat test/**/*_toprint.log || true 2025-09-07T16:46:51.9802647Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:51.9803222Z env: 2025-09-07T16:46:51.9803452Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:51.9803795Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:51.9804252Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:51.9804855Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:51.9805364Z DEVICE_NAME: 2025-09-07T16:46:51.9805597Z DEVICE_TYPE: 2025-09-07T16:46:51.9805837Z ##[endgroup] 2025-09-07T16:46:51.9991091Z cat: 'test/**/*_toprint.log': No such file or directory 2025-09-07T16:46:52.0245445Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-09-07T16:46:52.0245939Z kill "$MONITOR_SCRIPT_PID" 2025-09-07T16:46:52.0258124Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:52.0258517Z env: 2025-09-07T16:46:52.0258746Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:52.0259087Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:52.0259537Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:52.0260139Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:52.0260656Z DEVICE_NAME: 2025-09-07T16:46:52.0260889Z DEVICE_TYPE: 2025-09-07T16:46:52.0261126Z MONITOR_SCRIPT_PID: 9476 2025-09-07T16:46:52.0261378Z ##[endgroup] 2025-09-07T16:46:52.0491110Z Prepare all required actions 2025-09-07T16:46:52.0491628Z Getting action download info 2025-09-07T16:46:52.1970870Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T16:46:52.8506219Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-09-07T16:46:55.1795771Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-09-07T16:46:55.1796147Z with: 2025-09-07T16:46:55.1796513Z file-suffix: test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T16:46:55.1796970Z s3-bucket: gha-artifacts 2025-09-07T16:46:55.1797230Z env: 2025-09-07T16:46:55.1797441Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:55.1797776Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:55.1798225Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:55.1798878Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:55.1799389Z DEVICE_NAME: 2025-09-07T16:46:55.1799604Z DEVICE_TYPE: 2025-09-07T16:46:55.1799834Z ##[endgroup] 2025-09-07T16:46:55.2238815Z ##[group]Run # Remove any previous test jsons if they exist 2025-09-07T16:46:55.2239291Z # Remove any previous test jsons if they exist 2025-09-07T16:46:55.2239681Z rm -f test-jsons-*.zip 2025-09-07T16:46:55.2240100Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-09-07T16:46:55.2252878Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:55.2253272Z env: 2025-09-07T16:46:55.2253496Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:55.2253834Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:55.2254283Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:55.2254888Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:55.2255394Z DEVICE_NAME: 2025-09-07T16:46:55.2255633Z DEVICE_TYPE: 2025-09-07T16:46:55.2256006Z FILE_SUFFIX: test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T16:46:55.2256570Z ##[endgroup] 2025-09-07T16:46:55.2438901Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.2467970Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.2497034Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.2578350Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.2704453Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.2837288Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.2883095Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.3035701Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.3066583Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.3198053Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.3345481Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.3382678Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.3409687Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.3436557Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.3483055Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.3512349Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.3539721Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.3673293Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.3805612Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.3930795Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.3970465Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.3999288Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.4028259Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.4067826Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4107568Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4134583Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.4163607Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.4209359Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4236144Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.4281620Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4321321Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4473305Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.4598763Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.4729687Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.4775927Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4798871Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.4838641Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4885047Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T16:46:55.4914037Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T16:46:55.5045091Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T16:46:55.5112220Z ##[group]Run # Remove any previous test reports if they exist 2025-09-07T16:46:55.5112710Z # Remove any previous test reports if they exist 2025-09-07T16:46:55.5113102Z rm -f test-reports-*.zip 2025-09-07T16:46:55.5113584Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-09-07T16:46:55.5125834Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:55.5126225Z env: 2025-09-07T16:46:55.5126445Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:55.5126783Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:55.5127231Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:55.5127824Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:55.5128330Z DEVICE_NAME: 2025-09-07T16:46:55.5128571Z DEVICE_TYPE: 2025-09-07T16:46:55.5128949Z FILE_SUFFIX: test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T16:46:55.5129385Z ##[endgroup] 2025-09-07T16:46:55.5275224Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T16:46:55.5276269Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5277302Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5278993Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5280027Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5281003Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5281964Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5283254Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5284369Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5285426Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5286401Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5287308Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5288273Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T16:46:55.5289262Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.csv (deflated 58%) 2025-09-07T16:46:55.5290254Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T16:46:55.5291382Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5292306Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.csv (deflated 58%) 2025-09-07T16:46:55.5293397Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5294538Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5295586Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.csv (deflated 58%) 2025-09-07T16:46:55.5296762Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T16:46:55.5297894Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 62%) 2025-09-07T16:46:55.5298843Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5299871Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5300835Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 70%) 2025-09-07T16:46:55.5301829Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T16:46:55.5303972Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5306603Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5307635Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5308538Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5309420Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.csv (deflated 57%) 2025-09-07T16:46:55.5310295Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 59%) 2025-09-07T16:46:55.5311220Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5312318Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T16:46:55.5313422Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 60%) 2025-09-07T16:46:55.5314360Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5315262Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.csv (deflated 53%) 2025-09-07T16:46:55.5316197Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.csv (deflated 57%) 2025-09-07T16:46:55.5317112Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T16:46:55.5318122Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5320290Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5323415Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T16:46:55.5569971Z ##[group]Run # Remove any previous usage logs if they exist 2025-09-07T16:46:55.5570448Z # Remove any previous usage logs if they exist 2025-09-07T16:46:55.5570827Z rm -f logs-*.zip 2025-09-07T16:46:55.5571191Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true 2025-09-07T16:46:55.5571718Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true 2025-09-07T16:46:55.5583526Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:55.5583921Z env: 2025-09-07T16:46:55.5584133Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:55.5584479Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:55.5585100Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:55.5585708Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:55.5586214Z DEVICE_NAME: 2025-09-07T16:46:55.5586457Z DEVICE_TYPE: 2025-09-07T16:46:55.5586839Z FILE_SUFFIX: test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T16:46:55.5587296Z ##[endgroup] 2025-09-07T16:46:55.5951141Z adding: usage_log.txt (deflated 92%) 2025-09-07T16:46:55.5965777Z 2025-09-07T16:46:55.5966152Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip) 2025-09-07T16:46:55.5996734Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-09-07T16:46:55.5997265Z # Remove any previous debugging artifacts if they exist 2025-09-07T16:46:55.5997675Z rm -f debug-*.zip 2025-09-07T16:46:55.5997947Z if [ -d 'test/debug' ]; then 2025-09-07T16:46:55.5998321Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-09-07T16:46:55.5998672Z fi 2025-09-07T16:46:55.6009968Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:55.6010363Z env: 2025-09-07T16:46:55.6010571Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:55.6010907Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:55.6011373Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:55.6011970Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:55.6012479Z DEVICE_NAME: 2025-09-07T16:46:55.6012695Z DEVICE_TYPE: 2025-09-07T16:46:55.6032398Z FILE_SUFFIX: test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420 2025-09-07T16:46:55.6032870Z ##[endgroup] 2025-09-07T16:46:55.6203582Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T16:46:55.6203904Z with: 2025-09-07T16:46:55.6204121Z s3-bucket: gha-artifacts 2025-09-07T16:46:55.6204454Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:55.6204807Z retention-days: 14 2025-09-07T16:46:55.6205044Z if-no-files-found: warn 2025-09-07T16:46:55.6205418Z path: test-jsons-*.zip 2025-09-07T16:46:55.6205671Z name: artifact 2025-09-07T16:46:55.6205900Z region: us-east-1 2025-09-07T16:46:55.6206112Z env: 2025-09-07T16:46:55.6206331Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:55.6206664Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:55.6207121Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:55.6207700Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:55.6208207Z DEVICE_NAME: 2025-09-07T16:46:55.6208435Z DEVICE_TYPE: 2025-09-07T16:46:55.6208658Z ##[endgroup] 2025-09-07T16:46:55.9535861Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T16:46:55.9536336Z With the provided path, there will be 1 file uploaded 2025-09-07T16:46:55.9536806Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:55.9544828Z Starting upload of test-jsons-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:46:56.0832178Z Finished upload of test-jsons-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:46:56.1176068Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T16:46:56.1176566Z with: 2025-09-07T16:46:56.1176792Z s3-bucket: gha-artifacts 2025-09-07T16:46:56.1177122Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:56.1177577Z retention-days: 14 2025-09-07T16:46:56.1177834Z if-no-files-found: error 2025-09-07T16:46:56.1178115Z path: test-reports-*.zip 2025-09-07T16:46:56.1178381Z name: artifact 2025-09-07T16:46:56.1178596Z region: us-east-1 2025-09-07T16:46:56.1178828Z env: 2025-09-07T16:46:56.1179042Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:56.1179377Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:56.1179989Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:56.1180596Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:56.1181114Z DEVICE_NAME: 2025-09-07T16:46:56.1181344Z DEVICE_TYPE: 2025-09-07T16:46:56.1181569Z ##[endgroup] 2025-09-07T16:46:56.4500622Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T16:46:56.4501101Z With the provided path, there will be 1 file uploaded 2025-09-07T16:46:56.4501561Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:56.4509487Z Starting upload of test-reports-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:46:56.5742579Z Finished upload of test-reports-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:46:56.6005088Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T16:46:56.6005440Z with: 2025-09-07T16:46:56.6005668Z s3-bucket: gha-artifacts 2025-09-07T16:46:56.6006010Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:56.6006355Z retention-days: 14 2025-09-07T16:46:56.6006616Z if-no-files-found: ignore 2025-09-07T16:46:56.6006899Z path: logs-*.zip 2025-09-07T16:46:56.6007134Z name: artifact 2025-09-07T16:46:56.6007352Z region: us-east-1 2025-09-07T16:46:56.6007581Z env: 2025-09-07T16:46:56.6007799Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:56.6008133Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:56.6008590Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:56.6009187Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:56.6009698Z DEVICE_NAME: 2025-09-07T16:46:56.6009930Z DEVICE_TYPE: 2025-09-07T16:46:56.6010155Z ##[endgroup] 2025-09-07T16:46:56.9336400Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T16:46:56.9336878Z With the provided path, there will be 1 file uploaded 2025-09-07T16:46:56.9337359Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:56.9345313Z Starting upload of logs-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:46:57.0505486Z Finished upload of logs-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:46:57.0753022Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T16:46:57.0753376Z with: 2025-09-07T16:46:57.0753601Z s3-bucket: gha-artifacts 2025-09-07T16:46:57.0753923Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T16:46:57.0754264Z retention-days: 14 2025-09-07T16:46:57.0754520Z if-no-files-found: ignore 2025-09-07T16:46:57.0754795Z path: debug-*.zip 2025-09-07T16:46:57.0755031Z name: artifact 2025-09-07T16:46:57.0755250Z region: us-east-1 2025-09-07T16:46:57.0755482Z env: 2025-09-07T16:46:57.0755700Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:57.0756042Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:57.0756494Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:57.0757103Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:57.0757618Z DEVICE_NAME: 2025-09-07T16:46:57.0757843Z DEVICE_TYPE: 2025-09-07T16:46:57.0758066Z ##[endgroup] 2025-09-07T16:46:57.3996299Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-09-07T16:46:57.4238854Z ##[group]Run # shellcheck disable=SC2156 2025-09-07T16:46:57.4239215Z # shellcheck disable=SC2156 2025-09-07T16:46:57.4239810Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-09-07T16:46:57.4252944Z shell: /usr/bin/bash -e {0} 2025-09-07T16:46:57.4253235Z env: 2025-09-07T16:46:57.4253457Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:57.4253781Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:57.4254249Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:57.4254845Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:57.4255366Z DEVICE_NAME: 2025-09-07T16:46:57.4255607Z DEVICE_TYPE: 2025-09-07T16:46:57.4255835Z ##[endgroup] 2025-09-07T16:46:57.9513863Z Prepare all required actions 2025-09-07T16:46:57.9514276Z Getting action download info 2025-09-07T16:46:58.0752973Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-09-07T16:46:58.0753350Z with: 2025-09-07T16:46:58.0753550Z job_id: 49775768420 2025-09-07T16:46:58.0754003Z job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T16:46:58.0754551Z workflow_name: inductor-A100-perf-nightly 2025-09-07T16:46:58.0754889Z workflow_run_id: 17525309334 2025-09-07T16:46:58.0755169Z workflow_attempt: 1 2025-09-07T16:46:58.0755399Z env: 2025-09-07T16:46:58.0755611Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:58.0755947Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:58.0756405Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:58.0756989Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:58.0757505Z DEVICE_NAME: 2025-09-07T16:46:58.0757771Z DEVICE_TYPE: 2025-09-07T16:46:58.0757983Z ##[endgroup] 2025-09-07T16:46:58.1113806Z ##[group]Run echo "workflow_id: 17525309334" 2025-09-07T16:46:58.1114183Z echo "workflow_id: 17525309334" 2025-09-07T16:46:58.1114517Z echo "workflow_attempt: 1" 2025-09-07T16:46:58.1114904Z echo "workflow_Name: inductor-A100-perf-nightly" 2025-09-07T16:46:58.1115293Z echo "job_id: 49775768420" 2025-09-07T16:46:58.1115835Z echo "job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)" 2025-09-07T16:46:58.1116390Z echo "artifact_prefix: " 2025-09-07T16:46:58.1116700Z python3 --version 2025-09-07T16:46:58.1129214Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:46:58.1129605Z env: 2025-09-07T16:46:58.1129814Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:58.1130155Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:58.1130740Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:58.1131341Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:58.1131859Z DEVICE_NAME: 2025-09-07T16:46:58.1132077Z DEVICE_TYPE: 2025-09-07T16:46:58.1132303Z ##[endgroup] 2025-09-07T16:46:58.1248601Z workflow_id: 17525309334 2025-09-07T16:46:58.1248902Z workflow_attempt: 1 2025-09-07T16:46:58.1249197Z workflow_Name: inductor-A100-perf-nightly 2025-09-07T16:46:58.1249514Z job_id: 49775768420 2025-09-07T16:46:58.1249955Z job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100) 2025-09-07T16:46:58.1250460Z artifact_prefix: 2025-09-07T16:46:58.1263576Z Python 3.10.12 2025-09-07T16:46:58.1421818Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T16:46:58.1422142Z with: 2025-09-07T16:46:58.1422340Z shell: bash 2025-09-07T16:46:58.1422568Z timeout_minutes: 5 2025-09-07T16:46:58.1422829Z max_attempts: 5 2025-09-07T16:46:58.1423088Z retry_wait_seconds: 30 2025-09-07T16:46:58.1423650Z 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 2025-09-07T16:46:58.1424359Z polling_interval_seconds: 1 2025-09-07T16:46:58.1424651Z warning_on_retry: true 2025-09-07T16:46:58.1424924Z continue_on_error: false 2025-09-07T16:46:58.1425189Z env: 2025-09-07T16:46:58.1425390Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:46:58.1425730Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:46:58.1426197Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:46:58.1426802Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:46:58.1427299Z DEVICE_NAME: 2025-09-07T16:46:58.1427528Z DEVICE_TYPE: 2025-09-07T16:46:58.1427752Z ##[endgroup] 2025-09-07T16:46:58.5248538Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T16:46:58.8857304Z Collecting python-dateutil==2.8.2 2025-09-07T16:46:58.9381164Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-09-07T16:46:59.0784264Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 247.7/247.7 KB 1.7 MB/s eta 0:00:00 2025-09-07T16:46:59.8197541Z Collecting boto3==1.35.42 2025-09-07T16:46:59.8232000Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-09-07T16:46:59.9773343Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.2/139.2 KB 848.0 kB/s eta 0:00:00 2025-09-07T16:47:00.3704988Z Collecting pandas==2.1.3 2025-09-07T16:47:00.3745161Z Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-09-07T16:47:00.5888275Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.3/12.3 MB 50.3 MB/s eta 0:00:00 2025-09-07T16:47:00.6505877Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/frank/.local/lib/python3.10/site-packages (0.6.7) 2025-09-07T16:47:00.6524190Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil==2.8.2) (1.16.0) 2025-09-07T16:47:00.6572909Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/frank/.local/lib/python3.10/site-packages (from boto3==1.35.42) (0.10.4) 2025-09-07T16:47:00.6578594Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/frank/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.0.1) 2025-09-07T16:47:00.6584069Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/frank/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.35.99) 2025-09-07T16:47:00.8436685Z Collecting tzdata>=2022.1 2025-09-07T16:47:00.8488887Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-09-07T16:47:00.9717304Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 347.8/347.8 KB 2.8 MB/s eta 0:00:00 2025-09-07T16:47:01.1557793Z Collecting pytz>=2020.1 2025-09-07T16:47:01.1594106Z Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) 2025-09-07T16:47:01.2647251Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 509.2/509.2 KB 4.8 MB/s eta 0:00:00 2025-09-07T16:47:01.8073423Z Collecting numpy<2,>=1.22.4 2025-09-07T16:47:01.8110292Z Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-09-07T16:47:02.4290255Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 17.5 MB/s eta 0:00:00 2025-09-07T16:47:02.4850176Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/frank/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-09-07T16:47:02.4867242Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/frank/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-09-07T16:47:02.4964671Z 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) 2025-09-07T16:47:02.5059413Z Requirement already satisfied: packaging>=17.0 in /home/frank/.local/lib/python3.10/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-09-07T16:47:02.5168578Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/frank/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0) 2025-09-07T16:47:02.5174185Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/frank/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-09-07T16:47:02.8093926Z Installing collected packages: pytz, tzdata, python-dateutil, numpy, pandas, boto3 2025-09-07T16:47:05.1427700Z WARNING: The script f2py is installed in '/home/frank/.local/bin' which is not on PATH. 2025-09-07T16:47:05.1428543Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T16:47:08.7500354Z Attempting uninstall: boto3 2025-09-07T16:47:08.7507053Z Found existing installation: boto3 1.35.33 2025-09-07T16:47:08.7694658Z Uninstalling boto3-1.35.33: 2025-09-07T16:47:08.7712554Z Successfully uninstalled boto3-1.35.33 2025-09-07T16:47:08.9899882Z 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 2025-09-07T16:47:09.2232690Z Command completed after 1 attempt(s). 2025-09-07T16:47:09.2385871Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T16:47:09.2388509Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T16:47:09.2389023Z  --workflow-run-id "17525309334" \ 2025-09-07T16:47:09.2389430Z  --workflow-name "inductor-A100-perf-nightly" \ 2025-09-07T16:47:09.2389841Z  --workflow-run-attempt "1" \ 2025-09-07T16:47:09.2390173Z  --job-id "49775768420" \ 2025-09-07T16:47:09.2390710Z  --job-name "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)" \ 2025-09-07T16:47:09.2391257Z  --local-path "" \ 2025-09-07T16:47:09.2391555Z  --artifact-prefix "" 2025-09-07T16:47:09.2404615Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T16:47:09.2405012Z env: 2025-09-07T16:47:09.2405222Z GIT_DEFAULT_BRANCH: main 2025-09-07T16:47:09.2405569Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T16:47:09.2406033Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5232 2025-09-07T16:47:09.2406633Z DOCKER_CONTAINER_ID: 733d4ba3112ffed69cb722279db19e1df51641f42bd5d9dc600afba3b385b2a4 2025-09-07T16:47:09.2407148Z DEVICE_NAME: 2025-09-07T16:47:09.2407369Z DEVICE_TYPE: 2025-09-07T16:47:09.2407597Z ##[endgroup] 2025-09-07T16:47:13.6173381Z repo: pytorch/pytorch 2025-09-07T16:47:13.6173756Z Search for test log in s3 bucket: ossci-utilization 2025-09-07T16:47:13.6174318Z Downloading logs-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:47:13.6175106Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf-3-6-linux.aws.a100_49775768420.zip 2025-09-07T16:47:13.6175762Z Converted Log Model: UtilizationMetadata: 2025-09-07T16:47:13.6177314Z UtilizationMetadata(level='metadata', workflow_id='17525309334', job_id='49775768420', workflow_name='inductor-A100-perf-nightly', job_name='cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757234874, gpu_count=1, cpu_count=96, gpu_type='pynvml', error=None) 2025-09-07T16:47:13.6179009Z [Db Segments] detected pytest cmd: 4, generated segments: 4 2025-09-07T16:47:13.6179417Z [db model] Peek db timeseries 2025-09-07T16:47:13.6179695Z :{ 2025-09-07T16:47:13.6179907Z "created_at": 1757263632, 2025-09-07T16:47:13.6180180Z "type": "utilization", 2025-09-07T16:47:13.6180445Z "tags": [ 2025-09-07T16:47:13.6180666Z "record" 2025-09-07T16:47:13.6180885Z ], 2025-09-07T16:47:13.6181088Z "time_stamp": 1757234874, 2025-09-07T16:47:13.6181370Z "repo": "pytorch/pytorch", 2025-09-07T16:47:13.6181653Z "workflow_id": 17525309334, 2025-09-07T16:47:13.6181943Z "run_attempt": 1, 2025-09-07T16:47:13.6182182Z "job_id": 49775768420, 2025-09-07T16:47:13.6182489Z "workflow_name": "inductor-A100-perf-nightly", 2025-09-07T16:47:13.6183372Z "job_name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 3, 6, linux.aws.a100)", 2025-09-07T16:47:13.6183892Z "json_data": "{}" 2025-09-07T16:47:13.6184121Z } 2025-09-07T16:47:13.6184633Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525309334/1/49775768420/metadata 2025-09-07T16:47:13.6185582Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525309334/1/49775768420/metadata 2025-09-07T16:47:13.6186570Z Writing 1914 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525309334/1/49775768420/time_series 2025-09-07T16:47:13.6187590Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525309334/1/49775768420/time_series 2025-09-07T16:47:13.7306255Z Post job cleanup. 2025-09-07T16:47:13.7553059Z Post job cleanup. 2025-09-07T16:47:13.8513786Z [command]/usr/bin/git version 2025-09-07T16:47:13.8548338Z git version 2.51.0 2025-09-07T16:47:13.8587335Z Temporarily overriding HOME='/home/frank/_work/_temp/ee9dea11-e399-4d8c-9512-61674b456d36' before making global git config changes 2025-09-07T16:47:13.8588234Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T16:47:13.8591982Z [command]/usr/bin/git config --global --add safe.directory /home/frank/_work/pytorch/pytorch 2025-09-07T16:47:13.8628085Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T16:47:13.8667598Z [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' || :" 2025-09-07T16:47:13.8904674Z Entering 'android/libs/fbjni' 2025-09-07T16:47:13.8946684Z Entering 'third_party/FP16' 2025-09-07T16:47:13.8989766Z Entering 'third_party/FXdiv' 2025-09-07T16:47:13.9031286Z Entering 'third_party/NNPACK' 2025-09-07T16:47:13.9074067Z Entering 'third_party/NVTX' 2025-09-07T16:47:13.9117798Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T16:47:13.9159520Z Entering 'third_party/XNNPACK' 2025-09-07T16:47:13.9218864Z Entering 'third_party/aiter' 2025-09-07T16:47:13.9261984Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T16:47:13.9312857Z Entering 'third_party/benchmark' 2025-09-07T16:47:13.9355745Z Entering 'third_party/composable_kernel' 2025-09-07T16:47:13.9405947Z Entering 'third_party/cpp-httplib' 2025-09-07T16:47:13.9448067Z Entering 'third_party/cpuinfo' 2025-09-07T16:47:13.9491013Z Entering 'third_party/cudnn_frontend' 2025-09-07T16:47:13.9533442Z Entering 'third_party/cutlass' 2025-09-07T16:47:13.9586712Z Entering 'third_party/fbgemm' 2025-09-07T16:47:13.9632586Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T16:47:13.9673245Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T16:47:13.9720885Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T16:47:13.9761777Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T16:47:14.0834365Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T16:47:14.0874199Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T16:47:14.0914640Z Entering 'third_party/fbgemm/external/json' 2025-09-07T16:47:14.0958123Z Entering 'third_party/flash-attention' 2025-09-07T16:47:14.1000743Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T16:47:14.1049739Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T16:47:14.1098904Z Entering 'third_party/flatbuffers' 2025-09-07T16:47:14.1143909Z Entering 'third_party/fmt' 2025-09-07T16:47:14.1186466Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T16:47:14.1228414Z Entering 'third_party/gloo' 2025-09-07T16:47:14.1270622Z Entering 'third_party/googletest' 2025-09-07T16:47:14.1311966Z Entering 'third_party/ideep' 2025-09-07T16:47:14.1353194Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T16:47:14.1400719Z Entering 'third_party/ittapi' 2025-09-07T16:47:14.1441875Z Entering 'third_party/kineto' 2025-09-07T16:47:14.1483799Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T16:47:14.1523531Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T16:47:14.1565551Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T16:47:14.1606486Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T16:47:14.1648943Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T16:47:14.1688295Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T16:47:14.1731092Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T16:47:14.1771707Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T16:47:14.1812739Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T16:47:14.1854856Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T16:47:14.1896865Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T16:47:14.1936953Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T16:47:14.1979154Z Entering 'third_party/kleidiai' 2025-09-07T16:47:14.2021977Z Entering 'third_party/mimalloc' 2025-09-07T16:47:14.2063906Z Entering 'third_party/nlohmann' 2025-09-07T16:47:14.2107877Z Entering 'third_party/onnx' 2025-09-07T16:47:14.2168397Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T16:47:14.2211741Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T16:47:14.2255648Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T16:47:14.2295869Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T16:47:14.2335766Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T16:47:14.2375687Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T16:47:14.2417100Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T16:47:14.2457114Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T16:47:14.2497545Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T16:47:14.2537017Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T16:47:14.2579153Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T16:47:14.2621148Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T16:47:14.2680223Z Entering 'third_party/pocketfft' 2025-09-07T16:47:14.2721308Z Entering 'third_party/protobuf' 2025-09-07T16:47:14.2766533Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T16:47:14.2806202Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T16:47:14.2848312Z Entering 'third_party/psimd' 2025-09-07T16:47:14.2890578Z Entering 'third_party/pthreadpool' 2025-09-07T16:47:14.2932082Z Entering 'third_party/pybind11' 2025-09-07T16:47:14.2973975Z Entering 'third_party/python-peachpy' 2025-09-07T16:47:14.3016490Z Entering 'third_party/sleef' 2025-09-07T16:47:14.3058273Z Entering 'third_party/tensorpipe' 2025-09-07T16:47:14.3100130Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T16:47:14.3139679Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T16:47:14.3180034Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T16:47:14.3220364Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T16:47:14.3260352Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T16:47:14.3318915Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T16:47:14.3341337Z http.https://github.com/.extraheader 2025-09-07T16:47:14.3350033Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-09-07T16:47:14.3446884Z [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' || :" 2025-09-07T16:47:14.3670163Z Entering 'android/libs/fbjni' 2025-09-07T16:47:14.3693735Z http.https://github.com/.extraheader 2025-09-07T16:47:14.3816239Z Entering 'third_party/FP16' 2025-09-07T16:47:14.3840580Z http.https://github.com/.extraheader 2025-09-07T16:47:14.3906639Z Entering 'third_party/FXdiv' 2025-09-07T16:47:14.3931219Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4026567Z Entering 'third_party/NNPACK' 2025-09-07T16:47:14.4051492Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4145400Z Entering 'third_party/NVTX' 2025-09-07T16:47:14.4169544Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4211025Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T16:47:14.4234812Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4325574Z Entering 'third_party/XNNPACK' 2025-09-07T16:47:14.4349703Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4461793Z Entering 'third_party/aiter' 2025-09-07T16:47:14.4486114Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4634692Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T16:47:14.4657621Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4763555Z Entering 'third_party/benchmark' 2025-09-07T16:47:14.4787342Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4844454Z Entering 'third_party/composable_kernel' 2025-09-07T16:47:14.4868603Z http.https://github.com/.extraheader 2025-09-07T16:47:14.4971761Z Entering 'third_party/cpp-httplib' 2025-09-07T16:47:14.4995914Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5067335Z Entering 'third_party/cpuinfo' 2025-09-07T16:47:14.5092155Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5146928Z Entering 'third_party/cudnn_frontend' 2025-09-07T16:47:14.5171240Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5268038Z Entering 'third_party/cutlass' 2025-09-07T16:47:14.5292397Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5378166Z Entering 'third_party/fbgemm' 2025-09-07T16:47:14.5402487Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5450759Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T16:47:14.5473291Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5563990Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T16:47:14.5587294Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5694905Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T16:47:14.5718119Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5751691Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T16:47:14.5774597Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5874407Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T16:47:14.5897695Z http.https://github.com/.extraheader 2025-09-07T16:47:14.5986411Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T16:47:14.6010416Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6051068Z Entering 'third_party/fbgemm/external/json' 2025-09-07T16:47:14.6074056Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6168989Z Entering 'third_party/flash-attention' 2025-09-07T16:47:14.6193384Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6289525Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T16:47:14.6311786Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6358495Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T16:47:14.6380929Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6477089Z Entering 'third_party/flatbuffers' 2025-09-07T16:47:14.6501261Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6593815Z Entering 'third_party/fmt' 2025-09-07T16:47:14.6618578Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6655282Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T16:47:14.6679378Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6778153Z Entering 'third_party/gloo' 2025-09-07T16:47:14.6802162Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6899563Z Entering 'third_party/googletest' 2025-09-07T16:47:14.6924447Z http.https://github.com/.extraheader 2025-09-07T16:47:14.6959856Z Entering 'third_party/ideep' 2025-09-07T16:47:14.6983671Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7077766Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T16:47:14.7100573Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7206860Z Entering 'third_party/ittapi' 2025-09-07T16:47:14.7231042Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7381640Z Entering 'third_party/kineto' 2025-09-07T16:47:14.7406428Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7499529Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T16:47:14.7522518Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7588487Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T16:47:14.7612155Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7711733Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T16:47:14.7734611Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7809575Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T16:47:14.7833018Z http.https://github.com/.extraheader 2025-09-07T16:47:14.7918653Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T16:47:14.7942197Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8040437Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T16:47:14.8063590Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8138633Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T16:47:14.8162137Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8252760Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T16:47:14.8276329Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8371767Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T16:47:14.8394824Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8471108Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T16:47:14.8494691Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8581572Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T16:47:14.8604677Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8698861Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T16:47:14.8722123Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8800724Z Entering 'third_party/kleidiai' 2025-09-07T16:47:14.8825029Z http.https://github.com/.extraheader 2025-09-07T16:47:14.8914169Z Entering 'third_party/mimalloc' 2025-09-07T16:47:14.8938111Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9030825Z Entering 'third_party/nlohmann' 2025-09-07T16:47:14.9055041Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9135467Z Entering 'third_party/onnx' 2025-09-07T16:47:14.9159517Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9260178Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T16:47:14.9283609Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9363957Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T16:47:14.9387589Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9461160Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T16:47:14.9483962Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9572887Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T16:47:14.9596132Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9689198Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T16:47:14.9712221Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9789445Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T16:47:14.9812544Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9870757Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T16:47:14.9894177Z http.https://github.com/.extraheader 2025-09-07T16:47:14.9988216Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T16:47:15.0011330Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0091109Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T16:47:15.0114129Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0202144Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T16:47:15.0225215Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0326268Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T16:47:15.0348878Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0396840Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T16:47:15.0419624Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0523089Z Entering 'third_party/pocketfft' 2025-09-07T16:47:15.0546370Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0622614Z Entering 'third_party/protobuf' 2025-09-07T16:47:15.0647418Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0748139Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T16:47:15.0771915Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0802752Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T16:47:15.0825590Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0925896Z Entering 'third_party/psimd' 2025-09-07T16:47:15.0950215Z http.https://github.com/.extraheader 2025-09-07T16:47:15.0979645Z Entering 'third_party/pthreadpool' 2025-09-07T16:47:15.1004098Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1034856Z Entering 'third_party/pybind11' 2025-09-07T16:47:15.1059179Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1089937Z Entering 'third_party/python-peachpy' 2025-09-07T16:47:15.1113932Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1144385Z Entering 'third_party/sleef' 2025-09-07T16:47:15.1168837Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1198589Z Entering 'third_party/tensorpipe' 2025-09-07T16:47:15.1222454Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1252032Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T16:47:15.1274630Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1304444Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T16:47:15.1327572Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1356779Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T16:47:15.1379154Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1408883Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T16:47:15.1432194Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1460908Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T16:47:15.1484276Z http.https://github.com/.extraheader 2025-09-07T16:47:15.1655842Z Post job cleanup. 2025-09-07T16:47:15.2614419Z [command]/usr/bin/git version 2025-09-07T16:47:15.2648975Z git version 2.51.0 2025-09-07T16:47:15.2687339Z Temporarily overriding HOME='/home/frank/_work/_temp/c3e6f609-193f-4aab-85d2-e481db144be5' before making global git config changes 2025-09-07T16:47:15.2688237Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T16:47:15.2692158Z [command]/usr/bin/git config --global --add safe.directory /home/frank/_work/pytorch/pytorch 2025-09-07T16:47:15.2724048Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T16:47:15.2761519Z [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' || :" 2025-09-07T16:47:15.2989165Z Entering 'android/libs/fbjni' 2025-09-07T16:47:15.3030782Z Entering 'third_party/FP16' 2025-09-07T16:47:15.3072584Z Entering 'third_party/FXdiv' 2025-09-07T16:47:15.3114263Z Entering 'third_party/NNPACK' 2025-09-07T16:47:15.3156094Z Entering 'third_party/NVTX' 2025-09-07T16:47:15.3198907Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T16:47:15.3241107Z Entering 'third_party/XNNPACK' 2025-09-07T16:47:15.3299711Z Entering 'third_party/aiter' 2025-09-07T16:47:15.3342662Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T16:47:15.3392851Z Entering 'third_party/benchmark' 2025-09-07T16:47:15.3434851Z Entering 'third_party/composable_kernel' 2025-09-07T16:47:15.3486186Z Entering 'third_party/cpp-httplib' 2025-09-07T16:47:15.3528287Z Entering 'third_party/cpuinfo' 2025-09-07T16:47:15.3570697Z Entering 'third_party/cudnn_frontend' 2025-09-07T16:47:15.3612925Z Entering 'third_party/cutlass' 2025-09-07T16:47:15.3663362Z Entering 'third_party/fbgemm' 2025-09-07T16:47:15.3707456Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T16:47:15.3747312Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T16:47:15.3795576Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T16:47:15.3835216Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T16:47:15.3884279Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T16:47:15.3923660Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T16:47:15.3963303Z Entering 'third_party/fbgemm/external/json' 2025-09-07T16:47:15.4006533Z Entering 'third_party/flash-attention' 2025-09-07T16:47:15.4048531Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T16:47:15.4094576Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T16:47:15.4143220Z Entering 'third_party/flatbuffers' 2025-09-07T16:47:15.4188573Z Entering 'third_party/fmt' 2025-09-07T16:47:15.4230255Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T16:47:15.4272415Z Entering 'third_party/gloo' 2025-09-07T16:47:15.4313570Z Entering 'third_party/googletest' 2025-09-07T16:47:15.4354992Z Entering 'third_party/ideep' 2025-09-07T16:47:15.4395585Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T16:47:15.4442166Z Entering 'third_party/ittapi' 2025-09-07T16:47:15.4483157Z Entering 'third_party/kineto' 2025-09-07T16:47:15.4524682Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T16:47:15.4564441Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T16:47:15.4605359Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T16:47:15.4645616Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T16:47:15.4685767Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T16:47:15.4725808Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 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2025-09-07T16:47:15.5286690Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T16:47:15.5326068Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T16:47:15.5365812Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T16:47:15.5405671Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T16:47:15.5446432Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T16:47:15.5485695Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T16:47:15.5524897Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T16:47:15.5563465Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T16:47:15.5605450Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T16:47:15.5647294Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T16:47:15.5709299Z Entering 'third_party/pocketfft' 2025-09-07T16:47:15.5749909Z Entering 'third_party/protobuf' 2025-09-07T16:47:15.5793643Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T16:47:15.5832754Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T16:47:15.5874617Z Entering 'third_party/psimd' 2025-09-07T16:47:15.5916109Z Entering 'third_party/pthreadpool' 2025-09-07T16:47:15.5957426Z Entering 'third_party/pybind11' 2025-09-07T16:47:15.5998894Z Entering 'third_party/python-peachpy' 2025-09-07T16:47:15.6040422Z Entering 'third_party/sleef' 2025-09-07T16:47:15.6081842Z Entering 'third_party/tensorpipe' 2025-09-07T16:47:15.6123859Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T16:47:15.6162336Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T16:47:15.6201211Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T16:47:15.6240879Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T16:47:15.6279402Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T16:47:15.6338196Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T16:47:15.6367735Z [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' || :" 2025-09-07T16:47:15.6590040Z Entering 'android/libs/fbjni' 2025-09-07T16:47:15.6631041Z Entering 'third_party/FP16' 2025-09-07T16:47:15.6672591Z Entering 'third_party/FXdiv' 2025-09-07T16:47:15.6713959Z Entering 'third_party/NNPACK' 2025-09-07T16:47:15.6755301Z Entering 'third_party/NVTX' 2025-09-07T16:47:15.6797364Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T16:47:15.6838996Z Entering 'third_party/XNNPACK' 2025-09-07T16:47:15.6897386Z Entering 'third_party/aiter' 2025-09-07T16:47:15.6940160Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T16:47:15.6988242Z Entering 'third_party/benchmark' 2025-09-07T16:47:15.7030470Z Entering 'third_party/composable_kernel' 2025-09-07T16:47:15.7080165Z Entering 'third_party/cpp-httplib' 2025-09-07T16:47:15.7121984Z Entering 'third_party/cpuinfo' 2025-09-07T16:47:15.7164813Z Entering 'third_party/cudnn_frontend' 2025-09-07T16:47:15.7206844Z Entering 'third_party/cutlass' 2025-09-07T16:47:15.7258782Z Entering 'third_party/fbgemm' 2025-09-07T16:47:15.7302690Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T16:47:15.7343642Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T16:47:15.7390713Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T16:47:15.7431025Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T16:47:15.7481676Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T16:47:15.7521381Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T16:47:15.7561332Z Entering 'third_party/fbgemm/external/json' 2025-09-07T16:47:15.7604230Z Entering 'third_party/flash-attention' 2025-09-07T16:47:15.7646030Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T16:47:15.7691296Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T16:47:15.7740361Z Entering 'third_party/flatbuffers' 2025-09-07T16:47:15.7784719Z Entering 'third_party/fmt' 2025-09-07T16:47:15.7826655Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T16:47:15.7868149Z Entering 'third_party/gloo' 2025-09-07T16:47:15.7909996Z Entering 'third_party/googletest' 2025-09-07T16:47:15.7951800Z Entering 'third_party/ideep' 2025-09-07T16:47:15.7992336Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T16:47:15.8038582Z Entering 'third_party/ittapi' 2025-09-07T16:47:15.8080799Z Entering 'third_party/kineto' 2025-09-07T16:47:15.8121981Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T16:47:15.8161336Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T16:47:15.8202406Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T16:47:15.8242150Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T16:47:15.8281532Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T16:47:15.8320886Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T16:47:15.8361991Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T16:47:15.8401981Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T16:47:15.8441550Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T16:47:15.8483343Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T16:47:15.8524587Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T16:47:15.8564404Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T16:47:15.8605840Z Entering 'third_party/kleidiai' 2025-09-07T16:47:15.8648187Z Entering 'third_party/mimalloc' 2025-09-07T16:47:15.8690051Z Entering 'third_party/nlohmann' 2025-09-07T16:47:15.8732764Z Entering 'third_party/onnx' 2025-09-07T16:47:15.8791785Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T16:47:15.8834284Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T16:47:15.8878649Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T16:47:15.8918047Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T16:47:15.8957612Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T16:47:15.8996585Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T16:47:15.9037211Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T16:47:15.9076497Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T16:47:15.9115634Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T16:47:15.9154120Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T16:47:15.9194843Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T16:47:15.9236138Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T16:47:15.9297222Z Entering 'third_party/pocketfft' 2025-09-07T16:47:15.9339117Z Entering 'third_party/protobuf' 2025-09-07T16:47:15.9383600Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T16:47:15.9422481Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T16:47:15.9464645Z Entering 'third_party/psimd' 2025-09-07T16:47:15.9506355Z Entering 'third_party/pthreadpool' 2025-09-07T16:47:15.9547386Z Entering 'third_party/pybind11' 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