2025-09-07T08:57:09.1437345Z Current runner version: '2.328.0' 2025-09-07T08:57:09.1443051Z Runner name: 'i-0b7d0f7dc0527ca9b-1008' 2025-09-07T08:57:09.1443926Z Runner group name: 'default' 2025-09-07T08:57:09.1444720Z Machine name: '304d8fe70f44' 2025-09-07T08:57:09.1447213Z ##[group]GITHUB_TOKEN Permissions 2025-09-07T08:57:09.1449155Z Contents: read 2025-09-07T08:57:09.1449760Z Metadata: read 2025-09-07T08:57:09.1450423Z ##[endgroup] 2025-09-07T08:57:09.1452619Z Secret source: Actions 2025-09-07T08:57:09.1453423Z Prepare workflow directory 2025-09-07T08:57:09.1936060Z Prepare all required actions 2025-09-07T08:57:09.1970798Z Getting action download info 2025-09-07T08:57:09.5012125Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd) 2025-09-07T08:57:10.2226191Z Download action repository 'pytorch/pytorch@main' (SHA:7a83cf430e97d83d6fb14880b9049e77ff725685) 2025-09-07T08:57:17.2195709Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-09-07T08:57:17.5620678Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-09-07T08:57:17.8397683Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-09-07T08:57:18.1455363Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T08:57:18.6205351Z Getting action download info 2025-09-07T08:57:18.7529253Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-09-07T08:57:19.0982959Z Getting action download info 2025-09-07T08:57:19.2070697Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-09-07T08:57:19.5372859Z Getting action download info 2025-09-07T08:57:19.6641826Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-09-07T08:57:19.9452192Z Getting action download info 2025-09-07T08:57:20.0897292Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634) 2025-09-07T08:57:20.0901650Z ##[group] Inputs 2025-09-07T08:57:20.0901992Z build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:57:20.0907363Z test-matrix: {"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T08:57:20.0913161Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:57:20.0913874Z sync-tag: 2025-09-07T08:57:20.0914678Z timeout-minutes: 1440 2025-09-07T08:57:20.0914899Z use-gha: 2025-09-07T08:57:20.0915790Z 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 2025-09-07T08:57:20.0916711Z s3-bucket: gha-artifacts 2025-09-07T08:57:20.0916915Z aws-role-to-assume: 2025-09-07T08:57:20.0917403Z disable-monitor: false 2025-09-07T08:57:20.0917645Z monitor-log-interval: 15 2025-09-07T08:57:20.0917864Z monitor-data-collect-interval: 4 2025-09-07T08:57:20.0918111Z ##[endgroup] 2025-09-07T08:57:20.0918431Z Complete job name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T08:57:20.1386625Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-09-07T08:57:20.1387403Z with: 2025-09-07T08:57:20.1387875Z github-secret: *** 2025-09-07T08:57:20.1388418Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-09-07T08:57:20.1388971Z activate-with-label: false 2025-09-07T08:57:20.1389184Z label: with-ssh 2025-09-07T08:57:20.1389384Z remove-existing-keys: true 2025-09-07T08:57:20.1389589Z fail-silently: true 2025-09-07T08:57:20.1389995Z env: 2025-09-07T08:57:20.1390166Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:57:20.1390557Z ##[endgroup] 2025-09-07T08:57:20.2450122Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-09-07T08:57:20.2451317Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-09-07T08:57:20.2627213Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-09-07T08:57:20.2627567Z with: 2025-09-07T08:57:20.2627728Z no-sudo: true 2025-09-07T08:57:20.2627913Z submodules: recursive 2025-09-07T08:57:20.2628109Z fetch-depth: 0 2025-09-07T08:57:20.2628278Z env: 2025-09-07T08:57:20.2628442Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:57:20.2628666Z ##[endgroup] 2025-09-07T08:57:20.2701163Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:57:20.2701935Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:57:20.2720532Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:57:20.2720889Z env: 2025-09-07T08:57:20.2721060Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:57:20.2721264Z ##[endgroup] 2025-09-07T08:57:20.2864003Z ##[group]Run actions/checkout@v4 2025-09-07T08:57:20.2864233Z with: 2025-09-07T08:57:20.2864420Z ref: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:57:20.2864661Z fetch-depth: 0 2025-09-07T08:57:20.2864836Z submodules: recursive 2025-09-07T08:57:20.2865025Z show-progress: false 2025-09-07T08:57:20.2865236Z repository: pytorch/pytorch 2025-09-07T08:57:20.2865785Z token: *** 2025-09-07T08:57:20.2865962Z ssh-strict: true 2025-09-07T08:57:20.2866137Z ssh-user: git 2025-09-07T08:57:20.2866320Z persist-credentials: true 2025-09-07T08:57:20.2866517Z clean: true 2025-09-07T08:57:20.2866710Z sparse-checkout-cone-mode: true 2025-09-07T08:57:20.2866932Z fetch-tags: false 2025-09-07T08:57:20.2867092Z lfs: false 2025-09-07T08:57:20.2867258Z set-safe-directory: true 2025-09-07T08:57:20.2867442Z env: 2025-09-07T08:57:20.2867599Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:57:20.2867782Z ##[endgroup] 2025-09-07T08:57:20.3824731Z Syncing repository: pytorch/pytorch 2025-09-07T08:57:20.3825953Z ##[group]Getting Git version info 2025-09-07T08:57:20.3826322Z Working directory is '/home/henry/_work/pytorch/pytorch' 2025-09-07T08:57:20.3826800Z [command]/usr/bin/git version 2025-09-07T08:57:20.3828276Z git version 2.50.1 2025-09-07T08:57:20.3852411Z ##[endgroup] 2025-09-07T08:57:20.3863460Z Temporarily overriding HOME='/home/henry/_work/_temp/8887068d-1c19-44f5-88b5-809c9eba0faf' before making global git config changes 2025-09-07T08:57:20.3864251Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T08:57:20.3868052Z [command]/usr/bin/git config --global --add safe.directory /home/henry/_work/pytorch/pytorch 2025-09-07T08:57:20.3903262Z Deleting the contents of '/home/henry/_work/pytorch/pytorch' 2025-09-07T08:57:20.3906227Z ##[group]Initializing the repository 2025-09-07T08:57:20.3909032Z [command]/usr/bin/git init /home/henry/_work/pytorch/pytorch 2025-09-07T08:57:20.3961946Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-09-07T08:57:20.3962571Z hint: is subject to change. To configure the initial branch name to use in all 2025-09-07T08:57:20.3963125Z hint: of your new repositories, which will suppress this warning, call: 2025-09-07T08:57:20.3963516Z hint: 2025-09-07T08:57:20.3963813Z hint: git config --global init.defaultBranch 2025-09-07T08:57:20.3964145Z hint: 2025-09-07T08:57:20.3964493Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-09-07T08:57:20.3965027Z hint: 'development'. The just-created branch can be renamed via this command: 2025-09-07T08:57:20.3965436Z hint: 2025-09-07T08:57:20.3965642Z hint: git branch -m 2025-09-07T08:57:20.3965894Z hint: 2025-09-07T08:57:20.3966242Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-09-07T08:57:20.3966834Z Initialized empty Git repository in /home/henry/_work/pytorch/pytorch/.git/ 2025-09-07T08:57:20.3972531Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-09-07T08:57:20.4013300Z ##[endgroup] 2025-09-07T08:57:20.4013709Z ##[group]Disabling automatic garbage collection 2025-09-07T08:57:20.4016218Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T08:57:20.4044981Z ##[endgroup] 2025-09-07T08:57:20.4045352Z ##[group]Setting up auth 2025-09-07T08:57:20.4050903Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T08:57:20.4079916Z [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' || :" 2025-09-07T08:57:20.4326843Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T08:57:20.4355454Z [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' || :" 2025-09-07T08:57:20.4583606Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T08:57:20.4632832Z ##[endgroup] 2025-09-07T08:57:20.4633217Z ##[group]Fetching the repository 2025-09-07T08:57:20.4639548Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T08:57:59.4804497Z From https://github.com/pytorch/pytorch 2025-09-07T08:57:59.4805048Z * [new branch] 160583 -> origin/160583 2025-09-07T08:57:59.4805918Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-09-07T08:57:59.4806507Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-09-07T08:57:59.4807112Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-09-07T08:57:59.4807754Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-09-07T08:57:59.4809123Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-09-07T08:57:59.4812258Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-09-07T08:57:59.4813630Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-09-07T08:57:59.4815732Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-09-07T08:57:59.4816796Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-09-07T08:57:59.4818544Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-09-07T08:57:59.4819905Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-09-07T08:57:59.4821726Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-09-07T08:57:59.4823491Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-09-07T08:57:59.4824979Z * [new branch] VLA_exp -> origin/VLA_exp 2025-09-07T08:57:59.4827273Z * [new branch] actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor 2025-09-07T08:57:59.4828896Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-09-07T08:57:59.4830698Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-09-07T08:57:59.4832554Z * [new branch] add-vllm-nightly-build -> origin/add-vllm-nightly-build 2025-09-07T08:57:59.4834279Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-09-07T08:57:59.4835604Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-09-07T08:57:59.4837213Z * [new branch] addsimde -> origin/addsimde 2025-09-07T08:57:59.4839415Z * [new branch] addvllmtest -> origin/addvllmtest 2025-09-07T08:57:59.4841454Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-09-07T08:57:59.4842969Z * [new branch] adi/test -> origin/adi/test 2025-09-07T08:57:59.4844557Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-09-07T08:57:59.4846166Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-09-07T08:57:59.4847795Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-09-07T08:57:59.4849630Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-09-07T08:57:59.4851208Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-09-07T08:57:59.4852836Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-09-07T08:57:59.4855542Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-09-07T08:57:59.4857287Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-09-07T08:57:59.4858899Z * [new branch] alt-disable -> origin/alt-disable 2025-09-07T08:57:59.4861537Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-09-07T08:57:59.4863226Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-09-07T08:57:59.4864811Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-09-07T08:57:59.4866560Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-09-07T08:57:59.4868151Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-09-07T08:57:59.4869713Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-09-07T08:57:59.4871668Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-09-07T08:57:59.4873188Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-09-07T08:57:59.4874693Z * [new branch] angelayi/fake_cache_empty -> origin/angelayi/fake_cache_empty 2025-09-07T08:57:59.4876231Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-09-07T08:57:59.4877641Z * [new branch] angelayi/item -> origin/angelayi/item 2025-09-07T08:57:59.4879228Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-09-07T08:57:59.4880942Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-09-07T08:57:59.4882848Z * [new branch] angelayi/pattern -> origin/angelayi/pattern 2025-09-07T08:57:59.4884442Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-09-07T08:57:59.4886315Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-09-07T08:57:59.4887916Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-09-07T08:57:59.4889500Z * [new branch] angelayi/test_cpp -> origin/angelayi/test_cpp 2025-09-07T08:57:59.4891359Z * [new branch] angelayi/torch_size -> origin/angelayi/torch_size 2025-09-07T08:57:59.4893040Z * [new branch] aoti-cuda-alloc -> origin/aoti-cuda-alloc 2025-09-07T08:57:59.4894656Z * [new branch] aoti_target_windows -> origin/aoti_target_windows 2025-09-07T08:57:59.4896254Z * [new branch] aoti_weight_sharing -> origin/aoti_weight_sharing 2025-09-07T08:57:59.4897981Z * [new branch] atalman-inductor-perf-cu124 -> origin/atalman-inductor-perf-cu124 2025-09-07T08:57:59.4899743Z * [new branch] atalman-inductor-perf-cu124.1 -> origin/atalman-inductor-perf-cu124.1 2025-09-07T08:57:59.4901412Z * [new branch] atalman-patch-1 -> origin/atalman-patch-1 2025-09-07T08:57:59.4903180Z * [new branch] atalman-patch-3 -> origin/atalman-patch-3 2025-09-07T08:57:59.4904798Z * [new branch] atalman-patch-4 -> origin/atalman-patch-4 2025-09-07T08:57:59.4906483Z * [new branch] atalman-patch-5 -> origin/atalman-patch-5 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2025-09-07T08:58:00.6848343Z * [new branch] xmfan/ca_fix_polyfills -> origin/xmfan/ca_fix_polyfills 2025-09-07T08:58:00.6849712Z * [new branch] xmfan/ca_jan3 -> origin/xmfan/ca_jan3 2025-09-07T08:58:00.6851510Z * [new branch] xmfan/ca_jun18 -> origin/xmfan/ca_jun18 2025-09-07T08:58:00.6853088Z * [new branch] xmfan/ca_jun24 -> origin/xmfan/ca_jun24 2025-09-07T08:58:00.6854597Z * [new branch] xmfan/ca_mem_base -> origin/xmfan/ca_mem_base 2025-09-07T08:58:00.6856116Z * [new branch] xmfan/ca_mem_fix -> origin/xmfan/ca_mem_fix 2025-09-07T08:58:00.6857677Z * [new branch] xmfan/ca_memory_fix -> origin/xmfan/ca_memory_fix 2025-09-07T08:58:00.6859228Z * [new branch] xmfan/ca_memory_fix_rebased -> origin/xmfan/ca_memory_fix_rebased 2025-09-07T08:58:00.6861051Z * [new branch] xmfan/ca_memory_fix_rebased2 -> origin/xmfan/ca_memory_fix_rebased2 2025-09-07T08:58:00.6862711Z * [new branch] xmfan/ca_move_to_cuda -> origin/xmfan/ca_move_to_cuda 2025-09-07T08:58:00.6864335Z * [new branch] xmfan/ca_nested -> origin/xmfan/ca_nested 2025-09-07T08:58:00.6865957Z * [new branch] xmfan/ca_overhead -> origin/xmfan/ca_overhead 2025-09-07T08:58:00.6867558Z * [new branch] xmfan/ca_overhead_0eba7e5451 -> origin/xmfan/ca_overhead_0eba7e5451 2025-09-07T08:58:00.6869168Z * [new branch] xmfan/ca_scalar -> origin/xmfan/ca_scalar 2025-09-07T08:58:00.6870960Z * [new branch] xmfan/ca_subclass_mem_fix -> origin/xmfan/ca_subclass_mem_fix 2025-09-07T08:58:00.6872571Z * [new branch] xmfan/ca_warm_mem -> origin/xmfan/ca_warm_mem 2025-09-07T08:58:00.6874105Z * [new branch] xmfan/ca_warm_mem_base -> origin/xmfan/ca_warm_mem_base 2025-09-07T08:58:00.6875641Z * [new branch] xmfan/cacu_jun18 -> origin/xmfan/cacu_jun18 2025-09-07T08:58:00.6877141Z * [new branch] xmfan/cacu_jun19 -> origin/xmfan/cacu_jun19 2025-09-07T08:58:00.6878638Z * [new branch] xmfan/cacu_jun4 -> origin/xmfan/cacu_jun4 2025-09-07T08:58:00.6880588Z * [new branch] xmfan/cacu_may27 -> origin/xmfan/cacu_may27 2025-09-07T08:58:00.6882212Z * [new branch] xmfan/disable_duck_shape -> origin/xmfan/disable_duck_shape 2025-09-07T08:58:00.6883788Z * [new branch] xmfan/fca_cpp_node_passthrough -> origin/xmfan/fca_cpp_node_passthrough 2025-09-07T08:58:00.6885235Z * [new branch] xmfan/issue_123374 -> origin/xmfan/issue_123374 2025-09-07T08:58:00.6887003Z * [new branch] xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T08:58:00.6888591Z * [new branch] xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T08:58:00.6890059Z * [new branch] xmfan/segfault_test -> origin/xmfan/segfault_test 2025-09-07T08:58:00.6891903Z * [new branch] xmfan/single_step -> origin/xmfan/single_step 2025-09-07T08:58:00.6893601Z * [new branch] xmfan/sth_0829 -> origin/xmfan/sth_0829 2025-09-07T08:58:00.6895247Z * [new branch] xmfan/test -> origin/xmfan/test 2025-09-07T08:58:00.6897642Z * [new branch] yguo/debug-0226-constexpr -> origin/yguo/debug-0226-constexpr 2025-09-07T08:58:00.6899059Z * [new branch] yguo/new_latest_changes -> origin/yguo/new_latest_changes 2025-09-07T08:58:00.6900695Z * [new branch] yguo/patch_constexpr_changes -> origin/yguo/patch_constexpr_changes 2025-09-07T08:58:00.6902683Z * [new branch] yihan_quantization -> origin/yihan_quantization 2025-09-07T08:58:00.6905089Z * [new branch] yiming/add_jit_trace_benchmark -> origin/yiming/add_jit_trace_benchmark 2025-09-07T08:58:00.6906550Z * [new branch] yiming/add_nativert_benchmark -> origin/yiming/add_nativert_benchmark 2025-09-07T08:58:00.6907976Z * [new branch] yiming/bootcamp -> origin/yiming/bootcamp 2025-09-07T08:58:00.6910196Z * [new branch] zainr/canary-test -> origin/zainr/canary-test 2025-09-07T08:58:00.6912275Z * [new branch] zainr/cleanup-gh-runners -> origin/zainr/cleanup-gh-runners 2025-09-07T08:58:00.6913725Z * [new branch] zainr/git-push-v2 -> origin/zainr/git-push-v2 2025-09-07T08:58:00.6915244Z * [new branch] zainr/pull-migration-c -> origin/zainr/pull-migration-c 2025-09-07T08:58:00.6916788Z * [new branch] zainr/test -> origin/zainr/test 2025-09-07T08:58:00.6918274Z * [new branch] zainr/test2 -> origin/zainr/test2 2025-09-07T08:58:00.6919762Z * [new branch] zainr/unstable -> origin/zainr/unstable 2025-09-07T08:58:00.6921574Z * [new branch] zainr/unstable-xla -> origin/zainr/unstable-xla 2025-09-07T08:58:00.6923488Z * [new branch] zasdfgbnm-patch-3 -> origin/zasdfgbnm-patch-3 2025-09-07T08:58:00.6925126Z * [new branch] zb2p -> origin/zb2p 2025-09-07T08:58:00.6926992Z * [new branch] zero_grad_optimization -> origin/zero_grad_optimization 2025-09-07T08:58:00.6929001Z * [new branch] zeros-and-scatter-part2 -> origin/zeros-and-scatter-part2 2025-09-07T08:58:00.6932093Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-09-07T08:58:00.6934367Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-09-07T08:58:00.6936682Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-09-07T08:58:00.6938045Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-09-07T08:58:00.6939357Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-09-07T08:58:00.6941155Z * [new tag] ciflow/binaries/156049 -> ciflow/binaries/156049 2025-09-07T08:58:00.6941799Z * [new tag] ciflow/binaries/156712 -> ciflow/binaries/156712 2025-09-07T08:58:00.6942836Z * [new tag] ciflow/binaries/157432 -> ciflow/binaries/157432 2025-09-07T08:58:00.6943862Z * [new tag] ciflow/binaries/157685 -> ciflow/binaries/157685 2025-09-07T08:58:00.6944622Z * [new tag] ciflow/binaries/157689 -> ciflow/binaries/157689 2025-09-07T08:58:00.6945570Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-09-07T08:58:00.6946512Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-09-07T08:58:00.6947457Z * [new tag] ciflow/binaries/160720 -> ciflow/binaries/160720 2025-09-07T08:58:00.6948368Z * [new tag] ciflow/binaries/162080 -> ciflow/binaries/162080 2025-09-07T08:58:00.6949079Z * [new tag] ciflow/binaries/162329 -> ciflow/binaries/162329 2025-09-07T08:58:00.6950448Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-09-07T08:58:00.6951452Z * [new tag] ciflow/binaries_libtorch/156711 -> ciflow/binaries_libtorch/156711 2025-09-07T08:58:00.6952198Z * [new tag] ciflow/binaries_libtorch/157432 -> ciflow/binaries_libtorch/157432 2025-09-07T08:58:00.6953514Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-09-07T08:58:00.6954235Z * [new tag] ciflow/binaries_wheel/156711 -> ciflow/binaries_wheel/156711 2025-09-07T08:58:00.6955191Z * [new tag] ciflow/binaries_wheel/157432 -> ciflow/binaries_wheel/157432 2025-09-07T08:58:00.6955953Z * [new tag] ciflow/binaries_wheel/162136 -> ciflow/binaries_wheel/162136 2025-09-07T08:58:00.6957092Z * [new tag] ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252 2025-09-07T08:58:00.6957867Z * [new tag] ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325 2025-09-07T08:58:00.6959201Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-09-07T08:58:00.6960458Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-09-07T08:58:00.6961500Z * [new tag] ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984 2025-09-07T08:58:00.6962276Z * [new tag] ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003 2025-09-07T08:58:00.6963198Z * [new tag] ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011 2025-09-07T08:58:00.6963960Z * [new tag] ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026 2025-09-07T08:58:00.6964837Z * [new tag] ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033 2025-09-07T08:58:00.6965594Z * [new tag] ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040 2025-09-07T08:58:00.6966509Z * [new tag] ciflow/h100-symm-mem/162041 -> ciflow/h100-symm-mem/162041 2025-09-07T08:58:00.6967411Z * [new tag] ciflow/h100-symm-mem/162142 -> ciflow/h100-symm-mem/162142 2025-09-07T08:58:00.6968269Z * [new tag] ciflow/h100-symm-mem/162150 -> ciflow/h100-symm-mem/162150 2025-09-07T08:58:00.6969184Z * [new tag] ciflow/h100-symm-mem/162243 -> ciflow/h100-symm-mem/162243 2025-09-07T08:58:00.6970035Z * [new tag] ciflow/h100-symm-mem/162320 -> ciflow/h100-symm-mem/162320 2025-09-07T08:58:00.6971453Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-09-07T08:58:00.6972713Z * [new tag] ciflow/h100/160480 -> ciflow/h100/160480 2025-09-07T08:58:00.6973664Z * [new tag] ciflow/h100/161749 -> ciflow/h100/161749 2025-09-07T08:58:00.6974730Z * [new tag] ciflow/h100/162022 -> ciflow/h100/162022 2025-09-07T08:58:00.6975376Z * [new tag] ciflow/h100/162278 -> ciflow/h100/162278 2025-09-07T08:58:00.6976882Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592 2025-09-07T08:58:00.6977954Z * [new tag] ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592 2025-09-07T08:58:00.6979100Z * [new tag] ciflow/inductor-periodic/162063 -> ciflow/inductor-periodic/162063 2025-09-07T08:58:00.6979862Z * [new tag] ciflow/inductor-periodic/162227 -> ciflow/inductor-periodic/162227 2025-09-07T08:58:00.6981144Z * [new tag] ciflow/inductor-periodic/162323 -> ciflow/inductor-periodic/162323 2025-09-07T08:58:00.6982375Z * [new tag] ciflow/inductor-rocm/154170 -> ciflow/inductor-rocm/154170 2025-09-07T08:58:00.6983635Z * [new tag] ciflow/inductor-rocm/159146 -> ciflow/inductor-rocm/159146 2025-09-07T08:58:00.6984394Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-09-07T08:58:00.6985441Z * [new tag] ciflow/inductor-rocm/161715 -> ciflow/inductor-rocm/161715 2025-09-07T08:58:00.6986433Z * [new tag] ciflow/inductor-rocm/162053 -> ciflow/inductor-rocm/162053 2025-09-07T08:58:00.6987352Z * [new tag] ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056 2025-09-07T08:58:00.6988528Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-09-07T08:58:00.6989394Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-09-07T08:58:00.6990683Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-09-07T08:58:00.6991362Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-09-07T08:58:00.6992288Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-09-07T08:58:00.6993173Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-09-07T08:58:00.6994044Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-09-07T08:58:00.6994797Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-09-07T08:58:00.6995706Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-09-07T08:58:00.6996449Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-09-07T08:58:00.6997396Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-09-07T08:58:00.6998261Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-09-07T08:58:00.6999101Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-09-07T08:58:00.6999965Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-09-07T08:58:00.7001243Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-09-07T08:58:00.7002288Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-09-07T08:58:00.7003192Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-09-07T08:58:00.7003903Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-09-07T08:58:00.7004986Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-09-07T08:58:00.7005856Z * [new tag] ciflow/inductor/158647 -> ciflow/inductor/158647 2025-09-07T08:58:00.7006918Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-09-07T08:58:00.7007798Z * [new tag] ciflow/inductor/159146 -> ciflow/inductor/159146 2025-09-07T08:58:00.7008811Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-09-07T08:58:00.7009695Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-09-07T08:58:00.7010773Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-09-07T08:58:00.7011932Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-09-07T08:58:00.7012837Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-09-07T08:58:00.7013859Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-09-07T08:58:00.7014937Z * [new tag] ciflow/inductor/160161 -> ciflow/inductor/160161 2025-09-07T08:58:00.7015821Z * [new tag] ciflow/inductor/160174 -> ciflow/inductor/160174 2025-09-07T08:58:00.7016856Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-09-07T08:58:00.7017969Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-09-07T08:58:00.7019081Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-09-07T08:58:00.7020182Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-09-07T08:58:00.7021349Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-09-07T08:58:00.7022454Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-09-07T08:58:00.7023572Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-09-07T08:58:00.7024516Z * [new tag] ciflow/inductor/160480 -> ciflow/inductor/160480 2025-09-07T08:58:00.7025391Z * [new tag] ciflow/inductor/160483 -> ciflow/inductor/160483 2025-09-07T08:58:00.7026534Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-09-07T08:58:00.7027998Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-09-07T08:58:00.7028938Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-09-07T08:58:00.7029829Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-09-07T08:58:00.7030999Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-09-07T08:58:00.7031976Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-09-07T08:58:00.7032920Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-09-07T08:58:00.7033877Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-09-07T08:58:00.7034650Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-09-07T08:58:00.7035672Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-09-07T08:58:00.7036715Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-09-07T08:58:00.7037723Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-09-07T08:58:00.7038634Z * [new tag] ciflow/inductor/160843 -> ciflow/inductor/160843 2025-09-07T08:58:00.7039892Z * [new tag] ciflow/inductor/160869 -> ciflow/inductor/160869 2025-09-07T08:58:00.7041097Z * [new tag] ciflow/inductor/160920 -> ciflow/inductor/160920 2025-09-07T08:58:00.7042077Z * [new tag] ciflow/inductor/160928 -> ciflow/inductor/160928 2025-09-07T08:58:00.7043073Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-09-07T08:58:00.7043988Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-09-07T08:58:00.7044920Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-09-07T08:58:00.7045981Z * [new tag] ciflow/inductor/161109 -> ciflow/inductor/161109 2025-09-07T08:58:00.7047069Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-09-07T08:58:00.7048036Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-09-07T08:58:00.7049025Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-09-07T08:58:00.7049949Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-09-07T08:58:00.7051146Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-09-07T08:58:00.7052117Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-09-07T08:58:00.7053222Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-09-07T08:58:00.7054220Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-09-07T08:58:00.7055146Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-09-07T08:58:00.7056090Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-09-07T08:58:00.7057291Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-09-07T08:58:00.7058232Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-09-07T08:58:00.7059483Z * [new tag] ciflow/inductor/161442 -> ciflow/inductor/161442 2025-09-07T08:58:00.7060555Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-09-07T08:58:00.7062163Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-09-07T08:58:00.7063189Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-09-07T08:58:00.7064336Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-09-07T08:58:00.7065296Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-09-07T08:58:00.7066286Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-09-07T08:58:00.7067215Z * [new tag] ciflow/inductor/161595 -> ciflow/inductor/161595 2025-09-07T08:58:00.7068161Z * [new tag] ciflow/inductor/161596 -> ciflow/inductor/161596 2025-09-07T08:58:00.7069514Z * [new tag] ciflow/inductor/161630 -> ciflow/inductor/161630 2025-09-07T08:58:00.7070681Z * [new tag] ciflow/inductor/161667 -> ciflow/inductor/161667 2025-09-07T08:58:00.7071737Z * [new tag] ciflow/inductor/161670 -> ciflow/inductor/161670 2025-09-07T08:58:00.7072635Z * [new tag] ciflow/inductor/161673 -> ciflow/inductor/161673 2025-09-07T08:58:00.7073604Z * [new tag] ciflow/inductor/161674 -> ciflow/inductor/161674 2025-09-07T08:58:00.7074609Z * [new tag] ciflow/inductor/161675 -> ciflow/inductor/161675 2025-09-07T08:58:00.7075586Z * [new tag] ciflow/inductor/161693 -> ciflow/inductor/161693 2025-09-07T08:58:00.7076530Z * [new tag] ciflow/inductor/161695 -> ciflow/inductor/161695 2025-09-07T08:58:00.7077477Z * [new tag] ciflow/inductor/161715 -> ciflow/inductor/161715 2025-09-07T08:58:00.7078479Z * [new tag] ciflow/inductor/161730 -> ciflow/inductor/161730 2025-09-07T08:58:00.7079434Z * [new tag] ciflow/inductor/161732 -> ciflow/inductor/161732 2025-09-07T08:58:00.7080668Z * [new tag] ciflow/inductor/161744 -> ciflow/inductor/161744 2025-09-07T08:58:00.7081795Z * [new tag] ciflow/inductor/161746 -> ciflow/inductor/161746 2025-09-07T08:58:00.7082772Z * [new tag] ciflow/inductor/161747 -> ciflow/inductor/161747 2025-09-07T08:58:00.7083782Z * [new tag] ciflow/inductor/161819 -> ciflow/inductor/161819 2025-09-07T08:58:00.7084830Z * [new tag] ciflow/inductor/161821 -> ciflow/inductor/161821 2025-09-07T08:58:00.7085988Z * [new tag] ciflow/inductor/161828 -> ciflow/inductor/161828 2025-09-07T08:58:00.7086920Z * [new tag] ciflow/inductor/161879 -> ciflow/inductor/161879 2025-09-07T08:58:00.7087808Z * [new tag] ciflow/inductor/161880 -> ciflow/inductor/161880 2025-09-07T08:58:00.7088760Z * [new tag] ciflow/inductor/161881 -> ciflow/inductor/161881 2025-09-07T08:58:00.7089896Z * [new tag] ciflow/inductor/161907 -> ciflow/inductor/161907 2025-09-07T08:58:00.7091194Z * [new tag] ciflow/inductor/161914 -> ciflow/inductor/161914 2025-09-07T08:58:00.7092356Z * [new tag] ciflow/inductor/161924 -> ciflow/inductor/161924 2025-09-07T08:58:00.7093539Z * [new tag] ciflow/inductor/161936 -> ciflow/inductor/161936 2025-09-07T08:58:00.7094578Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-09-07T08:58:00.7095601Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-09-07T08:58:00.7096588Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-09-07T08:58:00.7097576Z * [new tag] ciflow/inductor/161955 -> ciflow/inductor/161955 2025-09-07T08:58:00.7098528Z * [new tag] ciflow/inductor/161957 -> ciflow/inductor/161957 2025-09-07T08:58:00.7099585Z * [new tag] ciflow/inductor/161975 -> ciflow/inductor/161975 2025-09-07T08:58:00.7100749Z * [new tag] ciflow/inductor/161977 -> ciflow/inductor/161977 2025-09-07T08:58:00.7101846Z * [new tag] ciflow/inductor/161978 -> ciflow/inductor/161978 2025-09-07T08:58:00.7102888Z * [new tag] ciflow/inductor/161979 -> ciflow/inductor/161979 2025-09-07T08:58:00.7103979Z * [new tag] ciflow/inductor/161980 -> ciflow/inductor/161980 2025-09-07T08:58:00.7104977Z * [new tag] ciflow/inductor/161988 -> ciflow/inductor/161988 2025-09-07T08:58:00.7105971Z * [new tag] ciflow/inductor/161994 -> ciflow/inductor/161994 2025-09-07T08:58:00.7106966Z * [new tag] ciflow/inductor/162013 -> ciflow/inductor/162013 2025-09-07T08:58:00.7107984Z * [new tag] ciflow/inductor/162014 -> ciflow/inductor/162014 2025-09-07T08:58:00.7109043Z * [new tag] ciflow/inductor/162017 -> ciflow/inductor/162017 2025-09-07T08:58:00.7110028Z * [new tag] ciflow/inductor/162021 -> ciflow/inductor/162021 2025-09-07T08:58:00.7111452Z * [new tag] ciflow/inductor/162023 -> ciflow/inductor/162023 2025-09-07T08:58:00.7112453Z * [new tag] ciflow/inductor/162027 -> ciflow/inductor/162027 2025-09-07T08:58:00.7113429Z * [new tag] ciflow/inductor/162029 -> ciflow/inductor/162029 2025-09-07T08:58:00.7114441Z * [new tag] ciflow/inductor/162030 -> ciflow/inductor/162030 2025-09-07T08:58:00.7115479Z * [new tag] ciflow/inductor/162031 -> ciflow/inductor/162031 2025-09-07T08:58:00.7116485Z * [new tag] ciflow/inductor/162033 -> ciflow/inductor/162033 2025-09-07T08:58:00.7117771Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-09-07T08:58:00.7118786Z * [new tag] ciflow/inductor/162053 -> ciflow/inductor/162053 2025-09-07T08:58:00.7119812Z * [new tag] ciflow/inductor/162056 -> ciflow/inductor/162056 2025-09-07T08:58:00.7121054Z * [new tag] ciflow/inductor/162063 -> ciflow/inductor/162063 2025-09-07T08:58:00.7122117Z * [new tag] ciflow/inductor/162066 -> ciflow/inductor/162066 2025-09-07T08:58:00.7123157Z * [new tag] ciflow/inductor/162068 -> ciflow/inductor/162068 2025-09-07T08:58:00.7124599Z * [new tag] ciflow/inductor/162081 -> ciflow/inductor/162081 2025-09-07T08:58:00.7125548Z * [new tag] ciflow/inductor/162088 -> ciflow/inductor/162088 2025-09-07T08:58:00.7126545Z * [new tag] ciflow/inductor/162089 -> ciflow/inductor/162089 2025-09-07T08:58:00.7127583Z * [new tag] ciflow/inductor/162094 -> ciflow/inductor/162094 2025-09-07T08:58:00.7128628Z * [new tag] ciflow/inductor/162098 -> ciflow/inductor/162098 2025-09-07T08:58:00.7129625Z * [new tag] ciflow/inductor/162101 -> ciflow/inductor/162101 2025-09-07T08:58:00.7130832Z * [new tag] ciflow/inductor/162102 -> ciflow/inductor/162102 2025-09-07T08:58:00.7131967Z * [new tag] ciflow/inductor/162104 -> ciflow/inductor/162104 2025-09-07T08:58:00.7133042Z * [new tag] ciflow/inductor/162106 -> ciflow/inductor/162106 2025-09-07T08:58:00.7134139Z * [new tag] ciflow/inductor/162108 -> ciflow/inductor/162108 2025-09-07T08:58:00.7135160Z * [new tag] ciflow/inductor/162126 -> ciflow/inductor/162126 2025-09-07T08:58:00.7136182Z * [new tag] ciflow/inductor/162149 -> ciflow/inductor/162149 2025-09-07T08:58:00.7137243Z * [new tag] ciflow/inductor/162164 -> ciflow/inductor/162164 2025-09-07T08:58:00.7138273Z * [new tag] ciflow/inductor/162166 -> ciflow/inductor/162166 2025-09-07T08:58:00.7139323Z * [new tag] ciflow/inductor/162169 -> ciflow/inductor/162169 2025-09-07T08:58:00.7140441Z * [new tag] ciflow/inductor/162170 -> ciflow/inductor/162170 2025-09-07T08:58:00.7142034Z * [new tag] ciflow/inductor/162171 -> ciflow/inductor/162171 2025-09-07T08:58:00.7143177Z * [new tag] ciflow/inductor/162183 -> ciflow/inductor/162183 2025-09-07T08:58:00.7144293Z * [new tag] ciflow/inductor/162189 -> ciflow/inductor/162189 2025-09-07T08:58:00.7145349Z * [new tag] ciflow/inductor/162190 -> ciflow/inductor/162190 2025-09-07T08:58:00.7146386Z * [new tag] ciflow/inductor/162191 -> ciflow/inductor/162191 2025-09-07T08:58:00.7147444Z * [new tag] ciflow/inductor/162194 -> ciflow/inductor/162194 2025-09-07T08:58:00.7148673Z * [new tag] ciflow/inductor/162200 -> ciflow/inductor/162200 2025-09-07T08:58:00.7149736Z * [new tag] ciflow/inductor/162201 -> ciflow/inductor/162201 2025-09-07T08:58:00.7151015Z * [new tag] ciflow/inductor/162208 -> ciflow/inductor/162208 2025-09-07T08:58:00.7152278Z * [new tag] ciflow/inductor/162211 -> ciflow/inductor/162211 2025-09-07T08:58:00.7153290Z * [new tag] ciflow/inductor/162216 -> ciflow/inductor/162216 2025-09-07T08:58:00.7154391Z * [new tag] ciflow/inductor/162220 -> ciflow/inductor/162220 2025-09-07T08:58:00.7155720Z * [new tag] ciflow/inductor/162222 -> ciflow/inductor/162222 2025-09-07T08:58:00.7156796Z * [new tag] ciflow/inductor/162227 -> ciflow/inductor/162227 2025-09-07T08:58:00.7157862Z * [new tag] ciflow/inductor/162238 -> ciflow/inductor/162238 2025-09-07T08:58:00.7158921Z * [new tag] ciflow/inductor/162239 -> ciflow/inductor/162239 2025-09-07T08:58:00.7160004Z * [new tag] ciflow/inductor/162240 -> ciflow/inductor/162240 2025-09-07T08:58:00.7161305Z * [new tag] ciflow/inductor/162244 -> ciflow/inductor/162244 2025-09-07T08:58:00.7162406Z * [new tag] ciflow/inductor/162245 -> ciflow/inductor/162245 2025-09-07T08:58:00.7163529Z * [new tag] ciflow/inductor/162262 -> ciflow/inductor/162262 2025-09-07T08:58:00.7164617Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-09-07T08:58:00.7165846Z * [new tag] ciflow/inductor/162278 -> ciflow/inductor/162278 2025-09-07T08:58:00.7166793Z * [new tag] ciflow/inductor/162284 -> ciflow/inductor/162284 2025-09-07T08:58:00.7167862Z * [new tag] ciflow/inductor/162286 -> ciflow/inductor/162286 2025-09-07T08:58:00.7168930Z * [new tag] ciflow/inductor/162288 -> ciflow/inductor/162288 2025-09-07T08:58:00.7170026Z * [new tag] ciflow/inductor/162293 -> ciflow/inductor/162293 2025-09-07T08:58:00.7171346Z * [new tag] ciflow/inductor/162294 -> ciflow/inductor/162294 2025-09-07T08:58:00.7172469Z * [new tag] ciflow/inductor/162295 -> ciflow/inductor/162295 2025-09-07T08:58:00.7173583Z * [new tag] ciflow/inductor/162296 -> ciflow/inductor/162296 2025-09-07T08:58:00.7174726Z * [new tag] ciflow/inductor/162298 -> ciflow/inductor/162298 2025-09-07T08:58:00.7175832Z * [new tag] ciflow/inductor/162307 -> ciflow/inductor/162307 2025-09-07T08:58:00.7176991Z * [new tag] ciflow/inductor/162309 -> ciflow/inductor/162309 2025-09-07T08:58:00.7178065Z * [new tag] ciflow/inductor/162311 -> ciflow/inductor/162311 2025-09-07T08:58:00.7179169Z * [new tag] ciflow/inductor/162312 -> ciflow/inductor/162312 2025-09-07T08:58:00.7180479Z * [new tag] ciflow/inductor/162315 -> ciflow/inductor/162315 2025-09-07T08:58:00.7181784Z * [new tag] ciflow/inductor/162316 -> ciflow/inductor/162316 2025-09-07T08:58:00.7182934Z * [new tag] ciflow/inductor/162318 -> ciflow/inductor/162318 2025-09-07T08:58:00.7184083Z * [new tag] ciflow/inductor/162323 -> ciflow/inductor/162323 2025-09-07T08:58:00.7185258Z * [new tag] ciflow/inductor/162341 -> ciflow/inductor/162341 2025-09-07T08:58:00.7186397Z * [new tag] ciflow/inductor/162345 -> ciflow/inductor/162345 2025-09-07T08:58:00.7187769Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-09-07T08:58:00.7188981Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-09-07T08:58:00.7190173Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-09-07T08:58:00.7191770Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-09-07T08:58:00.7192713Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-09-07T08:58:00.7193420Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-09-07T08:58:00.7194625Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-09-07T08:58:00.7195493Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-09-07T08:58:00.7196219Z * [new tag] ciflow/mps/161988 -> ciflow/mps/161988 2025-09-07T08:58:00.7197106Z * [new tag] ciflow/mps/162108 -> ciflow/mps/162108 2025-09-07T08:58:00.7198010Z * [new tag] ciflow/mps/162153 -> ciflow/mps/162153 2025-09-07T08:58:00.7198691Z * [new tag] ciflow/mps/162281 -> ciflow/mps/162281 2025-09-07T08:58:00.7199901Z * [new tag] ciflow/nightly/156049 -> ciflow/nightly/156049 2025-09-07T08:58:00.7200947Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-09-07T08:58:00.7202101Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-09-07T08:58:00.7203502Z * [new tag] ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529 2025-09-07T08:58:00.7204269Z * [new tag] ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715 2025-09-07T08:58:00.7205865Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-09-07T08:58:00.7206501Z * [new tag] ciflow/periodic/156703 -> ciflow/periodic/156703 2025-09-07T08:58:00.7207436Z * [new tag] ciflow/periodic/161715 -> ciflow/periodic/161715 2025-09-07T08:58:00.7208193Z * [new tag] ciflow/periodic/162021 -> ciflow/periodic/162021 2025-09-07T08:58:00.7209093Z * [new tag] ciflow/periodic/162323 -> ciflow/periodic/162323 2025-09-07T08:58:00.7210111Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-09-07T08:58:00.7211464Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-09-07T08:58:00.7212468Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-09-07T08:58:00.7213603Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-09-07T08:58:00.7214747Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-09-07T08:58:00.7216231Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-09-07T08:58:00.7217339Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-09-07T08:58:00.7218325Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-09-07T08:58:00.7219438Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-09-07T08:58:00.7221079Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-09-07T08:58:00.7222021Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-09-07T08:58:00.7223290Z * [new tag] ciflow/rocm-mi300/154170 -> ciflow/rocm-mi300/154170 2025-09-07T08:58:00.7224333Z * [new tag] ciflow/rocm-mi300/158747 -> ciflow/rocm-mi300/158747 2025-09-07T08:58:00.7225190Z * [new tag] ciflow/rocm-mi300/159146 -> ciflow/rocm-mi300/159146 2025-09-07T08:58:00.7225941Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-09-07T08:58:00.7226808Z * [new tag] ciflow/rocm-mi300/161715 -> ciflow/rocm-mi300/161715 2025-09-07T08:58:00.7227701Z * [new tag] ciflow/rocm-mi300/161957 -> ciflow/rocm-mi300/161957 2025-09-07T08:58:00.7228445Z * [new tag] ciflow/rocm-mi300/162053 -> ciflow/rocm-mi300/162053 2025-09-07T08:58:00.7229339Z * [new tag] ciflow/rocm-mi300/162056 -> ciflow/rocm-mi300/162056 2025-09-07T08:58:00.7230459Z * [new tag] ciflow/rocm-mi300/162112 -> ciflow/rocm-mi300/162112 2025-09-07T08:58:00.7231544Z * [new tag] ciflow/rocm-mi300/162245 -> ciflow/rocm-mi300/162245 2025-09-07T08:58:00.7232427Z * [new tag] ciflow/rocm-mi300/162278 -> ciflow/rocm-mi300/162278 2025-09-07T08:58:00.7233303Z * [new tag] ciflow/rocm-mi300/162288 -> ciflow/rocm-mi300/162288 2025-09-07T08:58:00.7234477Z * [new tag] ciflow/rocm-mi355/162053 -> ciflow/rocm-mi355/162053 2025-09-07T08:58:00.7235413Z * [new tag] ciflow/rocm-mi355/162056 -> ciflow/rocm-mi355/162056 2025-09-07T08:58:00.7236551Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-09-07T08:58:00.7237388Z * [new tag] ciflow/rocm/154170 -> ciflow/rocm/154170 2025-09-07T08:58:00.7238481Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-09-07T08:58:00.7239396Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-09-07T08:58:00.7240101Z * [new tag] ciflow/rocm/158747 -> ciflow/rocm/158747 2025-09-07T08:58:00.7241322Z * [new tag] ciflow/rocm/159146 -> ciflow/rocm/159146 2025-09-07T08:58:00.7242575Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-09-07T08:58:00.7243256Z * [new tag] ciflow/rocm/161715 -> ciflow/rocm/161715 2025-09-07T08:58:00.7244237Z * [new tag] ciflow/rocm/161972 -> ciflow/rocm/161972 2025-09-07T08:58:00.7245097Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-09-07T08:58:00.7245970Z * [new tag] ciflow/rocm/162053 -> ciflow/rocm/162053 2025-09-07T08:58:00.7246818Z * [new tag] ciflow/rocm/162056 -> ciflow/rocm/162056 2025-09-07T08:58:00.7247543Z * [new tag] ciflow/rocm/162112 -> ciflow/rocm/162112 2025-09-07T08:58:00.7248428Z * [new tag] ciflow/rocm/162278 -> ciflow/rocm/162278 2025-09-07T08:58:00.7249262Z * [new tag] ciflow/rocm/162288 -> ciflow/rocm/162288 2025-09-07T08:58:00.7250150Z * [new tag] ciflow/rocm/162305 -> ciflow/rocm/162305 2025-09-07T08:58:00.7251656Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-09-07T08:58:00.7252641Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-09-07T08:58:00.7254046Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-09-07T08:58:00.7254761Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-09-07T08:58:00.7255646Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-09-07T08:58:00.7256700Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-09-07T08:58:00.7257750Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-09-07T08:58:00.7258725Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-09-07T08:58:00.7259703Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-09-07T08:58:00.7260894Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-09-07T08:58:00.7262003Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-09-07T08:58:00.7263143Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-09-07T08:58:00.7264128Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-09-07T08:58:00.7265519Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-09-07T08:58:00.7266253Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-09-07T08:58:00.7267346Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-09-07T08:58:00.7268402Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-09-07T08:58:00.7269444Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-09-07T08:58:00.7270711Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-09-07T08:58:00.7272303Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-09-07T08:58:00.7273197Z * [new tag] ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329 2025-09-07T08:58:00.7274309Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-09-07T08:58:00.7275156Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-09-07T08:58:00.7276056Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-09-07T08:58:00.7276767Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-09-07T08:58:00.7277705Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-09-07T08:58:00.7279261Z * [new tag] ciflow/trunk/148919 -> ciflow/trunk/148919 2025-09-07T08:58:00.7279858Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-09-07T08:58:00.7280658Z * [new tag] ciflow/trunk/154170 -> ciflow/trunk/154170 2025-09-07T08:58:00.7282007Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-09-07T08:58:00.7282698Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-09-07T08:58:00.7283547Z * [new tag] ciflow/trunk/156703 -> ciflow/trunk/156703 2025-09-07T08:58:00.7284380Z * [new tag] ciflow/trunk/156711 -> ciflow/trunk/156711 2025-09-07T08:58:00.7285213Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-09-07T08:58:00.7286082Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-09-07T08:58:00.7286911Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-09-07T08:58:00.7287755Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-09-07T08:58:00.7288557Z * [new tag] ciflow/trunk/157813 -> ciflow/trunk/157813 2025-09-07T08:58:00.7289397Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-09-07T08:58:00.7290459Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-09-07T08:58:00.7291713Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-09-07T08:58:00.7292358Z * [new tag] ciflow/trunk/158404 -> ciflow/trunk/158404 2025-09-07T08:58:00.7293257Z * [new tag] ciflow/trunk/158647 -> ciflow/trunk/158647 2025-09-07T08:58:00.7294521Z * [new tag] ciflow/trunk/158846 -> ciflow/trunk/158846 2025-09-07T08:58:00.7295186Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-09-07T08:58:00.7296344Z * [new tag] ciflow/trunk/159682 -> ciflow/trunk/159682 2025-09-07T08:58:00.7297074Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-09-07T08:58:00.7297927Z * [new tag] ciflow/trunk/160161 -> ciflow/trunk/160161 2025-09-07T08:58:00.7298795Z * [new tag] ciflow/trunk/160236 -> ciflow/trunk/160236 2025-09-07T08:58:00.7299637Z * [new tag] ciflow/trunk/160329 -> ciflow/trunk/160329 2025-09-07T08:58:00.7300670Z * [new tag] ciflow/trunk/160480 -> ciflow/trunk/160480 2025-09-07T08:58:00.7301811Z * [new tag] ciflow/trunk/160483 -> ciflow/trunk/160483 2025-09-07T08:58:00.7302566Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-09-07T08:58:00.7303826Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-09-07T08:58:00.7304483Z * [new tag] ciflow/trunk/160843 -> ciflow/trunk/160843 2025-09-07T08:58:00.7305381Z * [new tag] ciflow/trunk/160869 -> ciflow/trunk/160869 2025-09-07T08:58:00.7306285Z * [new tag] ciflow/trunk/160928 -> ciflow/trunk/160928 2025-09-07T08:58:00.7307412Z * [new tag] ciflow/trunk/160940 -> ciflow/trunk/160940 2025-09-07T08:58:00.7308210Z * [new tag] ciflow/trunk/160943 -> ciflow/trunk/160943 2025-09-07T08:58:00.7309438Z * [new tag] ciflow/trunk/160953 -> ciflow/trunk/160953 2025-09-07T08:58:00.7310691Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-09-07T08:58:00.7311562Z * [new tag] ciflow/trunk/161178 -> ciflow/trunk/161178 2025-09-07T08:58:00.7312429Z * [new tag] ciflow/trunk/161349 -> ciflow/trunk/161349 2025-09-07T08:58:00.7313513Z * [new tag] ciflow/trunk/161350 -> ciflow/trunk/161350 2025-09-07T08:58:00.7314295Z * [new tag] ciflow/trunk/161351 -> ciflow/trunk/161351 2025-09-07T08:58:00.7315169Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-09-07T08:58:00.7316243Z * [new tag] ciflow/trunk/161405 -> ciflow/trunk/161405 2025-09-07T08:58:00.7317031Z * [new tag] ciflow/trunk/161406 -> ciflow/trunk/161406 2025-09-07T08:58:00.7317923Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-09-07T08:58:00.7318823Z * [new tag] ciflow/trunk/161468 -> ciflow/trunk/161468 2025-09-07T08:58:00.7319752Z * [new tag] ciflow/trunk/161499 -> ciflow/trunk/161499 2025-09-07T08:58:00.7321222Z * [new tag] ciflow/trunk/161527 -> ciflow/trunk/161527 2025-09-07T08:58:00.7322077Z * [new tag] ciflow/trunk/161534 -> ciflow/trunk/161534 2025-09-07T08:58:00.7323017Z * [new tag] ciflow/trunk/161591 -> ciflow/trunk/161591 2025-09-07T08:58:00.7324112Z * [new tag] ciflow/trunk/161595 -> ciflow/trunk/161595 2025-09-07T08:58:00.7324929Z * [new tag] ciflow/trunk/161596 -> ciflow/trunk/161596 2025-09-07T08:58:00.7325816Z * [new tag] ciflow/trunk/161633 -> ciflow/trunk/161633 2025-09-07T08:58:00.7326792Z * [new tag] ciflow/trunk/161634 -> ciflow/trunk/161634 2025-09-07T08:58:00.7327708Z * [new tag] ciflow/trunk/161635 -> ciflow/trunk/161635 2025-09-07T08:58:00.7328812Z * [new tag] ciflow/trunk/161667 -> ciflow/trunk/161667 2025-09-07T08:58:00.7329635Z * [new tag] ciflow/trunk/161670 -> ciflow/trunk/161670 2025-09-07T08:58:00.7330875Z * [new tag] ciflow/trunk/161692 -> ciflow/trunk/161692 2025-09-07T08:58:00.7331766Z * [new tag] ciflow/trunk/161693 -> ciflow/trunk/161693 2025-09-07T08:58:00.7332654Z * [new tag] ciflow/trunk/161695 -> ciflow/trunk/161695 2025-09-07T08:58:00.7333733Z * [new tag] ciflow/trunk/161730 -> ciflow/trunk/161730 2025-09-07T08:58:00.7334534Z * [new tag] ciflow/trunk/161744 -> ciflow/trunk/161744 2025-09-07T08:58:00.7335587Z * [new tag] ciflow/trunk/161749 -> ciflow/trunk/161749 2025-09-07T08:58:00.7336393Z * [new tag] ciflow/trunk/161881 -> ciflow/trunk/161881 2025-09-07T08:58:00.7337403Z * [new tag] ciflow/trunk/161924 -> ciflow/trunk/161924 2025-09-07T08:58:00.7338517Z * [new tag] ciflow/trunk/161926 -> ciflow/trunk/161926 2025-09-07T08:58:00.7339395Z * [new tag] ciflow/trunk/161936 -> ciflow/trunk/161936 2025-09-07T08:58:00.7340407Z * [new tag] ciflow/trunk/161952 -> ciflow/trunk/161952 2025-09-07T08:58:00.7341562Z * [new tag] ciflow/trunk/161955 -> ciflow/trunk/161955 2025-09-07T08:58:00.7342417Z * [new tag] ciflow/trunk/161957 -> ciflow/trunk/161957 2025-09-07T08:58:00.7343592Z * [new tag] ciflow/trunk/161959 -> ciflow/trunk/161959 2025-09-07T08:58:00.7344399Z * [new tag] ciflow/trunk/161977 -> ciflow/trunk/161977 2025-09-07T08:58:00.7345505Z * [new tag] ciflow/trunk/161988 -> ciflow/trunk/161988 2025-09-07T08:58:00.7346276Z * [new tag] ciflow/trunk/161994 -> ciflow/trunk/161994 2025-09-07T08:58:00.7347439Z * [new tag] ciflow/trunk/162007 -> ciflow/trunk/162007 2025-09-07T08:58:00.7348277Z * [new tag] ciflow/trunk/162013 -> ciflow/trunk/162013 2025-09-07T08:58:00.7349346Z * [new tag] ciflow/trunk/162017 -> ciflow/trunk/162017 2025-09-07T08:58:00.7350449Z * [new tag] ciflow/trunk/162021 -> ciflow/trunk/162021 2025-09-07T08:58:00.7351582Z * [new tag] ciflow/trunk/162022 -> ciflow/trunk/162022 2025-09-07T08:58:00.7352389Z * [new tag] ciflow/trunk/162040 -> ciflow/trunk/162040 2025-09-07T08:58:00.7353439Z * [new tag] ciflow/trunk/162041 -> ciflow/trunk/162041 2025-09-07T08:58:00.7354526Z * [new tag] ciflow/trunk/162062 -> ciflow/trunk/162062 2025-09-07T08:58:00.7355428Z * [new tag] ciflow/trunk/162066 -> ciflow/trunk/162066 2025-09-07T08:58:00.7356428Z * [new tag] ciflow/trunk/162089 -> ciflow/trunk/162089 2025-09-07T08:58:00.7357342Z * [new tag] ciflow/trunk/162099 -> ciflow/trunk/162099 2025-09-07T08:58:00.7358385Z * [new tag] ciflow/trunk/162104 -> ciflow/trunk/162104 2025-09-07T08:58:00.7359435Z * [new tag] ciflow/trunk/162106 -> ciflow/trunk/162106 2025-09-07T08:58:00.7360437Z * [new tag] ciflow/trunk/162112 -> ciflow/trunk/162112 2025-09-07T08:58:00.7362026Z * [new tag] ciflow/trunk/162119 -> ciflow/trunk/162119 2025-09-07T08:58:00.7363097Z * [new tag] ciflow/trunk/162142 -> ciflow/trunk/162142 2025-09-07T08:58:00.7364020Z * [new tag] ciflow/trunk/162169 -> ciflow/trunk/162169 2025-09-07T08:58:00.7365065Z * [new tag] ciflow/trunk/162183 -> ciflow/trunk/162183 2025-09-07T08:58:00.7365960Z * [new tag] ciflow/trunk/162190 -> ciflow/trunk/162190 2025-09-07T08:58:00.7367116Z * [new tag] ciflow/trunk/162194 -> ciflow/trunk/162194 2025-09-07T08:58:00.7368140Z * [new tag] ciflow/trunk/162200 -> ciflow/trunk/162200 2025-09-07T08:58:00.7369213Z * [new tag] ciflow/trunk/162206 -> ciflow/trunk/162206 2025-09-07T08:58:00.7370098Z * [new tag] ciflow/trunk/162208 -> ciflow/trunk/162208 2025-09-07T08:58:00.7371440Z * [new tag] ciflow/trunk/162222 -> ciflow/trunk/162222 2025-09-07T08:58:00.7372336Z * [new tag] ciflow/trunk/162238 -> ciflow/trunk/162238 2025-09-07T08:58:00.7373396Z * [new tag] ciflow/trunk/162244 -> ciflow/trunk/162244 2025-09-07T08:58:00.7374713Z * [new tag] ciflow/trunk/162267 -> ciflow/trunk/162267 2025-09-07T08:58:00.7375867Z * [new tag] ciflow/trunk/162269 -> ciflow/trunk/162269 2025-09-07T08:58:00.7376912Z * [new tag] ciflow/trunk/162278 -> ciflow/trunk/162278 2025-09-07T08:58:00.7377827Z * [new tag] ciflow/trunk/162286 -> ciflow/trunk/162286 2025-09-07T08:58:00.7378916Z * [new tag] ciflow/trunk/162288 -> ciflow/trunk/162288 2025-09-07T08:58:00.7379946Z * [new tag] ciflow/trunk/162293 -> ciflow/trunk/162293 2025-09-07T08:58:00.7381230Z * [new tag] ciflow/trunk/162310 -> ciflow/trunk/162310 2025-09-07T08:58:00.7382295Z * [new tag] ciflow/trunk/162311 -> ciflow/trunk/162311 2025-09-07T08:58:00.7383435Z * [new tag] ciflow/trunk/162315 -> ciflow/trunk/162315 2025-09-07T08:58:00.7384515Z * [new tag] ciflow/trunk/162325 -> ciflow/trunk/162325 2025-09-07T08:58:00.7385752Z * [new tag] ciflow/trunk/162328 -> ciflow/trunk/162328 2025-09-07T08:58:00.7386830Z * [new tag] ciflow/trunk/162329 -> ciflow/trunk/162329 2025-09-07T08:58:00.7388139Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-09-07T08:58:00.7389310Z * [new tag] ciflow/vllm/162292 -> ciflow/vllm/162292 2025-09-07T08:58:00.7390654Z * [new tag] ciflow/win-arm64/156049 -> ciflow/win-arm64/156049 2025-09-07T08:58:00.7391712Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-09-07T08:58:00.7392737Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-09-07T08:58:00.7393517Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-09-07T08:58:00.7394589Z * [new tag] ciflow/xpu/159459 -> ciflow/xpu/159459 2025-09-07T08:58:00.7395353Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-09-07T08:58:00.7396224Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-09-07T08:58:00.7397278Z * [new tag] ciflow/xpu/160867 -> ciflow/xpu/160867 2025-09-07T08:58:00.7398164Z * [new tag] ciflow/xpu/160938 -> ciflow/xpu/160938 2025-09-07T08:58:00.7399010Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-09-07T08:58:00.7399824Z * [new tag] ciflow/xpu/160953 -> ciflow/xpu/160953 2025-09-07T08:58:00.7401207Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-09-07T08:58:00.7402261Z * [new tag] ciflow/xpu/161058 -> ciflow/xpu/161058 2025-09-07T08:58:00.7403029Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-09-07T08:58:00.7403880Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-09-07T08:58:00.7404735Z * [new tag] ciflow/xpu/161485 -> ciflow/xpu/161485 2025-09-07T08:58:00.7405577Z * [new tag] ciflow/xpu/161988 -> ciflow/xpu/161988 2025-09-07T08:58:00.7406430Z * [new tag] ciflow/xpu/162062 -> ciflow/xpu/162062 2025-09-07T08:58:00.7407559Z * [new tag] cslpull75 -> cslpull75 2025-09-07T08:58:00.7408348Z * [new tag] cslpull76 -> cslpull76 2025-09-07T08:58:00.7409201Z * [new tag] cslpull77 -> cslpull77 2025-09-07T08:58:00.7410336Z * [new tag] cslpull78 -> cslpull78 2025-09-07T08:58:00.7411385Z * [new tag] cslpull79 -> cslpull79 2025-09-07T08:58:00.7412196Z * [new tag] cslpull80 -> cslpull80 2025-09-07T08:58:00.7413239Z * [new tag] cslpull81 -> cslpull81 2025-09-07T08:58:00.7414162Z * [new tag] cslpull82 -> cslpull82 2025-09-07T08:58:00.7415153Z * [new tag] cslpull83 -> cslpull83 2025-09-07T08:58:00.7416003Z * [new tag] cslpull84 -> cslpull84 2025-09-07T08:58:00.7416974Z * [new tag] cslpull85 -> cslpull85 2025-09-07T08:58:00.7417856Z * [new tag] cslpull86 -> cslpull86 2025-09-07T08:58:00.7418912Z * [new tag] cslpull87 -> cslpull87 2025-09-07T08:58:00.7419878Z * [new tag] cslpull88 -> cslpull88 2025-09-07T08:58:00.7421072Z * [new tag] cslpull89 -> cslpull89 2025-09-07T08:58:00.7421840Z * [new tag] cslpull90 -> cslpull90 2025-09-07T08:58:00.7423405Z * [new tag] cslpull91 -> cslpull91 2025-09-07T08:58:00.7424275Z * [new tag] cslpull92 -> cslpull92 2025-09-07T08:58:00.7425282Z * [new tag] flight_5 -> flight_5 2025-09-07T08:58:00.7426182Z * [new tag] flight_5.1 -> flight_5.1 2025-09-07T08:58:00.7427291Z * [new tag] flight_5.2 -> flight_5.2 2025-09-07T08:58:00.7428189Z * [new tag] flight_5.3 -> flight_5.3 2025-09-07T08:58:00.7429376Z * [new tag] forpull1 -> forpull1 2025-09-07T08:58:00.7430678Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-09-07T08:58:00.7431888Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-09-07T08:58:00.7432806Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-09-07T08:58:00.7433855Z * [new tag] nightly-binary -> nightly-binary 2025-09-07T08:58:00.7434629Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-09-07T08:58:00.7435812Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-09-07T08:58:00.7437287Z * [new tag] trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608 2025-09-07T08:58:00.7438310Z * [new tag] trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 2025-09-07T08:58:00.7439318Z * [new tag] trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544 2025-09-07T08:58:00.7440484Z * [new tag] trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b 2025-09-07T08:58:00.7441726Z * [new tag] trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388 2025-09-07T08:58:00.7442763Z * [new tag] trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 2025-09-07T08:58:00.7443773Z * [new tag] trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4 2025-09-07T08:58:00.7444774Z * [new tag] trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 2025-09-07T08:58:00.7445970Z * [new tag] trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23 2025-09-07T08:58:00.7446976Z * [new tag] trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 2025-09-07T08:58:00.7448032Z * [new tag] trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 2025-09-07T08:58:00.7448995Z * [new tag] trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 2025-09-07T08:58:00.7449980Z * [new tag] trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 2025-09-07T08:58:00.7451852Z * [new tag] trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 2025-09-07T08:58:00.7452758Z * [new tag] trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 2025-09-07T08:58:00.7453751Z * [new tag] trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c 2025-09-07T08:58:00.7454917Z * [new tag] trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 2025-09-07T08:58:00.7455909Z * [new tag] trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e 2025-09-07T08:58:00.7456924Z * [new tag] trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 2025-09-07T08:58:00.7457983Z * [new tag] trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f 2025-09-07T08:58:00.7458935Z * [new tag] trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f 2025-09-07T08:58:00.7460038Z * [new tag] trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0 2025-09-07T08:58:00.7461452Z * [new tag] trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c 2025-09-07T08:58:00.7462312Z * [new tag] trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 2025-09-07T08:58:00.7463354Z * [new tag] trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 2025-09-07T08:58:00.7464488Z * [new tag] trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb 2025-09-07T08:58:00.7465518Z * [new tag] trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 2025-09-07T08:58:00.7466581Z * [new tag] trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 2025-09-07T08:58:00.7468144Z * [new tag] trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c 2025-09-07T08:58:00.7469043Z * [new tag] trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 2025-09-07T08:58:00.7470147Z * [new tag] trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 2025-09-07T08:58:00.7471272Z * [new tag] trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 2025-09-07T08:58:00.7472343Z * [new tag] trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a 2025-09-07T08:58:00.7473344Z * [new tag] trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 2025-09-07T08:58:00.7474449Z * [new tag] trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 2025-09-07T08:58:00.7475463Z * [new tag] trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a 2025-09-07T08:58:00.7477105Z * [new tag] trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b 2025-09-07T08:58:00.7478018Z * [new tag] trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc 2025-09-07T08:58:00.7479148Z * [new tag] trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05 2025-09-07T08:58:00.7480131Z * [new tag] trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 2025-09-07T08:58:00.7481612Z * [new tag] trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd 2025-09-07T08:58:00.7482540Z * [new tag] trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 2025-09-07T08:58:00.7483587Z * [new tag] trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f 2025-09-07T08:58:00.7484581Z * [new tag] trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23 2025-09-07T08:58:00.7485592Z * [new tag] trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 2025-09-07T08:58:00.7486919Z * [new tag] trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f 2025-09-07T08:58:00.7487903Z * [new tag] trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 2025-09-07T08:58:00.7488934Z * [new tag] trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9 2025-09-07T08:58:00.7490109Z * [new tag] trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 2025-09-07T08:58:00.7491318Z * [new tag] trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef 2025-09-07T08:58:00.7492516Z * [new tag] trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c 2025-09-07T08:58:00.7494449Z * [new tag] trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6 2025-09-07T08:58:00.7495077Z * [new tag] trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 2025-09-07T08:58:00.7495911Z * [new tag] trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a 2025-09-07T08:58:00.7496803Z * [new tag] trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 2025-09-07T08:58:00.7497745Z * [new tag] trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 2025-09-07T08:58:00.7498786Z * [new tag] trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 2025-09-07T08:58:00.7499724Z * [new tag] trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 2025-09-07T08:58:00.7501108Z * [new tag] trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176 2025-09-07T08:58:00.7502142Z * [new tag] trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 2025-09-07T08:58:00.7503151Z * [new tag] trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b 2025-09-07T08:58:00.7504062Z * [new tag] trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 2025-09-07T08:58:00.7505154Z * [new tag] trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287 2025-09-07T08:58:00.7506183Z * [new tag] trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f 2025-09-07T08:58:00.7507214Z * [new tag] trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 2025-09-07T08:58:00.7508322Z * [new tag] trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 2025-09-07T08:58:00.7509523Z * [new tag] trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f 2025-09-07T08:58:00.7510783Z * [new tag] trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf 2025-09-07T08:58:00.7511890Z * [new tag] trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 2025-09-07T08:58:00.7512916Z * [new tag] trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d 2025-09-07T08:58:00.7513979Z * [new tag] trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa 2025-09-07T08:58:00.7515175Z * [new tag] trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 2025-09-07T08:58:00.7516214Z * [new tag] trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336 2025-09-07T08:58:00.7517346Z * [new tag] trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63 2025-09-07T08:58:00.7518428Z * [new tag] trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3 2025-09-07T08:58:00.7519564Z * [new tag] trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c 2025-09-07T08:58:00.7520570Z * [new tag] trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 2025-09-07T08:58:00.7522042Z * [new tag] trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf 2025-09-07T08:58:00.7522934Z * [new tag] trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e 2025-09-07T08:58:00.7524096Z * [new tag] trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 2025-09-07T08:58:00.7525172Z * [new tag] trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215 2025-09-07T08:58:00.7526332Z * [new tag] trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d 2025-09-07T08:58:00.7527417Z * [new tag] trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 2025-09-07T08:58:00.7529170Z * [new tag] trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c 2025-09-07T08:58:00.7530387Z * [new tag] trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 2025-09-07T08:58:00.7531502Z * [new tag] trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b 2025-09-07T08:58:00.7532896Z * [new tag] trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 2025-09-07T08:58:00.7533896Z * [new tag] trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503 2025-09-07T08:58:00.7535035Z * [new tag] trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 2025-09-07T08:58:00.7536151Z * [new tag] trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 2025-09-07T08:58:00.7537313Z * [new tag] trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 2025-09-07T08:58:00.7538420Z * [new tag] trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 2025-09-07T08:58:00.7539547Z * [new tag] trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a 2025-09-07T08:58:00.7540747Z * [new tag] trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 2025-09-07T08:58:00.7542076Z * [new tag] trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 2025-09-07T08:58:00.7543225Z * [new tag] trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c 2025-09-07T08:58:00.7544370Z * [new tag] trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 2025-09-07T08:58:00.7545547Z * [new tag] trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806 2025-09-07T08:58:00.7546628Z * [new tag] trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 2025-09-07T08:58:00.7547702Z * [new tag] trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 2025-09-07T08:58:00.7548828Z * [new tag] trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 2025-09-07T08:58:00.7550107Z * [new tag] trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251 2025-09-07T08:58:00.7552032Z * [new tag] trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 2025-09-07T08:58:00.7552931Z * [new tag] trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c 2025-09-07T08:58:00.7554093Z * [new tag] trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a 2025-09-07T08:58:00.7555292Z * [new tag] trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db 2025-09-07T08:58:00.7556436Z * [new tag] trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536 2025-09-07T08:58:00.7557548Z * [new tag] trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f 2025-09-07T08:58:00.7558670Z * [new tag] trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 2025-09-07T08:58:00.7559810Z * [new tag] trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b 2025-09-07T08:58:00.7561343Z * [new tag] trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda 2025-09-07T08:58:00.7562421Z * [new tag] trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b 2025-09-07T08:58:00.7563609Z * [new tag] trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 2025-09-07T08:58:00.7564756Z * [new tag] trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8 2025-09-07T08:58:00.7565958Z * [new tag] trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b 2025-09-07T08:58:00.7567085Z * [new tag] trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab 2025-09-07T08:58:00.7568434Z * [new tag] trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 2025-09-07T08:58:00.7569357Z * [new tag] trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe 2025-09-07T08:58:00.7570527Z * [new tag] trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 2025-09-07T08:58:00.7571728Z * [new tag] trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 2025-09-07T08:58:00.7572700Z * [new tag] trunk/7a83cf430e97d83d6fb14880b9049e77ff725685 -> trunk/7a83cf430e97d83d6fb14880b9049e77ff725685 2025-09-07T08:58:00.7573852Z * [new tag] trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 2025-09-07T08:58:00.7574928Z * [new tag] trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c 2025-09-07T08:58:00.7576074Z * [new tag] trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d 2025-09-07T08:58:00.7577061Z * [new tag] trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429 2025-09-07T08:58:00.7578224Z * [new tag] trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 2025-09-07T08:58:00.7579600Z * [new tag] trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c 2025-09-07T08:58:00.7580941Z * [new tag] trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895 2025-09-07T08:58:00.7582038Z * [new tag] trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 2025-09-07T08:58:00.7583261Z * [new tag] trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435 2025-09-07T08:58:00.7584609Z * [new tag] trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965 2025-09-07T08:58:00.7585699Z * [new tag] trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 2025-09-07T08:58:00.7586911Z * [new tag] trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 2025-09-07T08:58:00.7588285Z * [new tag] trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 2025-09-07T08:58:00.7589439Z * [new tag] trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 2025-09-07T08:58:00.7590933Z * [new tag] trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 2025-09-07T08:58:00.7592236Z * [new tag] trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f 2025-09-07T08:58:00.7593372Z * [new tag] trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 2025-09-07T08:58:00.7597155Z * [new tag] trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610 2025-09-07T08:58:00.7598248Z * [new tag] trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 2025-09-07T08:58:00.7599429Z * [new tag] trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af 2025-09-07T08:58:00.7601620Z * [new tag] trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 2025-09-07T08:58:00.7602954Z * [new tag] trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d 2025-09-07T08:58:00.7604089Z * [new tag] trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 2025-09-07T08:58:00.7605286Z * [new tag] trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 2025-09-07T08:58:00.7606637Z * [new tag] trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab 2025-09-07T08:58:00.7607735Z * [new tag] trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d 2025-09-07T08:58:00.7609101Z * [new tag] trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:58:00.7610325Z * [new tag] trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c 2025-09-07T08:58:00.7611813Z * [new tag] trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e 2025-09-07T08:58:00.7613265Z * [new tag] trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 2025-09-07T08:58:00.7614294Z * [new tag] trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1 2025-09-07T08:58:00.7615420Z * [new tag] trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 2025-09-07T08:58:00.7616553Z * [new tag] trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a 2025-09-07T08:58:00.7618064Z * [new tag] trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500 2025-09-07T08:58:00.7619030Z * [new tag] trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 2025-09-07T08:58:00.7620099Z * [new tag] trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6 2025-09-07T08:58:00.7621621Z * [new tag] trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 2025-09-07T08:58:00.7622850Z * [new tag] trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd 2025-09-07T08:58:00.7624215Z * [new tag] trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57 2025-09-07T08:58:00.7625243Z * [new tag] trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4 2025-09-07T08:58:00.7626334Z * [new tag] trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e 2025-09-07T08:58:00.7627390Z * [new tag] trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839 2025-09-07T08:58:00.7628502Z * [new tag] trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60 2025-09-07T08:58:00.7629753Z * [new tag] trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 2025-09-07T08:58:00.7631284Z * [new tag] trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 2025-09-07T08:58:00.7632359Z * [new tag] trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 2025-09-07T08:58:00.7633453Z * [new tag] trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 2025-09-07T08:58:00.7634546Z * [new tag] trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d 2025-09-07T08:58:00.7635650Z * [new tag] trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 2025-09-07T08:58:00.7636776Z * [new tag] trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92 2025-09-07T08:58:00.7646384Z * [new tag] trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098 2025-09-07T08:58:00.7647064Z * [new tag] trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356 2025-09-07T08:58:00.7647698Z * [new tag] trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae 2025-09-07T08:58:00.7648354Z * [new tag] trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 2025-09-07T08:58:00.7648986Z * [new tag] trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e 2025-09-07T08:58:00.7649599Z * [new tag] trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 2025-09-07T08:58:00.7650380Z * [new tag] trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 2025-09-07T08:58:00.7651010Z * [new tag] trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c 2025-09-07T08:58:00.7651635Z * [new tag] trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 2025-09-07T08:58:00.7652503Z * [new tag] trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d 2025-09-07T08:58:00.7653136Z * [new tag] trunk/ada43ed39c80b746b4822c92640a1882619e2795 -> trunk/ada43ed39c80b746b4822c92640a1882619e2795 2025-09-07T08:58:00.7653741Z * [new tag] trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa 2025-09-07T08:58:00.7654366Z * [new tag] trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c 2025-09-07T08:58:00.7654973Z * [new tag] trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d 2025-09-07T08:58:00.7655586Z * [new tag] trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 2025-09-07T08:58:00.7656366Z * [new tag] trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f 2025-09-07T08:58:00.7657339Z * [new tag] trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 2025-09-07T08:58:00.7658502Z * [new tag] trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 2025-09-07T08:58:00.7659682Z * [new tag] trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de 2025-09-07T08:58:00.7661101Z * [new tag] trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b 2025-09-07T08:58:00.7662380Z * [new tag] trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 2025-09-07T08:58:00.7663627Z * [new tag] trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 2025-09-07T08:58:00.7664820Z * [new tag] trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b 2025-09-07T08:58:00.7666039Z * [new tag] trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde 2025-09-07T08:58:00.7667293Z * [new tag] trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c 2025-09-07T08:58:00.7668390Z * [new tag] trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 2025-09-07T08:58:00.7670016Z * [new tag] trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052 2025-09-07T08:58:00.7671319Z * [new tag] trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e 2025-09-07T08:58:00.7672508Z * [new tag] trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 2025-09-07T08:58:00.7673599Z * [new tag] trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 2025-09-07T08:58:00.7674795Z * [new tag] trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85 2025-09-07T08:58:00.7676198Z * [new tag] trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d 2025-09-07T08:58:00.7677004Z * [new tag] trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 2025-09-07T08:58:00.7678095Z * [new tag] trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865 2025-09-07T08:58:00.7679274Z * [new tag] trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 2025-09-07T08:58:00.7680620Z * [new tag] trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 2025-09-07T08:58:00.7682198Z * [new tag] trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 2025-09-07T08:58:00.7683048Z * [new tag] trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf 2025-09-07T08:58:00.7684154Z * [new tag] trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 2025-09-07T08:58:00.7685347Z * [new tag] trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad 2025-09-07T08:58:00.7686461Z * [new tag] trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 2025-09-07T08:58:00.7687636Z * [new tag] trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 2025-09-07T08:58:00.7688997Z * [new tag] trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76 2025-09-07T08:58:00.7689943Z * [new tag] trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5 2025-09-07T08:58:00.7691454Z * [new tag] trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 2025-09-07T08:58:00.7692489Z * [new tag] trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd 2025-09-07T08:58:00.7693657Z * [new tag] trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741 2025-09-07T08:58:00.7694769Z * [new tag] trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b 2025-09-07T08:58:00.7695762Z * [new tag] trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 2025-09-07T08:58:00.7696984Z * [new tag] trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 2025-09-07T08:58:00.7698115Z * [new tag] trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b 2025-09-07T08:58:00.7699246Z * [new tag] trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8 2025-09-07T08:58:00.7700602Z * [new tag] trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 2025-09-07T08:58:00.7702151Z * [new tag] trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7 2025-09-07T08:58:00.7703326Z * [new tag] trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87 2025-09-07T08:58:00.7704526Z * [new tag] trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e 2025-09-07T08:58:00.7705620Z * [new tag] trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e 2025-09-07T08:58:00.7707019Z * [new tag] trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d 2025-09-07T08:58:00.7708095Z * [new tag] trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 2025-09-07T08:58:00.7709198Z * [new tag] trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e 2025-09-07T08:58:00.7710429Z * [new tag] trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 2025-09-07T08:58:00.7711659Z * [new tag] trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 2025-09-07T08:58:00.7713008Z * [new tag] trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 2025-09-07T08:58:00.7713825Z * [new tag] trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462 2025-09-07T08:58:00.7715017Z * [new tag] trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 2025-09-07T08:58:00.7716737Z * [new tag] trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285 2025-09-07T08:58:00.7717788Z * [new tag] trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643 2025-09-07T08:58:00.7718941Z * [new tag] trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 2025-09-07T08:58:00.7720083Z * [new tag] trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661 2025-09-07T08:58:00.7721786Z * [new tag] trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab 2025-09-07T08:58:00.7722815Z * [new tag] trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 2025-09-07T08:58:00.7723792Z * [new tag] trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 2025-09-07T08:58:00.7725023Z * [new tag] trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061 2025-09-07T08:58:00.7725994Z * [new tag] trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a 2025-09-07T08:58:00.7727144Z * [new tag] trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 2025-09-07T08:58:00.7728319Z * [new tag] trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d 2025-09-07T08:58:00.7729537Z * [new tag] trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717 2025-09-07T08:58:00.7731093Z * [new tag] trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 2025-09-07T08:58:00.7732191Z * [new tag] trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 2025-09-07T08:58:00.7733402Z * [new tag] trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439 2025-09-07T08:58:00.7734482Z * [new tag] trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 2025-09-07T08:58:00.7735645Z * [new tag] trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 2025-09-07T08:58:00.7736673Z * [new tag] trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 2025-09-07T08:58:00.7737798Z * [new tag] trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b 2025-09-07T08:58:00.7738952Z * [new tag] trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090 2025-09-07T08:58:00.7740033Z * [new tag] trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087 2025-09-07T08:58:00.7741555Z * [new tag] trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 2025-09-07T08:58:00.7742552Z * [new tag] trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de 2025-09-07T08:58:00.7743705Z * [new tag] trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 2025-09-07T08:58:00.7744970Z * [new tag] trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 2025-09-07T08:58:00.7745969Z * [new tag] trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b 2025-09-07T08:58:00.7747138Z * [new tag] trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37 2025-09-07T08:58:00.7748456Z * [new tag] trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 2025-09-07T08:58:00.7749623Z * [new tag] trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd 2025-09-07T08:58:00.7750974Z * [new tag] trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb 2025-09-07T08:58:00.7752086Z * [new tag] trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c 2025-09-07T08:58:00.7753205Z * [new tag] trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8 2025-09-07T08:58:00.7754340Z * [new tag] trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c 2025-09-07T08:58:00.7755504Z * [new tag] trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c 2025-09-07T08:58:00.7756630Z * [new tag] trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 2025-09-07T08:58:00.7757811Z * [new tag] trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 2025-09-07T08:58:00.7759239Z * [new tag] trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa 2025-09-07T08:58:00.7760354Z * [new tag] trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab 2025-09-07T08:58:00.7761558Z * [new tag] trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd 2025-09-07T08:58:00.7762418Z * [new tag] v0.1.1 -> v0.1.1 2025-09-07T08:58:00.7763540Z * [new tag] v0.1.10 -> v0.1.10 2025-09-07T08:58:00.7764554Z * [new tag] v0.1.11 -> v0.1.11 2025-09-07T08:58:00.7765644Z * [new tag] v0.1.12 -> v0.1.12 2025-09-07T08:58:00.7766493Z * [new tag] v0.1.2 -> v0.1.2 2025-09-07T08:58:00.7767562Z * [new tag] v0.1.3 -> v0.1.3 2025-09-07T08:58:00.7768421Z * [new tag] v0.1.4 -> v0.1.4 2025-09-07T08:58:00.7769574Z * [new tag] v0.1.5 -> v0.1.5 2025-09-07T08:58:00.7771123Z * [new tag] v0.1.6 -> v0.1.6 2025-09-07T08:58:00.7771991Z * [new tag] v0.1.7 -> v0.1.7 2025-09-07T08:58:00.7773007Z * [new tag] v0.1.8 -> v0.1.8 2025-09-07T08:58:00.7774006Z * [new tag] v0.1.9 -> v0.1.9 2025-09-07T08:58:00.7775086Z * [new tag] v0.2.0 -> v0.2.0 2025-09-07T08:58:00.7776242Z * [new tag] v0.3.0 -> v0.3.0 2025-09-07T08:58:00.7777157Z * [new tag] v0.3.1 -> v0.3.1 2025-09-07T08:58:00.7778291Z * [new tag] v0.4.0 -> v0.4.0 2025-09-07T08:58:00.7779214Z * [new tag] v0.4.1 -> v0.4.1 2025-09-07T08:58:00.7780655Z * [new tag] v1.0.0 -> v1.0.0 2025-09-07T08:58:00.7782050Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-09-07T08:58:00.7782863Z * [new tag] v1.0.1 -> v1.0.1 2025-09-07T08:58:00.7784097Z * [new tag] v1.0rc0 -> v1.0rc0 2025-09-07T08:58:00.7784863Z * [new tag] v1.0rc1 -> v1.0rc1 2025-09-07T08:58:00.7786048Z * [new tag] v1.1.0 -> v1.1.0 2025-09-07T08:58:00.7787144Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-09-07T08:58:00.7788393Z * [new tag] v1.10.0 -> v1.10.0 2025-09-07T08:58:00.7789594Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-09-07T08:58:00.7790983Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-09-07T08:58:00.7791916Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-09-07T08:58:00.7793100Z * [new tag] v1.10.1 -> v1.10.1 2025-09-07T08:58:00.7793937Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-09-07T08:58:00.7794813Z * [new tag] v1.10.2 -> v1.10.2 2025-09-07T08:58:00.7795705Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-09-07T08:58:00.7796857Z * [new tag] v1.11.0 -> v1.11.0 2025-09-07T08:58:00.7797978Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-09-07T08:58:00.7799224Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-09-07T08:58:00.7800493Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-09-07T08:58:00.7801841Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-09-07T08:58:00.7802989Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-09-07T08:58:00.7803811Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-09-07T08:58:00.7804696Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-09-07T08:58:00.7805964Z * [new tag] v1.12.0 -> v1.12.0 2025-09-07T08:58:00.7807109Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-09-07T08:58:00.7808280Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-09-07T08:58:00.7809447Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-09-07T08:58:00.7810825Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-09-07T08:58:00.7812071Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-09-07T08:58:00.7813250Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-09-07T08:58:00.7814056Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-09-07T08:58:00.7815030Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-09-07T08:58:00.7815826Z * [new tag] v1.12.1 -> v1.12.1 2025-09-07T08:58:00.7817187Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-09-07T08:58:00.7818344Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-09-07T08:58:00.7819543Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-09-07T08:58:00.7820942Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-09-07T08:58:00.7821965Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-09-07T08:58:00.7823248Z * [new tag] v1.13.0 -> v1.13.0 2025-09-07T08:58:00.7824299Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-09-07T08:58:00.7825362Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-09-07T08:58:00.7826520Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-09-07T08:58:00.7828035Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-09-07T08:58:00.7828727Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-09-07T08:58:00.7829628Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-09-07T08:58:00.7831125Z * [new tag] v1.13.1 -> v1.13.1 2025-09-07T08:58:00.7831978Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-09-07T08:58:00.7833224Z * [new tag] v1.2.0 -> v1.2.0 2025-09-07T08:58:00.7834370Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-09-07T08:58:00.7835518Z * [new tag] v1.3.0 -> v1.3.0 2025-09-07T08:58:00.7836665Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-09-07T08:58:00.7837637Z * [new tag] v1.3.1 -> v1.3.1 2025-09-07T08:58:00.7838759Z * [new tag] v1.4.0 -> v1.4.0 2025-09-07T08:58:00.7839844Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-09-07T08:58:00.7841012Z * [new tag] v1.4.1 -> v1.4.1 2025-09-07T08:58:00.7842274Z * [new tag] v1.5.0 -> v1.5.0 2025-09-07T08:58:00.7843488Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-09-07T08:58:00.7844681Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-09-07T08:58:00.7845905Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-09-07T08:58:00.7847051Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-09-07T08:58:00.7847991Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-09-07T08:58:00.7849160Z * [new tag] v1.5.1 -> v1.5.1 2025-09-07T08:58:00.7850101Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-09-07T08:58:00.7851244Z * [new tag] v1.6.0 -> v1.6.0 2025-09-07T08:58:00.7852368Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-09-07T08:58:00.7853639Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-09-07T08:58:00.7854835Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-09-07T08:58:00.7855956Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-09-07T08:58:00.7857050Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-09-07T08:58:00.7858267Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-09-07T08:58:00.7859227Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-09-07T08:58:00.7860565Z * [new tag] v1.7.0 -> v1.7.0 2025-09-07T08:58:00.7861825Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-09-07T08:58:00.7863198Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-09-07T08:58:00.7864466Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-09-07T08:58:00.7865414Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-09-07T08:58:00.7866581Z * [new tag] v1.7.1 -> v1.7.1 2025-09-07T08:58:00.7867855Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-09-07T08:58:00.7869116Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-09-07T08:58:00.7870038Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-09-07T08:58:00.7871464Z * [new tag] v1.8.0 -> v1.8.0 2025-09-07T08:58:00.7872427Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-09-07T08:58:00.7873614Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-09-07T08:58:00.7874788Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-09-07T08:58:00.7876092Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-09-07T08:58:00.7876980Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-09-07T08:58:00.7877909Z * [new tag] v1.8.1 -> v1.8.1 2025-09-07T08:58:00.7879095Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-09-07T08:58:00.7880043Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-09-07T08:58:00.7881688Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-09-07T08:58:00.7883302Z * [new tag] v1.8.2 -> v1.8.2 2025-09-07T08:58:00.7884278Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-09-07T08:58:00.7885483Z * [new tag] v1.9.0 -> v1.9.0 2025-09-07T08:58:00.7886698Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-09-07T08:58:00.7887954Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-09-07T08:58:00.7889169Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-09-07T08:58:00.7890184Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-09-07T08:58:00.7891642Z * [new tag] v1.9.1 -> v1.9.1 2025-09-07T08:58:00.7893014Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-09-07T08:58:00.7893988Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-09-07T08:58:00.7895232Z * [new tag] v2.0.0 -> v2.0.0 2025-09-07T08:58:00.7896343Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-09-07T08:58:00.7897641Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-09-07T08:58:00.7898846Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-09-07T08:58:00.7900023Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-09-07T08:58:00.7901546Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-09-07T08:58:00.7902491Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-09-07T08:58:00.7904020Z * [new tag] v2.0.1 -> v2.0.1 2025-09-07T08:58:00.7905262Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-09-07T08:58:00.7906254Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-09-07T08:58:00.7907414Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-09-07T08:58:00.7908391Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-09-07T08:58:00.7910005Z * [new tag] v2.1.0 -> v2.1.0 2025-09-07T08:58:00.7911496Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-09-07T08:58:00.7912674Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-09-07T08:58:00.7913943Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-09-07T08:58:00.7915168Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-09-07T08:58:00.7916383Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-09-07T08:58:00.7917405Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-09-07T08:58:00.7918639Z * [new tag] v2.1.1 -> v2.1.1 2025-09-07T08:58:00.7919922Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-09-07T08:58:00.7921292Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-09-07T08:58:00.7922722Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-09-07T08:58:00.7923995Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-09-07T08:58:00.7925147Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-09-07T08:58:00.7926338Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-09-07T08:58:00.7927394Z * [new tag] v2.1.2 -> v2.1.2 2025-09-07T08:58:00.7928684Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-09-07T08:58:00.7930006Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-09-07T08:58:00.7931214Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-09-07T08:58:00.7932485Z * [new tag] v2.2.0 -> v2.2.0 2025-09-07T08:58:00.7933705Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-09-07T08:58:00.7934912Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-09-07T08:58:00.7936111Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-09-07T08:58:00.7937278Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-09-07T08:58:00.7938425Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-09-07T08:58:00.7939584Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-09-07T08:58:00.7940801Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-09-07T08:58:00.7941925Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-09-07T08:58:00.7943405Z * [new tag] v2.2.1 -> v2.2.1 2025-09-07T08:58:00.7944626Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-09-07T08:58:00.7945684Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-09-07T08:58:00.7946727Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-09-07T08:58:00.7947758Z * [new tag] v2.2.2 -> v2.2.2 2025-09-07T08:58:00.7949087Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-09-07T08:58:00.7950082Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-09-07T08:58:00.7951332Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-09-07T08:58:00.7952531Z * [new tag] v2.3.0 -> v2.3.0 2025-09-07T08:58:00.7953709Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-09-07T08:58:00.7954921Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-09-07T08:58:00.7956194Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-09-07T08:58:00.7957203Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-09-07T08:58:00.7958464Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-09-07T08:58:00.7959775Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-09-07T08:58:00.7961227Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-09-07T08:58:00.7962496Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-09-07T08:58:00.7963576Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-09-07T08:58:00.7964859Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-09-07T08:58:00.7966128Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-09-07T08:58:00.7967164Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-09-07T08:58:00.7968181Z * [new tag] v2.3.1 -> v2.3.1 2025-09-07T08:58:00.7969453Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-09-07T08:58:00.7970915Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-09-07T08:58:00.7972926Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-09-07T08:58:00.7974116Z * [new tag] v2.4.0 -> v2.4.0 2025-09-07T08:58:00.7975263Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-09-07T08:58:00.7976707Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-09-07T08:58:00.7977727Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-09-07T08:58:00.7978876Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-09-07T08:58:00.7980190Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-09-07T08:58:00.7981754Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-09-07T08:58:00.7983093Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-09-07T08:58:00.7984293Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-09-07T08:58:00.7985507Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-09-07T08:58:00.7986539Z * [new tag] v2.4.1 -> v2.4.1 2025-09-07T08:58:00.7987809Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-09-07T08:58:00.7989079Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-09-07T08:58:00.7990480Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-09-07T08:58:00.7991742Z * [new tag] v2.5.0 -> v2.5.0 2025-09-07T08:58:00.7992994Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-09-07T08:58:00.7993973Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-09-07T08:58:00.7995187Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-09-07T08:58:00.7996333Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-09-07T08:58:00.7997604Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-09-07T08:58:00.7998824Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-09-07T08:58:00.8000055Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-09-07T08:58:00.8001596Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-09-07T08:58:00.8002802Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-09-07T08:58:00.8004047Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-09-07T08:58:00.8005044Z * [new tag] v2.5.1 -> v2.5.1 2025-09-07T08:58:00.8006077Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-09-07T08:58:00.8007104Z * [new tag] v2.6.0 -> v2.6.0 2025-09-07T08:58:00.8008364Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-09-07T08:58:00.8009665Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-09-07T08:58:00.8011148Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-09-07T08:58:00.8012345Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-09-07T08:58:00.8013742Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-09-07T08:58:00.8015102Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-09-07T08:58:00.8016401Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-09-07T08:58:00.8017731Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-09-07T08:58:00.8018999Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-09-07T08:58:00.8020523Z * [new tag] v2.7.0 -> v2.7.0 2025-09-07T08:58:00.8021940Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-09-07T08:58:00.8023036Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-09-07T08:58:00.8024374Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-09-07T08:58:00.8026704Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-09-07T08:58:00.8028040Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-09-07T08:58:00.8029477Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-09-07T08:58:00.8030610Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-09-07T08:58:00.8032036Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-09-07T08:58:00.8033336Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-09-07T08:58:00.8034583Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-09-07T08:58:00.8035608Z * [new tag] v2.7.1 -> v2.7.1 2025-09-07T08:58:00.8036912Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-09-07T08:58:00.8038162Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-09-07T08:58:00.8039480Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-09-07T08:58:00.8040950Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-09-07T08:58:00.8042125Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-09-07T08:58:00.8043234Z * [new tag] v2.8.0 -> v2.8.0 2025-09-07T08:58:00.8044493Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-09-07T08:58:00.8045672Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-09-07T08:58:00.8046922Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-09-07T08:58:00.8048259Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-09-07T08:58:00.8049520Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-09-07T08:58:00.8051141Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-09-07T08:58:00.8052335Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-09-07T08:58:00.8053558Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-09-07T08:58:00.8054854Z * [new tag] whc_flight_1 -> whc_flight_1 2025-09-07T08:58:00.8056115Z * [new tag] whc_flight_2 -> whc_flight_2 2025-09-07T08:58:00.8057242Z * [new tag] whc_flight_4 -> whc_flight_4 2025-09-07T08:58:00.8919418Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T08:58:00.8953536Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:58:00.8957543Z ##[endgroup] 2025-09-07T08:58:00.8957809Z ##[group]Determining the checkout info 2025-09-07T08:58:00.8958554Z ##[endgroup] 2025-09-07T08:58:00.8962499Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T08:58:00.9262008Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T08:58:00.9300084Z ##[group]Checking out the ref 2025-09-07T08:58:00.9303738Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:58:01.9715808Z Updating files: 80% (15567/19405) 2025-09-07T08:58:01.9943837Z Updating files: 81% (15719/19405) 2025-09-07T08:58:02.0154305Z Updating files: 82% (15913/19405) 2025-09-07T08:58:02.0265177Z Updating files: 83% (16107/19405) 2025-09-07T08:58:02.0391213Z Updating files: 84% (16301/19405) 2025-09-07T08:58:02.0538974Z Updating files: 85% (16495/19405) 2025-09-07T08:58:02.0667053Z Updating files: 86% (16689/19405) 2025-09-07T08:58:02.0795389Z Updating files: 87% (16883/19405) 2025-09-07T08:58:02.0892597Z 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2025-09-07T08:58:02.4499495Z You are in 'detached HEAD' state. You can look around, make experimental 2025-09-07T08:58:02.4500004Z changes and commit them, and you can discard any commits you make in this 2025-09-07T08:58:02.4500938Z state without impacting any branches by switching back to a branch. 2025-09-07T08:58:02.4501228Z 2025-09-07T08:58:02.4501424Z If you want to create a new branch to retain commits you create, you may 2025-09-07T08:58:02.4501892Z do so (now or later) by using -c with the switch command. Example: 2025-09-07T08:58:02.4502152Z 2025-09-07T08:58:02.4502302Z git switch -c 2025-09-07T08:58:02.4502508Z 2025-09-07T08:58:02.4502712Z Or undo this operation with: 2025-09-07T08:58:02.4502907Z 2025-09-07T08:58:02.4503006Z git switch - 2025-09-07T08:58:02.4503151Z 2025-09-07T08:58:02.4503364Z Turn off this advice by setting config variable advice.detachedHead to false 2025-09-07T08:58:02.4503648Z 2025-09-07T08:58:02.4503799Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T08:58:02.4641919Z ##[endgroup] 2025-09-07T08:58:02.4642329Z ##[group]Setting up auth for fetching submodules 2025-09-07T08:58:02.4647913Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T08:58:02.9339289Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T08:58:02.9375497Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T08:58:03.2412652Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T08:58:03.3234259Z ##[endgroup] 2025-09-07T08:58:03.3234687Z ##[group]Fetching submodules 2025-09-07T08:58:03.3237542Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T08:58:03.3507590Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T08:58:03.4013017Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-09-07T08:58:03.4333754Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-09-07T08:58:03.4625036Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-09-07T08:58:03.4908749Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-09-07T08:58:03.5331453Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-09-07T08:58:03.5645584Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-09-07T08:58:03.5981485Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-09-07T08:58:03.6235416Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-09-07T08:58:03.6635810Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-09-07T08:58:03.6919113Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-09-07T08:58:03.7253691Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-09-07T08:58:03.7547310Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-09-07T08:58:03.7880756Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-09-07T08:58:03.8063918Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-09-07T08:58:03.8218486Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-09-07T08:58:03.8441741Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-09-07T08:58:03.8565952Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-09-07T08:58:03.8695097Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-09-07T08:58:03.8783837Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-09-07T08:58:03.8841248Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-09-07T08:58:03.8909403Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-09-07T08:58:03.9022436Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-09-07T08:58:03.9137074Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-09-07T08:58:03.9368450Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-09-07T08:58:03.9455513Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-09-07T08:58:03.9553867Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-09-07T08:58:03.9631299Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-09-07T08:58:03.9933060Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-09-07T08:58:04.1215969Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-09-07T08:58:04.3736770Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-09-07T08:58:04.6303103Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-09-07T08:58:04.8856304Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-09-07T08:58:05.1361464Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-09-07T08:58:05.2590977Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-09-07T08:58:05.5141904Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-09-07T08:58:05.7693055Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-09-07T08:58:06.0229977Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-09-07T08:58:06.0270349Z Cloning into '/home/henry/_work/pytorch/pytorch/android/libs/fbjni'... 2025-09-07T08:58:08.7362478Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/FP16'... 2025-09-07T08:58:10.0950069Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/FXdiv'... 2025-09-07T08:58:12.2043957Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/NNPACK'... 2025-09-07T08:58:12.8562023Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/NVTX'... 2025-09-07T08:58:14.9482292Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-09-07T08:58:16.6848288Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-09-07T08:58:26.3217091Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/aiter'... 2025-09-07T08:58:29.4837701Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/benchmark'... 2025-09-07T08:58:30.0064033Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-09-07T08:58:32.9792762Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-09-07T08:58:33.6013202Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-09-07T08:58:34.3020875Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-09-07T08:58:35.4104388Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/cutlass'... 2025-09-07T08:58:38.4965648Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm'... 2025-09-07T08:58:41.6068251Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/flash-attention'... 2025-09-07T08:58:42.6219266Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-09-07T08:58:43.9073497Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fmt'... 2025-09-07T08:58:44.8790976Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-09-07T08:58:45.3575481Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/gloo'... 2025-09-07T08:58:45.8487864Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/googletest'... 2025-09-07T08:58:46.7190869Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/ideep'... 2025-09-07T08:58:47.1762141Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/ittapi'... 2025-09-07T08:58:47.7438404Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto'... 2025-09-07T08:58:48.9572756Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kleidiai'... 2025-09-07T08:58:49.5286717Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/mimalloc'... 2025-09-07T08:58:50.4523077Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/nlohmann'... 2025-09-07T08:58:55.8986538Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/onnx'... 2025-09-07T08:58:58.4261412Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-09-07T08:59:03.3286782Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/pocketfft'... 2025-09-07T08:59:03.6769319Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/protobuf'... 2025-09-07T08:59:10.8334171Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/psimd'... 2025-09-07T08:59:11.1090594Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-09-07T08:59:11.4691026Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/pybind11'... 2025-09-07T08:59:12.3891319Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-09-07T08:59:12.8120936Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/sleef'... 2025-09-07T08:59:13.6978952Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-09-07T08:59:14.2535237Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T08:59:14.2673107Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T08:59:14.2780003Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T08:59:14.3051661Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T08:59:14.3827027Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T08:59:14.4374590Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T08:59:15.1932840Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T08:59:15.3506416Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T08:59:15.3543512Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T08:59:15.3577709Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-09-07T08:59:21.2256783Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T08:59:21.3488138Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T08:59:21.7215003Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T08:59:21.8435944Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T08:59:22.0562592Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T08:59:22.1681891Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T08:59:22.9569298Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T08:59:23.2144525Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T08:59:23.3808851Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-09-07T08:59:23.5091207Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-09-07T08:59:23.6382039Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-09-07T08:59:23.7647434Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-09-07T08:59:23.8897695Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-09-07T08:59:24.0091292Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-09-07T08:59:24.1349413Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-09-07T08:59:24.1384897Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-09-07T08:59:26.0282822Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-09-07T08:59:27.0419955Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-09-07T08:59:27.7379177Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-09-07T08:59:29.4165254Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-09-07T08:59:30.2816923Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-09-07T08:59:30.7471005Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-09-07T08:59:36.3474495Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T08:59:36.6181829Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T08:59:36.7193943Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T08:59:37.3551634Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T08:59:37.4007312Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T08:59:37.4139398Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T08:59:37.5196104Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T08:59:37.5941250Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T08:59:37.5972505Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T08:59:37.5982842Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-09-07T08:59:37.6013979Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-09-07T08:59:40.5663736Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-09-07T08:59:42.7396484Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T08:59:43.3153818Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T08:59:43.4591192Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T08:59:43.4917742Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T08:59:43.5324420Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T08:59:43.5580762Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T08:59:43.6020008Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T08:59:43.6166221Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T08:59:43.6194048Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-09-07T08:59:43.6222798Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-09-07T08:59:54.5341639Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T08:59:54.5571896Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T08:59:54.6460435Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T08:59:54.6521190Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T08:59:54.6664283Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T08:59:54.6754692Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T08:59:54.6786844Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-09-07T08:59:55.5461380Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-09-07T08:59:57.0002807Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-09-07T08:59:58.0191878Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T08:59:58.0225597Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T08:59:58.0240952Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T08:59:58.0256852Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T08:59:58.0271536Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T08:59:58.0286234Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T08:59:58.0300028Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T08:59:58.0314112Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T08:59:58.0327647Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T08:59:58.0364560Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-09-07T08:59:59.3266611Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-09-07T08:59:59.7731853Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-09-07T09:00:00.7222777Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-09-07T09:00:01.1162181Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-09-07T09:00:01.6439884Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-09-07T09:00:02.6213816Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-09-07T09:00:08.6822506Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-09-07T09:00:09.5436331Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T09:00:09.5899137Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T09:00:09.6550542Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T09:00:09.6831280Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T09:00:09.7166727Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T09:00:09.7194183Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-09-07T09:00:10.5601796Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T09:00:10.5829532Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T09:00:10.6246524Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T09:00:10.7265315Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T09:00:10.7613084Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T09:00:10.7954629Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T09:00:10.8534296Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T09:00:10.9222804Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T09:00:10.9824917Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T09:00:11.1090569Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T09:00:11.7699242Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T09:00:11.8072215Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:11.8109261Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'... 2025-09-07T09:00:12.8977815Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T09:00:12.9724378Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T09:00:12.9760755Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:12.9775799Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:12.9790370Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:12.9804163Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:12.9817919Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:12.9831897Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:12.9844991Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:12.9858274Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:12.9889160Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-09-07T09:00:13.4923493Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-09-07T09:00:14.4172978Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-09-07T09:00:14.8480790Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-09-07T09:00:22.0026592Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-09-07T09:00:22.5249151Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-09-07T09:00:22.8960146Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-09-07T09:00:23.3104478Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-09-07T09:00:29.1085444Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T09:00:29.1489822Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T09:00:29.1666434Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T09:00:29.2737874Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T09:00:29.2894904Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T09:00:29.3053962Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T09:00:29.3223724Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T09:00:29.3254414Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:29.3267210Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:29.3298936Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'... 2025-09-07T09:00:31.1099691Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'... 2025-09-07T09:00:32.2681392Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T09:00:32.3143383Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T09:00:32.8611558Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T09:00:32.8754021Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T09:00:33.1489977Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T09:00:33.1529932Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:33.1543327Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:33.1576484Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/protobuf/third_party/benchmark'... 2025-09-07T09:00:33.6910693Z Cloning into '/home/henry/_work/pytorch/pytorch/third_party/protobuf/third_party/googletest'... 2025-09-07T09:00:34.5972065Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T09:00:34.6664424Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T09:00:34.6803492Z Submodule 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2025-09-07T09:00:42.4594123Z 7e1e1fe3858c63c251c637ae41a20de425dde96f android/libs/fbjni (v0.1.0-12-g7e1e1fe) 2025-09-07T09:00:42.4680728Z 4dfe081cf6bcd15db339cf2680b9281b8451eeb3 third_party/FP16 (4dfe081) 2025-09-07T09:00:42.4766803Z b408327ac2a15ec3e43352421954f5b1967701d1 third_party/FXdiv (b408327) 2025-09-07T09:00:42.4864903Z c07e3a0400713d546e0dea2d5466dd22ea389c73 third_party/NNPACK (c07e3a0) 2025-09-07T09:00:42.4919226Z 2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07 third_party/NVTX (v3.1.0-263-g2942f16) 2025-09-07T09:00:42.5002402Z 1d8f600fd424278486eade7ed3e877c99f0846b1 third_party/VulkanMemoryAllocator (v2.1.0-982-g1d8f600) 2025-09-07T09:00:42.5468933Z 51a0103656eff6fc9bfd39a4597923c4b542c883 third_party/XNNPACK (remotes/origin/ds/ndk-1243-g51a0103656) 2025-09-07T09:00:42.5509201Z 01aae101b9e5e94d6c16a9514c9fb8df99c93150 third_party/aiter (v0.1.1-92-g01aae101) 2025-09-07T09:00:42.5537747Z 299e5928955cc62af9968370293b916f5130916f third_party/benchmark (v1.9.3) 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'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T09:00:43.9456643Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9491608Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T09:00:43.9517861Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9551347Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T09:00:43.9577121Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9615904Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T09:00:43.9642407Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9677131Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T09:00:43.9703682Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9738303Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T09:00:43.9765155Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9800157Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T09:00:43.9826385Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9863787Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T09:00:43.9890551Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9925922Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T09:00:43.9953245Z http.https://github.com/.extraheader 2025-09-07T09:00:43.9991827Z Entering 'third_party/kleidiai' 2025-09-07T09:00:44.0019064Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0054502Z Entering 'third_party/mimalloc' 2025-09-07T09:00:44.0082178Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0117172Z Entering 'third_party/nlohmann' 2025-09-07T09:00:44.0144775Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0180882Z Entering 'third_party/onnx' 2025-09-07T09:00:44.0208459Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0257677Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:44.0285856Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0325937Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T09:00:44.0361713Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0404983Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:44.0433274Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0467863Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:44.0494013Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0528078Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:44.0554049Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0588315Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:44.0614297Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0649579Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:44.0675552Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0709515Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:44.0735319Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0771141Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:44.0798405Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0831683Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:44.0858467Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0896748Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:44.0925753Z http.https://github.com/.extraheader 2025-09-07T09:00:44.0964059Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:44.0990502Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1044404Z Entering 'third_party/pocketfft' 2025-09-07T09:00:44.1072236Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1107348Z Entering 'third_party/protobuf' 2025-09-07T09:00:44.1134682Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1171519Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:44.1199344Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1234666Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:44.1262648Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1300817Z Entering 'third_party/psimd' 2025-09-07T09:00:44.1328442Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1363727Z Entering 'third_party/pthreadpool' 2025-09-07T09:00:44.1391446Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1426440Z Entering 'third_party/pybind11' 2025-09-07T09:00:44.1454119Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1489776Z Entering 'third_party/python-peachpy' 2025-09-07T09:00:44.1517356Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1552651Z Entering 'third_party/sleef' 2025-09-07T09:00:44.1580468Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1615692Z Entering 'third_party/tensorpipe' 2025-09-07T09:00:44.1643587Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1679640Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:44.1705373Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1741178Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:44.1767414Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1802349Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:44.1829369Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1864485Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:44.1891964Z http.https://github.com/.extraheader 2025-09-07T09:00:44.1926147Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:44.1954084Z http.https://github.com/.extraheader 2025-09-07T09:00:44.2017296Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T09:00:44.2056787Z ##[endgroup] 2025-09-07T09:00:44.2057150Z ##[group]Fetching the repository 2025-09-07T09:00:44.2064168Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T09:00:44.8059295Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T09:00:44.8088026Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:00:44.8093485Z ##[endgroup] 2025-09-07T09:00:44.8093895Z ##[group]Determining the checkout info 2025-09-07T09:00:44.8094665Z ##[endgroup] 2025-09-07T09:00:44.8098235Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T09:00:44.8290743Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T09:00:44.8319489Z ##[group]Checking out the ref 2025-09-07T09:00:44.8323827Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:00:44.8657831Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T09:00:44.8668567Z ##[endgroup] 2025-09-07T09:00:44.8668922Z ##[group]Setting up auth for fetching submodules 2025-09-07T09:00:44.8672841Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T09:00:44.8710548Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T09:00:44.8739704Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T09:00:44.8769814Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T09:00:44.8797083Z ##[endgroup] 2025-09-07T09:00:44.8797501Z ##[group]Fetching submodules 2025-09-07T09:00:44.8800546Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T09:00:44.9080657Z Synchronizing submodule url for 'android/libs/fbjni' 2025-09-07T09:00:44.9106790Z Synchronizing submodule url for 'third_party/FP16' 2025-09-07T09:00:44.9131585Z Synchronizing submodule url for 'third_party/FXdiv' 2025-09-07T09:00:44.9155675Z Synchronizing submodule url for 'third_party/NNPACK' 2025-09-07T09:00:44.9180527Z Synchronizing submodule url for 'third_party/NVTX' 2025-09-07T09:00:44.9205612Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator' 2025-09-07T09:00:44.9229624Z Synchronizing submodule url for 'third_party/XNNPACK' 2025-09-07T09:00:44.9268059Z Synchronizing submodule url for 'third_party/aiter' 2025-09-07T09:00:44.9292304Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T09:00:44.9326644Z Synchronizing submodule url for 'third_party/benchmark' 2025-09-07T09:00:44.9351330Z Synchronizing submodule url for 'third_party/composable_kernel' 2025-09-07T09:00:44.9383047Z Synchronizing submodule url for 'third_party/cpp-httplib' 2025-09-07T09:00:44.9407354Z Synchronizing submodule url for 'third_party/cpuinfo' 2025-09-07T09:00:44.9433254Z Synchronizing submodule url for 'third_party/cudnn_frontend' 2025-09-07T09:00:44.9458502Z Synchronizing submodule url for 'third_party/cutlass' 2025-09-07T09:00:44.9493196Z Synchronizing submodule url for 'third_party/fbgemm' 2025-09-07T09:00:44.9518553Z Synchronizing submodule url for 'third_party/fbgemm/external/asmjit' 2025-09-07T09:00:44.9543846Z Synchronizing submodule url for 'third_party/fbgemm/external/composable_kernel' 2025-09-07T09:00:44.9573864Z Synchronizing submodule url for 'third_party/fbgemm/external/cpuinfo' 2025-09-07T09:00:44.9597106Z Synchronizing submodule url for 'third_party/fbgemm/external/cutlass' 2025-09-07T09:00:44.9628296Z Synchronizing submodule url for 'third_party/fbgemm/external/googletest' 2025-09-07T09:00:44.9651143Z Synchronizing submodule url for 'third_party/fbgemm/external/hipify_torch' 2025-09-07T09:00:44.9673360Z Synchronizing submodule url for 'third_party/fbgemm/external/json' 2025-09-07T09:00:44.9702011Z Synchronizing submodule url for 'third_party/flash-attention' 2025-09-07T09:00:44.9725739Z Synchronizing submodule url for 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T09:00:44.9755597Z Synchronizing submodule url for 'third_party/flash-attention/csrc/cutlass' 2025-09-07T09:00:44.9789117Z Synchronizing submodule url for 'third_party/flatbuffers' 2025-09-07T09:00:44.9821289Z Synchronizing submodule url for 'third_party/fmt' 2025-09-07T09:00:44.9846502Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp' 2025-09-07T09:00:44.9870916Z Synchronizing submodule url for 'third_party/gloo' 2025-09-07T09:00:44.9895404Z Synchronizing submodule url for 'third_party/googletest' 2025-09-07T09:00:44.9919603Z Synchronizing submodule url for 'third_party/ideep' 2025-09-07T09:00:44.9942160Z Synchronizing submodule url for 'third_party/ideep/mkl-dnn' 2025-09-07T09:00:44.9975098Z Synchronizing submodule url for 'third_party/ittapi' 2025-09-07T09:00:45.0001083Z Synchronizing submodule url for 'third_party/kineto' 2025-09-07T09:00:45.0025192Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T09:00:45.0048588Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T09:00:45.0074781Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T09:00:45.0098095Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T09:00:45.0123385Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T09:00:45.0146038Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T09:00:45.0171856Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T09:00:45.0194591Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T09:00:45.0218098Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T09:00:45.0241983Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T09:00:45.0268007Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T09:00:45.0293039Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T09:00:45.0320155Z Synchronizing submodule url for 'third_party/kleidiai' 2025-09-07T09:00:45.0345918Z Synchronizing submodule url for 'third_party/mimalloc' 2025-09-07T09:00:45.0370469Z Synchronizing submodule url for 'third_party/nlohmann' 2025-09-07T09:00:45.0396316Z Synchronizing submodule url for 'third_party/onnx' 2025-09-07T09:00:45.0434610Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:45.0462206Z Synchronizing submodule url for 'third_party/opentelemetry-cpp' 2025-09-07T09:00:45.0487367Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:45.0511232Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:45.0534255Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:45.0557175Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:45.0581247Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:45.0603768Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:45.0626467Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:45.0648020Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:45.0674614Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:45.0702671Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:45.0746888Z Synchronizing submodule url for 'third_party/pocketfft' 2025-09-07T09:00:45.0772583Z Synchronizing submodule url for 'third_party/protobuf' 2025-09-07T09:00:45.0798568Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:45.0822527Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:45.0849476Z Synchronizing submodule url for 'third_party/psimd' 2025-09-07T09:00:45.0874307Z Synchronizing submodule url for 'third_party/pthreadpool' 2025-09-07T09:00:45.0898175Z Synchronizing submodule url for 'third_party/pybind11' 2025-09-07T09:00:45.0923062Z Synchronizing submodule url for 'third_party/python-peachpy' 2025-09-07T09:00:45.0949412Z Synchronizing submodule url for 'third_party/sleef' 2025-09-07T09:00:45.0974355Z Synchronizing submodule url for 'third_party/tensorpipe' 2025-09-07T09:00:45.0997237Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:45.1021070Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:45.1043478Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:45.1066232Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:45.1087407Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:45.1131550Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T09:00:45.1533457Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T09:00:45.1663114Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T09:00:45.1764505Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T09:00:45.1994653Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T09:00:45.2818719Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T09:00:45.3169509Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T09:00:45.5776355Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T09:00:45.7801749Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T09:00:46.0312380Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T09:00:46.0520404Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T09:00:46.3725158Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T09:00:46.4285303Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T09:00:46.4717178Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T09:00:46.5169462Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T09:00:47.3273191Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T09:00:47.4691089Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T09:00:47.5271540Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T09:00:47.7971567Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T09:00:47.9165944Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T09:00:48.3651796Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T09:00:48.4019309Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T09:00:48.4153742Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T09:00:48.5150540Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T09:00:48.5890598Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T09:00:48.8309625Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T09:00:49.2213142Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T09:00:49.4359242Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T09:00:49.4651909Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T09:00:49.5031840Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T09:00:49.5245582Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T09:00:49.5589728Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T09:00:49.5728603Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T09:00:50.2974779Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T09:00:50.3195785Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T09:00:50.4052530Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T09:00:50.4935862Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T09:00:50.6689227Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T09:00:50.6853487Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T09:00:50.7157906Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T09:00:50.7301060Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T09:00:50.7407705Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T09:00:50.7569757Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T09:00:50.7912291Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T09:00:50.8757655Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T09:00:50.8918250Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T09:00:50.9206434Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T09:00:50.9560610Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T09:00:50.9998396Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T09:00:51.0504460Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T09:00:51.1595229Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T09:00:51.4887438Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T09:00:51.5210914Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T09:00:51.6176285Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T09:00:51.6352748Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T09:00:51.6690135Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T09:00:51.6820666Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T09:00:51.7820985Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T09:00:51.7971441Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T09:00:51.8114821Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T09:00:51.8262780Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T09:00:52.0957354Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T09:00:52.1312516Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T09:00:52.4653054Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T09:00:52.8738577Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T09:00:53.2011478Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T09:00:53.2154160Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T09:00:53.2545560Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T09:00:53.2657752Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900' 2025-09-07T09:00:53.2811013Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8' 2025-09-07T09:00:53.3163200Z Submodule path 'third_party/pybind11': checked out 'f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8' 2025-09-07T09:00:53.3593697Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67' 2025-09-07T09:00:53.4069134Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68' 2025-09-07T09:00:53.4295783Z Submodule path 'third_party/tensorpipe': checked out 'af0118d13e52f5a08841464a768e01a0bf3e3075' 2025-09-07T09:00:53.4638991Z Submodule path 'third_party/tensorpipe/third_party/googletest': checked out 'aee0f9d9b5b87796ee8a0ab26b7587ec30e8858e' 2025-09-07T09:00:53.4794867Z Submodule path 'third_party/tensorpipe/third_party/libnop': checked out '910b55815be16109f04f4180e9adee14fb4ce281' 2025-09-07T09:00:53.5310462Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '5152db2cbfeb5582e9c27c5ea1dba2cd9e10759b' 2025-09-07T09:00:53.5553514Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef' 2025-09-07T09:00:53.5653901Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5' 2025-09-07T09:00:53.5702519Z [command]/usr/bin/git submodule foreach --recursive git config --local gc.auto 0 2025-09-07T09:00:53.5976303Z Entering 'android/libs/fbjni' 2025-09-07T09:00:53.6020944Z Entering 'third_party/FP16' 2025-09-07T09:00:53.6064559Z Entering 'third_party/FXdiv' 2025-09-07T09:00:53.6107747Z Entering 'third_party/NNPACK' 2025-09-07T09:00:53.6152313Z Entering 'third_party/NVTX' 2025-09-07T09:00:53.6196407Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T09:00:53.6241512Z Entering 'third_party/XNNPACK' 2025-09-07T09:00:53.6299984Z Entering 'third_party/aiter' 2025-09-07T09:00:53.6345607Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T09:00:53.6398229Z Entering 'third_party/benchmark' 2025-09-07T09:00:53.6443586Z Entering 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2025-09-07T09:00:53.8145304Z Entering 'third_party/mimalloc' 2025-09-07T09:00:53.8190153Z Entering 'third_party/nlohmann' 2025-09-07T09:00:53.8234641Z Entering 'third_party/onnx' 2025-09-07T09:00:53.8292612Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:53.8340612Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T09:00:53.8385939Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:53.8426855Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:53.8467577Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:53.8508537Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:53.8549846Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:53.8591201Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:53.8632558Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:53.8672317Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:53.8716580Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:53.8761203Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:53.8821719Z Entering 'third_party/pocketfft' 2025-09-07T09:00:53.8866515Z Entering 'third_party/protobuf' 2025-09-07T09:00:53.8913892Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:53.8956796Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:53.9001481Z Entering 'third_party/psimd' 2025-09-07T09:00:53.9045409Z Entering 'third_party/pthreadpool' 2025-09-07T09:00:53.9089113Z Entering 'third_party/pybind11' 2025-09-07T09:00:53.9134921Z Entering 'third_party/python-peachpy' 2025-09-07T09:00:53.9180382Z Entering 'third_party/sleef' 2025-09-07T09:00:53.9225057Z Entering 'third_party/tensorpipe' 2025-09-07T09:00:53.9271076Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:53.9312346Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:53.9353467Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:53.9393900Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:53.9434115Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:53.9494694Z ##[endgroup] 2025-09-07T09:00:53.9495044Z ##[group]Persisting credentials for submodules 2025-09-07T09:00:53.9502089Z [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' || :" 2025-09-07T09:00:53.9769932Z Entering 'android/libs/fbjni' 2025-09-07T09:00:53.9798714Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9799038Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9835134Z Entering 'third_party/FP16' 2025-09-07T09:00:53.9863957Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9864264Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9900145Z Entering 'third_party/FXdiv' 2025-09-07T09:00:53.9928104Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9928389Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9963834Z Entering 'third_party/NNPACK' 2025-09-07T09:00:53.9991751Z url.https://github.com/.insteadof 2025-09-07T09:00:53.9992050Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0028842Z Entering 'third_party/NVTX' 2025-09-07T09:00:54.0056686Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0056995Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0094948Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T09:00:54.0123294Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0123558Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0159583Z Entering 'third_party/XNNPACK' 2025-09-07T09:00:54.0187117Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0187413Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0239258Z Entering 'third_party/aiter' 2025-09-07T09:00:54.0266781Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0267083Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0303648Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T09:00:54.0331280Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0331590Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0377553Z Entering 'third_party/benchmark' 2025-09-07T09:00:54.0405459Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0405736Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0442310Z Entering 'third_party/composable_kernel' 2025-09-07T09:00:54.0469990Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0470424Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0514606Z Entering 'third_party/cpp-httplib' 2025-09-07T09:00:54.0543088Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0543371Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0578445Z Entering 'third_party/cpuinfo' 2025-09-07T09:00:54.0606610Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0606901Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0643234Z Entering 'third_party/cudnn_frontend' 2025-09-07T09:00:54.0671870Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0672180Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0708117Z Entering 'third_party/cutlass' 2025-09-07T09:00:54.0735623Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0735904Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0779467Z Entering 'third_party/fbgemm' 2025-09-07T09:00:54.0807757Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0808045Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0844662Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T09:00:54.0871985Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0872308Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0907567Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T09:00:54.0934259Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0934549Z url.https://github.com/.insteadof 2025-09-07T09:00:54.0976255Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T09:00:54.1010682Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1010992Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1040312Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T09:00:54.1068092Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1068386Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1111971Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T09:00:54.1138904Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1139214Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1173750Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T09:00:54.1202086Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1202408Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1236356Z Entering 'third_party/fbgemm/external/json' 2025-09-07T09:00:54.1262969Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1263259Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1301635Z Entering 'third_party/flash-attention' 2025-09-07T09:00:54.1330170Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1330748Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1366107Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T09:00:54.1393499Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1393791Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1433580Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T09:00:54.1459331Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1459610Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1503823Z Entering 'third_party/flatbuffers' 2025-09-07T09:00:54.1532824Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1533127Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1571382Z Entering 'third_party/fmt' 2025-09-07T09:00:54.1598102Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1598393Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1633473Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T09:00:54.1661315Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1661611Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1697386Z Entering 'third_party/gloo' 2025-09-07T09:00:54.1725122Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1725432Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1760863Z Entering 'third_party/googletest' 2025-09-07T09:00:54.1788935Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1789241Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1825076Z Entering 'third_party/ideep' 2025-09-07T09:00:54.1852853Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1853162Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1886887Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T09:00:54.1914112Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1914407Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1956961Z Entering 'third_party/ittapi' 2025-09-07T09:00:54.1985003Z url.https://github.com/.insteadof 2025-09-07T09:00:54.1985330Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2022495Z Entering 'third_party/kineto' 2025-09-07T09:00:54.2050145Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2050527Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2085476Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T09:00:54.2113107Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2113413Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2146857Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T09:00:54.2172607Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2172901Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2209529Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T09:00:54.2236703Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2237019Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2272755Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T09:00:54.2300045Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2300472Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2336476Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T09:00:54.2363670Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2363969Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2398506Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T09:00:54.2426086Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2426360Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2464121Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T09:00:54.2491160Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2491449Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2527694Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T09:00:54.2554698Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2555244Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2591138Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T09:00:54.2618017Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2618322Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2655362Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T09:00:54.2682299Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2682620Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2720849Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T09:00:54.2747733Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2747984Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2781425Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T09:00:54.2807994Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2808264Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2845213Z Entering 'third_party/kleidiai' 2025-09-07T09:00:54.2875375Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2875688Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2912425Z Entering 'third_party/mimalloc' 2025-09-07T09:00:54.2939516Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2939831Z url.https://github.com/.insteadof 2025-09-07T09:00:54.2975415Z Entering 'third_party/nlohmann' 2025-09-07T09:00:54.3003310Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3003900Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3040753Z Entering 'third_party/onnx' 2025-09-07T09:00:54.3068656Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3068944Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3118303Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:54.3145819Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3146079Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3186054Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T09:00:54.3214028Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3214322Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3249845Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:54.3276922Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3277218Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3311212Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:54.3336794Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3337091Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3370925Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:54.3396826Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3397114Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3431224Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:54.3459462Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3459769Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3495930Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:54.3522264Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3522551Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3556706Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:54.3583027Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3583313Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3617070Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:54.3644090Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3644352Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3677389Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:54.3705570Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3705869Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3743526Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:54.3774094Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3774401Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3828910Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:54.3854812Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3855098Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3911107Z Entering 'third_party/pocketfft' 2025-09-07T09:00:54.3938861Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3939165Z url.https://github.com/.insteadof 2025-09-07T09:00:54.3977115Z Entering 'third_party/protobuf' 2025-09-07T09:00:54.4005251Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4005590Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4044465Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:54.4071726Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4072010Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4106575Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:54.4132742Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4133006Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4170515Z Entering 'third_party/psimd' 2025-09-07T09:00:54.4198471Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4198807Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4234178Z Entering 'third_party/pthreadpool' 2025-09-07T09:00:54.4261831Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4262116Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4297752Z Entering 'third_party/pybind11' 2025-09-07T09:00:54.4325347Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4325655Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4363659Z Entering 'third_party/python-peachpy' 2025-09-07T09:00:54.4391805Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4392129Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4428107Z Entering 'third_party/sleef' 2025-09-07T09:00:54.4455625Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4455923Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4491667Z Entering 'third_party/tensorpipe' 2025-09-07T09:00:54.4519537Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4519831Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4554904Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:54.4582035Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4582321Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4616660Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:54.4642584Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4642886Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4676472Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:54.4702277Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4702545Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4736642Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:54.4762739Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4763024Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4795846Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:54.4821646Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4821954Z url.https://github.com/.insteadof 2025-09-07T09:00:54.4882037Z [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" 2025-09-07T09:00:54.5141764Z Entering 'android/libs/fbjni' 2025-09-07T09:00:54.5182431Z file:/home/henry/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T09:00:54.5205206Z Entering 'third_party/FP16' 2025-09-07T09:00:54.5247567Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T09:00:54.5269248Z Entering 'third_party/FXdiv' 2025-09-07T09:00:54.5310158Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T09:00:54.5331375Z Entering 'third_party/NNPACK' 2025-09-07T09:00:54.5373384Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T09:00:54.5394964Z Entering 'third_party/NVTX' 2025-09-07T09:00:54.5437191Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T09:00:54.5460436Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T09:00:54.5501949Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T09:00:54.5523311Z Entering 'third_party/XNNPACK' 2025-09-07T09:00:54.5565096Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T09:00:54.5601238Z Entering 'third_party/aiter' 2025-09-07T09:00:54.5642553Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T09:00:54.5663831Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T09:00:54.5706152Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T09:00:54.5737171Z Entering 'third_party/benchmark' 2025-09-07T09:00:54.5780567Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T09:00:54.5802318Z Entering 'third_party/composable_kernel' 2025-09-07T09:00:54.5851049Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T09:00:54.5881340Z Entering 'third_party/cpp-httplib' 2025-09-07T09:00:54.5922940Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T09:00:54.5945513Z Entering 'third_party/cpuinfo' 2025-09-07T09:00:54.5985657Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T09:00:54.6007839Z Entering 'third_party/cudnn_frontend' 2025-09-07T09:00:54.6049542Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T09:00:54.6072371Z Entering 'third_party/cutlass' 2025-09-07T09:00:54.6114057Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config remote.origin.url 2025-09-07T09:00:54.6144263Z Entering 'third_party/fbgemm' 2025-09-07T09:00:54.6188691Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T09:00:54.6212546Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T09:00:54.6254321Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T09:00:54.6276404Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T09:00:54.6317871Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T09:00:54.6346174Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T09:00:54.6386999Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T09:00:54.6407433Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T09:00:54.7610043Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T09:00:54.7641790Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T09:00:54.7683582Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T09:00:54.7704974Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T09:00:54.7746663Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T09:00:54.7767522Z Entering 'third_party/fbgemm/external/json' 2025-09-07T09:00:54.7809762Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T09:00:54.7836315Z Entering 'third_party/flash-attention' 2025-09-07T09:00:54.7879985Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T09:00:54.7901483Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T09:00:54.7942658Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T09:00:54.7968757Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T09:00:54.8008534Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T09:00:54.8038652Z Entering 'third_party/flatbuffers' 2025-09-07T09:00:54.8079907Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T09:00:54.8105171Z Entering 'third_party/fmt' 2025-09-07T09:00:54.8146441Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T09:00:54.8168502Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T09:00:54.8209337Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T09:00:54.8231498Z Entering 'third_party/gloo' 2025-09-07T09:00:54.8272064Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T09:00:54.8293841Z Entering 'third_party/googletest' 2025-09-07T09:00:54.8339637Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T09:00:54.8361721Z Entering 'third_party/ideep' 2025-09-07T09:00:54.8403349Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T09:00:54.8424130Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T09:00:54.8468300Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T09:00:54.8497570Z Entering 'third_party/ittapi' 2025-09-07T09:00:54.8539140Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T09:00:54.8562897Z Entering 'third_party/kineto' 2025-09-07T09:00:54.8605890Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T09:00:54.8627154Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T09:00:54.8669835Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T09:00:54.8690411Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T09:00:54.8733663Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T09:00:54.8755727Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T09:00:54.8796568Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T09:00:54.8817318Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T09:00:54.8858269Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T09:00:54.8878740Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T09:00:54.8919219Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T09:00:54.8938129Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T09:00:54.8980553Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T09:00:54.9004957Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T09:00:54.9045079Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T09:00:54.9065571Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T09:00:54.9106439Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T09:00:54.9127904Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T09:00:54.9168407Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T09:00:54.9189755Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T09:00:54.9231223Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T09:00:54.9254912Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T09:00:54.9296571Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T09:00:54.9317714Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T09:00:54.9359055Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T09:00:54.9382980Z Entering 'third_party/kleidiai' 2025-09-07T09:00:54.9426985Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T09:00:54.9449469Z Entering 'third_party/mimalloc' 2025-09-07T09:00:54.9491725Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T09:00:54.9513578Z Entering 'third_party/nlohmann' 2025-09-07T09:00:54.9555700Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T09:00:54.9578727Z Entering 'third_party/onnx' 2025-09-07T09:00:54.9621068Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T09:00:54.9658882Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:54.9700971Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T09:00:54.9726337Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T09:00:54.9768920Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T09:00:54.9791107Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:54.9832282Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config remote.origin.url 2025-09-07T09:00:54.9852243Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:54.9891794Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config remote.origin.url 2025-09-07T09:00:54.9912005Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:54.9951917Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config remote.origin.url 2025-09-07T09:00:54.9972232Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:55.0012165Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config remote.origin.url 2025-09-07T09:00:55.0033283Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:55.0073645Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config remote.origin.url 2025-09-07T09:00:55.0093308Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:55.0132956Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config remote.origin.url 2025-09-07T09:00:55.0152955Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:55.0192814Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config remote.origin.url 2025-09-07T09:00:55.0211447Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:55.0253551Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config remote.origin.url 2025-09-07T09:00:55.0275665Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:55.0315891Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/googletest/config remote.origin.url 2025-09-07T09:00:55.0339182Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:55.0379451Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/tools/vcpkg/config remote.origin.url 2025-09-07T09:00:55.0418367Z Entering 'third_party/pocketfft' 2025-09-07T09:00:55.0459907Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/pocketfft/config remote.origin.url 2025-09-07T09:00:55.0482651Z Entering 'third_party/protobuf' 2025-09-07T09:00:55.0524439Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/protobuf/config remote.origin.url 2025-09-07T09:00:55.0549038Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:55.0590455Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/benchmark/config remote.origin.url 2025-09-07T09:00:55.0610799Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:55.0650533Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/googletest/config remote.origin.url 2025-09-07T09:00:55.0674071Z Entering 'third_party/psimd' 2025-09-07T09:00:55.0715557Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/psimd/config remote.origin.url 2025-09-07T09:00:55.0737292Z Entering 'third_party/pthreadpool' 2025-09-07T09:00:55.0779447Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/pthreadpool/config remote.origin.url 2025-09-07T09:00:55.0802002Z Entering 'third_party/pybind11' 2025-09-07T09:00:55.0843921Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/pybind11/config remote.origin.url 2025-09-07T09:00:55.0866835Z Entering 'third_party/python-peachpy' 2025-09-07T09:00:55.0908564Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/python-peachpy/config remote.origin.url 2025-09-07T09:00:55.0931298Z Entering 'third_party/sleef' 2025-09-07T09:00:55.0973067Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/sleef/config remote.origin.url 2025-09-07T09:00:55.0996026Z Entering 'third_party/tensorpipe' 2025-09-07T09:00:55.1038240Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/config remote.origin.url 2025-09-07T09:00:55.1059520Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:55.1100595Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/googletest/config remote.origin.url 2025-09-07T09:00:55.1120881Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:55.1164063Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libnop/config remote.origin.url 2025-09-07T09:00:55.1185107Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:55.1225538Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libuv/config remote.origin.url 2025-09-07T09:00:55.1245735Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:55.1285789Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/config remote.origin.url 2025-09-07T09:00:55.1304800Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:55.1346082Z file:/home/henry/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/modules/tools/clang/config remote.origin.url 2025-09-07T09:00:55.1622461Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'git@github.com:' 2025-09-07T09:00:55.1885404Z Entering 'android/libs/fbjni' 2025-09-07T09:00:55.1929998Z Entering 'third_party/FP16' 2025-09-07T09:00:55.1973936Z Entering 'third_party/FXdiv' 2025-09-07T09:00:55.2017831Z Entering 'third_party/NNPACK' 2025-09-07T09:00:55.2061712Z Entering 'third_party/NVTX' 2025-09-07T09:00:55.2106167Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T09:00:55.2150348Z Entering 'third_party/XNNPACK' 2025-09-07T09:00:55.2208192Z Entering 'third_party/aiter' 2025-09-07T09:00:55.2251956Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T09:00:55.2304403Z Entering 'third_party/benchmark' 2025-09-07T09:00:55.2348463Z Entering 'third_party/composable_kernel' 2025-09-07T09:00:55.2399612Z Entering 'third_party/cpp-httplib' 2025-09-07T09:00:55.2443888Z Entering 'third_party/cpuinfo' 2025-09-07T09:00:55.2488221Z Entering 'third_party/cudnn_frontend' 2025-09-07T09:00:55.2532629Z Entering 'third_party/cutlass' 2025-09-07T09:00:55.2584415Z Entering 'third_party/fbgemm' 2025-09-07T09:00:55.2628085Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T09:00:55.2669566Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T09:00:55.2717034Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T09:00:55.2761493Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T09:00:55.2812053Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T09:00:55.2853160Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T09:00:55.2893788Z Entering 'third_party/fbgemm/external/json' 2025-09-07T09:00:55.2938849Z Entering 'third_party/flash-attention' 2025-09-07T09:00:55.2983237Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T09:00:55.3030652Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T09:00:55.3081145Z Entering 'third_party/flatbuffers' 2025-09-07T09:00:55.3127898Z Entering 'third_party/fmt' 2025-09-07T09:00:55.3172087Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T09:00:55.3216320Z Entering 'third_party/gloo' 2025-09-07T09:00:55.3260015Z Entering 'third_party/googletest' 2025-09-07T09:00:55.3304045Z Entering 'third_party/ideep' 2025-09-07T09:00:55.3346144Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T09:00:55.3395368Z Entering 'third_party/ittapi' 2025-09-07T09:00:55.3439331Z Entering 'third_party/kineto' 2025-09-07T09:00:55.3482947Z Entering 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'third_party/psimd' 2025-09-07T09:00:55.4928561Z Entering 'third_party/pthreadpool' 2025-09-07T09:00:55.4971694Z Entering 'third_party/pybind11' 2025-09-07T09:00:55.5015593Z Entering 'third_party/python-peachpy' 2025-09-07T09:00:55.5059028Z Entering 'third_party/sleef' 2025-09-07T09:00:55.5102801Z Entering 'third_party/tensorpipe' 2025-09-07T09:00:55.5145815Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:55.5186861Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:55.5227213Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:55.5268249Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:55.5307424Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:55.5373624Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-09-07T09:00:55.5635752Z Entering 'android/libs/fbjni' 2025-09-07T09:00:55.5680045Z Entering 'third_party/FP16' 2025-09-07T09:00:55.5724084Z Entering 'third_party/FXdiv' 2025-09-07T09:00:55.5767994Z Entering 'third_party/NNPACK' 2025-09-07T09:00:55.5812393Z Entering 'third_party/NVTX' 2025-09-07T09:00:55.5856600Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T09:00:55.5900535Z Entering 'third_party/XNNPACK' 2025-09-07T09:00:55.5958088Z Entering 'third_party/aiter' 2025-09-07T09:00:55.6002394Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T09:00:55.6054591Z Entering 'third_party/benchmark' 2025-09-07T09:00:55.6098874Z Entering 'third_party/composable_kernel' 2025-09-07T09:00:55.6150403Z Entering 'third_party/cpp-httplib' 2025-09-07T09:00:55.6194280Z Entering 'third_party/cpuinfo' 2025-09-07T09:00:55.6238530Z Entering 'third_party/cudnn_frontend' 2025-09-07T09:00:55.6282632Z Entering 'third_party/cutlass' 2025-09-07T09:00:55.6334227Z Entering 'third_party/fbgemm' 2025-09-07T09:00:55.6379405Z Entering 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2025-09-07T09:00:55.7021662Z Entering 'third_party/googletest' 2025-09-07T09:00:55.7065362Z Entering 'third_party/ideep' 2025-09-07T09:00:55.7108188Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T09:00:55.7157623Z Entering 'third_party/ittapi' 2025-09-07T09:00:55.7201397Z Entering 'third_party/kineto' 2025-09-07T09:00:55.7243976Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T09:00:55.7284478Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T09:00:55.7327291Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T09:00:55.7368079Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T09:00:55.7408440Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T09:00:55.7446927Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T09:00:55.7491677Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T09:00:55.7532376Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T09:00:55.7573595Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T09:00:55.7615127Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T09:00:55.7661871Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T09:00:55.7702407Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T09:00:55.7746471Z Entering 'third_party/kleidiai' 2025-09-07T09:00:55.7792111Z Entering 'third_party/mimalloc' 2025-09-07T09:00:55.7835827Z Entering 'third_party/nlohmann' 2025-09-07T09:00:55.7882038Z Entering 'third_party/onnx' 2025-09-07T09:00:55.7940768Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T09:00:55.7988461Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T09:00:55.8033197Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T09:00:55.8073570Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T09:00:55.8114465Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T09:00:55.8153817Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T09:00:55.8194803Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T09:00:55.8234351Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T09:00:55.8274752Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T09:00:55.8313475Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T09:00:55.8357354Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T09:00:55.8400895Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T09:00:55.8461091Z Entering 'third_party/pocketfft' 2025-09-07T09:00:55.8504798Z Entering 'third_party/protobuf' 2025-09-07T09:00:55.8550869Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T09:00:55.8591904Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T09:00:55.8636538Z Entering 'third_party/psimd' 2025-09-07T09:00:55.8682498Z Entering 'third_party/pthreadpool' 2025-09-07T09:00:55.8726074Z Entering 'third_party/pybind11' 2025-09-07T09:00:55.8770894Z Entering 'third_party/python-peachpy' 2025-09-07T09:00:55.8814823Z Entering 'third_party/sleef' 2025-09-07T09:00:55.8858399Z Entering 'third_party/tensorpipe' 2025-09-07T09:00:55.8901728Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T09:00:55.8943184Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T09:00:55.8983768Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T09:00:55.9025257Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T09:00:55.9064350Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T09:00:55.9125592Z ##[endgroup] 2025-09-07T09:00:55.9173214Z [command]/usr/bin/git log -1 --format=%H 2025-09-07T09:00:55.9201082Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:00:55.9377781Z Prepare all required actions 2025-09-07T09:00:55.9378212Z Getting action download info 2025-09-07T09:00:56.1161176Z ##[group]Run ./.github/actions/setup-linux 2025-09-07T09:00:56.1161432Z env: 2025-09-07T09:00:56.1161597Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:56.1161786Z ##[endgroup] 2025-09-07T09:00:56.1197487Z ##[group]Run set -euo pipefail 2025-09-07T09:00:56.1197781Z set -euo pipefail 2025-09-07T09:00:56.1198250Z function get_ec2_metadata() { 2025-09-07T09:00:56.1198534Z  # Pulled from instance metadata endpoint for EC2 2025-09-07T09:00:56.1199012Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-09-07T09:00:56.1199445Z  category=$1 2025-09-07T09:00:56.1199722Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-09-07T09:00:56.1200055Z  runner_name_str=i-0b7d0f7dc0527ca9b-1008 2025-09-07T09:00:56.1200533Z  if [[ -f /.inarc ]]; then 2025-09-07T09:00:56.1200800Z  echo "ARC Runner, no info on ec2 metadata" 2025-09-07T09:00:56.1201083Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-09-07T09:00:56.1201417Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-09-07T09:00:56.1201721Z  else 2025-09-07T09:00:56.1202331Z  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}" 2025-09-07T09:00:56.1202970Z  fi 2025-09-07T09:00:56.1203125Z } 2025-09-07T09:00:56.1203330Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-09-07T09:00:56.1203654Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-09-07T09:00:56.1204023Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-09-07T09:00:56.1204326Z echo "system info $(uname -a)" 2025-09-07T09:00:56.1219048Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:56.1219345Z env: 2025-09-07T09:00:56.1219515Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:56.1219714Z ##[endgroup] 2025-09-07T09:00:56.1257745Z ami-id: ARC Runner, no info on ec2 metadata 2025-09-07T09:00:56.1263691Z instance-id: ARC Runner, no info on ec2 metadata 2025-09-07T09:00:56.1269679Z instance-type: ARC Runner, no info on ec2 metadata 2025-09-07T09:00:56.1281685Z system info Linux 304d8fe70f44 6.8.0-1017-aws #18~22.04.1-Ubuntu SMP Thu Oct 3 19:57:42 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux 2025-09-07T09:00:56.1304078Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T09:00:56.1304791Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T09:00:56.1319374Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:56.1319677Z env: 2025-09-07T09:00:56.1319845Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:56.1320040Z ##[endgroup] 2025-09-07T09:00:56.1395386Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T09:00:56.1395618Z with: 2025-09-07T09:00:56.1395769Z shell: bash 2025-09-07T09:00:56.1395936Z timeout_minutes: 5 2025-09-07T09:00:56.1396113Z max_attempts: 3 2025-09-07T09:00:56.1396291Z retry_wait_seconds: 30 2025-09-07T09:00:56.1398142Z command: AWS_ACCOUNT_ID=$(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 2025-09-07T09:00:56.1399757Z polling_interval_seconds: 1 2025-09-07T09:00:56.1399955Z warning_on_retry: true 2025-09-07T09:00:56.1400148Z continue_on_error: false 2025-09-07T09:00:56.1400496Z env: 2025-09-07T09:00:56.1400650Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:56.1400836Z AWS_RETRY_MODE: standard 2025-09-07T09:00:56.1401018Z AWS_MAX_ATTEMPTS: 5 2025-09-07T09:00:56.1401380Z AWS_DEFAULT_REGION: us-east-1 2025-09-07T09:00:56.1401576Z ##[endgroup] 2025-09-07T09:00:57.6791010Z 2025-09-07T09:00:57.6791652Z WARNING! Your credentials are stored unencrypted in '/home/henry/.docker/config.json'. 2025-09-07T09:00:57.6792234Z Configure a credential helper to remove this warning. See 2025-09-07T09:00:57.6792654Z https://docs.docker.com/go/credential-store/ 2025-09-07T09:00:57.6792881Z 2025-09-07T09:00:57.6792991Z Login Succeeded 2025-09-07T09:00:58.2122112Z Command completed after 1 attempt(s). 2025-09-07T09:00:58.2209001Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T09:00:58.2209412Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T09:00:58.2209739Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T09:00:58.2224593Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:58.2224890Z env: 2025-09-07T09:00:58.2225054Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:58.2225272Z ##[endgroup] 2025-09-07T09:00:58.2321330Z ##[group]Run set +e 2025-09-07T09:00:58.2321571Z set +e 2025-09-07T09:00:58.2321756Z set -x 2025-09-07T09:00:58.2321920Z  2025-09-07T09:00:58.2322108Z PT_DOMAIN=download.pytorch.org 2025-09-07T09:00:58.2322567Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-09-07T09:00:58.2323120Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-09-07T09:00:58.2323538Z # one is returned at random 2025-09-07T09:00:58.2323833Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-09-07T09:00:58.2324128Z  2025-09-07T09:00:58.2324307Z if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T09:00:58.2324628Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-09-07T09:00:58.2325010Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-09-07T09:00:58.2325447Z  2025-09-07T09:00:58.2325620Z  if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T09:00:58.2325902Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-09-07T09:00:58.2326156Z  exit 1 2025-09-07T09:00:58.2326326Z  fi 2025-09-07T09:00:58.2326482Z fi 2025-09-07T09:00:58.2326630Z  2025-09-07T09:00:58.2326809Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-09-07T09:00:58.2327076Z  # Clean up any old records first 2025-09-07T09:00:58.2327336Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-09-07T09:00:58.2327562Z fi 2025-09-07T09:00:58.2327701Z  2025-09-07T09:00:58.2327926Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-09-07T09:00:58.2328213Z cat /etc/hosts 2025-09-07T09:00:58.2343059Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:58.2343358Z env: 2025-09-07T09:00:58.2343546Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:58.2343741Z ##[endgroup] 2025-09-07T09:00:58.2373589Z + PT_DOMAIN=download.pytorch.org 2025-09-07T09:00:58.2380796Z ++ dig -4 +short download.pytorch.org 2025-09-07T09:00:58.2381533Z ++ tail -n1 2025-09-07T09:00:58.2769947Z + RESOLVED_IP=3.170.131.102 2025-09-07T09:00:58.2770386Z + '[' -z 3.170.131.102 ']' 2025-09-07T09:00:58.2770673Z + grep -r download.pytorch.org /etc/hosts 2025-09-07T09:00:58.2787860Z + echo '3.170.131.102 download.pytorch.org' 2025-09-07T09:00:58.2788713Z + sudo tee -a /etc/hosts 2025-09-07T09:00:58.2853204Z 3.170.131.102 download.pytorch.org 2025-09-07T09:00:58.2862217Z + cat /etc/hosts 2025-09-07T09:00:58.2870453Z 127.0.0.1 localhost 2025-09-07T09:00:58.2875128Z ::1 localhost ip6-localhost ip6-loopback 2025-09-07T09:00:58.2875440Z fe00:: ip6-localnet 2025-09-07T09:00:58.2875653Z ff00:: ip6-mcastprefix 2025-09-07T09:00:58.2875870Z ff02::1 ip6-allnodes 2025-09-07T09:00:58.2876075Z ff02::2 ip6-allrouters 2025-09-07T09:00:58.2876522Z 172.17.0.2 304d8fe70f44 2025-09-07T09:00:58.2876748Z 3.170.131.102 download.pytorch.org 2025-09-07T09:00:58.2896283Z ##[group]Run set +x 2025-09-07T09:00:58.2896504Z set +x 2025-09-07T09:00:58.2896666Z  2025-09-07T09:00:58.2896824Z max_attempts=30 2025-09-07T09:00:58.2897018Z delay=10 2025-09-07T09:00:58.2897181Z attempt=1 2025-09-07T09:00:58.2897344Z  2025-09-07T09:00:58.2897523Z for attempt in $(seq 1 $max_attempts); do 2025-09-07T09:00:58.2897925Z  echo "Attempt $attempt of $max_attempts: Checking if Docker daemon is running..." 2025-09-07T09:00:58.2898296Z  if docker info > /dev/null 2>&1; then 2025-09-07T09:00:58.2898606Z  echo "Docker is running. Proceeding with the next steps" 2025-09-07T09:00:58.2898883Z  exit 0 2025-09-07T09:00:58.2899044Z  else 2025-09-07T09:00:58.2899227Z  echo "Docker is not running yet." 2025-09-07T09:00:58.2899631Z  echo "Retrying in $delay seconds..." 2025-09-07T09:00:58.2899877Z  sleep $delay 2025-09-07T09:00:58.2900051Z  fi 2025-09-07T09:00:58.2900203Z done 2025-09-07T09:00:58.2900624Z echo "Reached maximum attempts to connect to Docker. Exiting." 2025-09-07T09:00:58.2900933Z exit 1 2025-09-07T09:00:58.2914898Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:58.2915186Z env: 2025-09-07T09:00:58.2915348Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:58.2915542Z ##[endgroup] 2025-09-07T09:00:58.2956690Z Attempt 1 of 30: Checking if Docker daemon is running... 2025-09-07T09:00:58.3408571Z Docker is running. Proceeding with the next steps 2025-09-07T09:00:58.3532480Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-09-07T09:00:58.3532862Z with: 2025-09-07T09:00:58.3533543Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:00:58.3534307Z use-custom-docker-registry: true 2025-09-07T09:00:58.3534532Z docker-build-dir: .ci/docker 2025-09-07T09:00:58.3534750Z docker-build-script: ./build.sh 2025-09-07T09:00:58.3534966Z working-directory: . 2025-09-07T09:00:58.3535225Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:00:58.3535522Z force-push: false 2025-09-07T09:00:58.3535691Z env: 2025-09-07T09:00:58.3535860Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:58.3536050Z ##[endgroup] 2025-09-07T09:00:58.3565394Z ##[group]Run set -ex 2025-09-07T09:00:58.3565632Z set -ex 2025-09-07T09:00:58.3565793Z  2025-09-07T09:00:58.3566119Z # If the docker build directory or the build script doesn't exist, the action will 2025-09-07T09:00:58.3566600Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-09-07T09:00:58.3567011Z # job could then download the pre-built image as usual 2025-09-07T09:00:58.3567520Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-09-07T09:00:58.3567974Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3568212Z else 2025-09-07T09:00:58.3568403Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3568715Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3569003Z  2025-09-07T09:00:58.3569402Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-09-07T09:00:58.3569854Z  exit 0 2025-09-07T09:00:58.3570010Z fi 2025-09-07T09:00:58.3570153Z  2025-09-07T09:00:58.3570576Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-09-07T09:00:58.3571248Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-09-07T09:00:58.3571626Z  # use it as it is, but first let's extract the tag 2025-09-07T09:00:58.3571972Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-09-07T09:00:58.3572331Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3572674Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3572972Z else 2025-09-07T09:00:58.3573170Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-09-07T09:00:58.3573438Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-09-07T09:00:58.3573732Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-09-07T09:00:58.3573978Z  fi 2025-09-07T09:00:58.3574302Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-09-07T09:00:58.3574738Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3575192Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3575688Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3576003Z fi 2025-09-07T09:00:58.3589950Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:58.3590411Z env: 2025-09-07T09:00:58.3590579Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:58.3590784Z REPO_NAME: pytorch 2025-09-07T09:00:58.3591705Z 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 2025-09-07T09:00:58.3592447Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T09:00:58.3592663Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-09-07T09:00:58.3592937Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:00:58.3593239Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-09-07T09:00:58.3593454Z CUSTOM_TAG_PREFIX: 2025-09-07T09:00:58.3593653Z ##[endgroup] 2025-09-07T09:00:58.3625203Z + [[ -d .ci/docker ]] 2025-09-07T09:00:58.3625462Z + [[ -f .ci/docker/./build.sh ]] 2025-09-07T09:00:58.3625702Z + [[ true == \t\r\u\e ]] 2025-09-07T09:00:58.3625915Z + echo skip=false 2025-09-07T09:00:58.3626915Z + [[ 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* ]] 2025-09-07T09:00:58.3633898Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:00:58.3634779Z ++ awk -F '[:,]' '{print $2}' 2025-09-07T09:00:58.3648397Z + DOCKER_TAG=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:00:58.3649370Z + echo docker-tag=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:00:58.3650670Z + 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 2025-09-07T09:00:58.3676153Z ##[group]Run set +e 2025-09-07T09:00:58.3676408Z set +e 2025-09-07T09:00:58.3676591Z set -x 2025-09-07T09:00:58.3676757Z  2025-09-07T09:00:58.3676916Z login() { 2025-09-07T09:00:58.3677308Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T09:00:58.3677684Z } 2025-09-07T09:00:58.3677854Z  2025-09-07T09:00:58.3678009Z retry () { 2025-09-07T09:00:58.3678211Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T09:00:58.3678670Z } 2025-09-07T09:00:58.3678823Z  2025-09-07T09:00:58.3678987Z retry login "${DOCKER_REGISTRY}" 2025-09-07T09:00:58.3679211Z  2025-09-07T09:00:58.3679368Z START_TIME=$(date +%s) 2025-09-07T09:00:58.3679584Z # Wait up to 120 minutes 2025-09-07T09:00:58.3679851Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-09-07T09:00:58.3680394Z  # Check if image already exists, if it does then skip building it 2025-09-07T09:00:58.3680764Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-09-07T09:00:58.3681024Z  exit 0 2025-09-07T09:00:58.3681195Z  fi 2025-09-07T09:00:58.3681361Z  2025-09-07T09:00:58.3681645Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-09-07T09:00:58.3682118Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-09-07T09:00:58.3682592Z  # latter, it will wait for the Docker images to become available before continuing 2025-09-07T09:00:58.3682963Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-09-07T09:00:58.3683259Z  # It's a Docker build job, let's build the image 2025-09-07T09:00:58.3683520Z  break 2025-09-07T09:00:58.3683696Z  else 2025-09-07T09:00:58.3683953Z  # It's a regular build job, wait for the image to become available 2025-09-07T09:00:58.3684258Z  sleep 300 2025-09-07T09:00:58.3684441Z  fi 2025-09-07T09:00:58.3684601Z done 2025-09-07T09:00:58.3684756Z  2025-09-07T09:00:58.3685225Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-09-07T09:00:58.3685644Z # be empty. The default action would be to continue rebuild the image 2025-09-07T09:00:58.3686019Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-09-07T09:00:58.3686349Z  # if we're on the base branch then use the parent commit 2025-09-07T09:00:58.3686637Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-09-07T09:00:58.3686891Z else 2025-09-07T09:00:58.3687139Z  # otherwise we're on a PR, so use the most recent base commit 2025-09-07T09:00:58.3687502Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-09-07T09:00:58.3687792Z fi 2025-09-07T09:00:58.3687951Z  2025-09-07T09:00:58.3688132Z if [[ -z "${MERGE_BASE}" ]]; then 2025-09-07T09:00:58.3688403Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3688648Z  2025-09-07T09:00:58.3688990Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-09-07T09:00:58.3689399Z  exit 0 2025-09-07T09:00:58.3689565Z fi 2025-09-07T09:00:58.3689730Z  2025-09-07T09:00:58.3689970Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-09-07T09:00:58.3690639Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-09-07T09:00:58.3691076Z  exit 1 2025-09-07T09:00:58.3691241Z fi 2025-09-07T09:00:58.3691397Z  2025-09-07T09:00:58.3691659Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-09-07T09:00:58.3692150Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-09-07T09:00:58.3692590Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-09-07T09:00:58.3693104Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-09-07T09:00:58.3693681Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-09-07T09:00:58.3694013Z fi 2025-09-07T09:00:58.3694342Z  2025-09-07T09:00:58.3694548Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T09:00:58.3708391Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:58.3708694Z env: 2025-09-07T09:00:58.3708864Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:58.3709087Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T09:00:58.3709343Z BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:00:58.3710098Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:00:58.3711255Z DOCKER_TAG: pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:00:58.3711843Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:00:58.3712136Z DOCKER_PUSH: 2025-09-07T09:00:58.3712315Z ##[endgroup] 2025-09-07T09:00:58.3745362Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:00:58.3745751Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:00:58.3749518Z + aws ecr get-login-password --region us-east-1 2025-09-07T09:00:58.3750073Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:00:59.1243597Z 2025-09-07T09:00:59.1244003Z Login Succeeded 2025-09-07T09:00:59.1244462Z WARNING! Your credentials are stored unencrypted in '/home/henry/.docker/config.json'. 2025-09-07T09:00:59.1244964Z Configure a credential helper to remove this warning. See 2025-09-07T09:00:59.1245344Z https://docs.docker.com/go/credential-store/ 2025-09-07T09:00:59.1245545Z 2025-09-07T09:00:59.1279064Z ++ date +%s 2025-09-07T09:00:59.1290182Z + START_TIME=1757235659 2025-09-07T09:00:59.1294629Z ++ date +%s 2025-09-07T09:00:59.1304723Z + [[ 1757228459 -lt 1757235659 ]] 2025-09-07T09:00:59.1305578Z + 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 2025-09-07T09:00:59.5428485Z { 2025-09-07T09:00:59.5428769Z "schemaVersion": 2, 2025-09-07T09:00:59.5429193Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-09-07T09:00:59.5429603Z "config": { 2025-09-07T09:00:59.5429914Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-09-07T09:00:59.5430525Z "size": 31375, 2025-09-07T09:00:59.5430925Z "digest": "sha256:29d1d8a31b215537637bab7c99e18c255840b899cf7023e4e3cb5efa3270aef8" 2025-09-07T09:00:59.5431362Z }, 2025-09-07T09:00:59.5431542Z "layers": [ 2025-09-07T09:00:59.5431729Z { 2025-09-07T09:00:59.5432070Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5432468Z "size": 30448359, 2025-09-07T09:00:59.5432855Z "digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46" 2025-09-07T09:00:59.5433270Z }, 2025-09-07T09:00:59.5433450Z { 2025-09-07T09:00:59.5433817Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5434196Z "size": 1554, 2025-09-07T09:00:59.5434553Z "digest": "sha256:171dcef20c49de4bc9268f60e02f111b72c638b0f24c3c5636c5013029db6d30" 2025-09-07T09:00:59.5434966Z }, 2025-09-07T09:00:59.5435139Z { 2025-09-07T09:00:59.5435419Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5435772Z "size": 313297922, 2025-09-07T09:00:59.5436154Z "digest": "sha256:4c92b3f72f1df31fe9f487fc1c27fcf1ba475ffb43abd69056306d1247786e40" 2025-09-07T09:00:59.5436569Z }, 2025-09-07T09:00:59.5436735Z { 2025-09-07T09:00:59.5437013Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5437373Z "size": 792, 2025-09-07T09:00:59.5437722Z "digest": "sha256:744f9ba90a6582eb601b3c20409bb10d6dad635dd118c3975f79721f4c82747c" 2025-09-07T09:00:59.5438121Z }, 2025-09-07T09:00:59.5438276Z { 2025-09-07T09:00:59.5438617Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5439414Z "size": 106, 2025-09-07T09:00:59.5439753Z "digest": "sha256:d3c08322a3326e45849dd80264a047c4f42ba4a2419d35c919542e2890e23934" 2025-09-07T09:00:59.5440153Z }, 2025-09-07T09:00:59.5440559Z { 2025-09-07T09:00:59.5440836Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5441199Z "size": 704, 2025-09-07T09:00:59.5441547Z "digest": "sha256:ffd43b71f3ccf3ba563606231cb1d191eb9dd0052f422d54835e6af350525170" 2025-09-07T09:00:59.5441953Z }, 2025-09-07T09:00:59.5442117Z { 2025-09-07T09:00:59.5442390Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5442747Z "size": 1215, 2025-09-07T09:00:59.5443080Z "digest": "sha256:830692b57f6e2758398ec80c3b67a20441d12696b54ed14f2ecebf926198f7d6" 2025-09-07T09:00:59.5443473Z }, 2025-09-07T09:00:59.5443635Z { 2025-09-07T09:00:59.5443914Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5444266Z "size": 482, 2025-09-07T09:00:59.5444610Z "digest": "sha256:5bad36d184686719399be50830a98939d7dbda2313fb407df5915217483fc6a3" 2025-09-07T09:00:59.5444985Z }, 2025-09-07T09:00:59.5445122Z { 2025-09-07T09:00:59.5445337Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5445684Z "size": 110343614, 2025-09-07T09:00:59.5445996Z "digest": "sha256:0e34fdd9ac5c39eb0a9d2c2d258b26f42bb79d7dc0a22014bf201daa2e033eb4" 2025-09-07T09:00:59.5446328Z }, 2025-09-07T09:00:59.5446457Z { 2025-09-07T09:00:59.5446696Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5446985Z "size": 4786, 2025-09-07T09:00:59.5447614Z "digest": "sha256:3c868a62868ef54f82ac11be8dabe1b4365d000bacfe4c104e08022fc96dd767" 2025-09-07T09:00:59.5447951Z }, 2025-09-07T09:00:59.5448084Z { 2025-09-07T09:00:59.5448310Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5448598Z "size": 1710, 2025-09-07T09:00:59.5448900Z "digest": "sha256:62170a22dd571d55ffccac64c0be17f4006d2498cfbf7c6289325f0899cba005" 2025-09-07T09:00:59.5449229Z }, 2025-09-07T09:00:59.5449365Z { 2025-09-07T09:00:59.5449592Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5449884Z "size": 724, 2025-09-07T09:00:59.5450170Z "digest": "sha256:553c1d23b6c4dbd8ab136d0c3659460391ffa14cb9b43be9d7b2f47f90895697" 2025-09-07T09:00:59.5450681Z }, 2025-09-07T09:00:59.5450818Z { 2025-09-07T09:00:59.5451035Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 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"sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T09:00:59.5515171Z }, 2025-09-07T09:00:59.5515305Z { 2025-09-07T09:00:59.5515530Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5515821Z "size": 104, 2025-09-07T09:00:59.5516090Z "digest": "sha256:951e8ce838415c4257680a9d60d216f3750cbb18d243d9a21e2008cce7e589cf" 2025-09-07T09:00:59.5516411Z }, 2025-09-07T09:00:59.5516547Z { 2025-09-07T09:00:59.5516770Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5517053Z "size": 408, 2025-09-07T09:00:59.5517344Z "digest": "sha256:32340b97ae50ba7b2918ab40d6f4a8db875afee69318f484e4deb0a1e2ec4beb" 2025-09-07T09:00:59.5517689Z }, 2025-09-07T09:00:59.5517830Z { 2025-09-07T09:00:59.5518049Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5518340Z "size": 32, 2025-09-07T09:00:59.5518626Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T09:00:59.5518961Z }, 2025-09-07T09:00:59.5519090Z { 2025-09-07T09:00:59.5519328Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5519615Z "size": 109, 2025-09-07T09:00:59.5519916Z "digest": "sha256:5bbb04cd6b57ae13d7cf05ab9e9b4ed9752833ee2dba4eeaac47bde6022c4725" 2025-09-07T09:00:59.5520394Z }, 2025-09-07T09:00:59.5520525Z { 2025-09-07T09:00:59.5520746Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5521032Z "size": 1897, 2025-09-07T09:00:59.5521314Z "digest": "sha256:d8c4b845cfc7ca7cc0604f472bf6da8b1f1d4e98dff3c76e1985a7013a5b9e3f" 2025-09-07T09:00:59.5521653Z }, 2025-09-07T09:00:59.5521794Z { 2025-09-07T09:00:59.5522019Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5522307Z "size": 243440375, 2025-09-07T09:00:59.5522595Z "digest": "sha256:b35c180f4d8ddc2396eac4a6b893f438481a8163ceb0b88f203488bc5f2a8ba4" 2025-09-07T09:00:59.5523083Z }, 2025-09-07T09:00:59.5523216Z { 2025-09-07T09:00:59.5523433Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5523718Z "size": 106, 2025-09-07T09:00:59.5524007Z "digest": "sha256:5f967b3c303a99e609441551f7c8988cca4fd464c0c3127506bff8509583091b" 2025-09-07T09:00:59.5524325Z }, 2025-09-07T09:00:59.5524460Z { 2025-09-07T09:00:59.5524676Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5524962Z "size": 166, 2025-09-07T09:00:59.5525252Z "digest": "sha256:04770904f012e5584f1c19a0bc92d9863baaebf08bf75b4a9981f2b7795c8953" 2025-09-07T09:00:59.5525578Z }, 2025-09-07T09:00:59.5525715Z { 2025-09-07T09:00:59.5525940Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5526233Z "size": 7943, 2025-09-07T09:00:59.5526516Z "digest": "sha256:73373941fb321b4cb4a171b1423a68a4c7fedada3a1498868d7efe93cb03170e" 2025-09-07T09:00:59.5526836Z }, 2025-09-07T09:00:59.5526974Z { 2025-09-07T09:00:59.5527198Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5527497Z "size": 8072, 2025-09-07T09:00:59.5527776Z "digest": "sha256:9572e6cd907bfa4888456dbccc6e22146a0044374585f3fa0a8ced19b831ed62" 2025-09-07T09:00:59.5528102Z }, 2025-09-07T09:00:59.5528239Z { 2025-09-07T09:00:59.5528464Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5528757Z "size": 304, 2025-09-07T09:00:59.5529042Z "digest": "sha256:64a544aba233551e38898f138dd6ba3161ccdb9554e0ffb5b9d8f0f7fe4a7fa8" 2025-09-07T09:00:59.5529372Z }, 2025-09-07T09:00:59.5529506Z { 2025-09-07T09:00:59.5529877Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5530187Z "size": 13362696, 2025-09-07T09:00:59.5530603Z "digest": "sha256:7e35418a24997de5428763c93826679486760a1a9563209ae64de66ba45f99c1" 2025-09-07T09:00:59.5530923Z }, 2025-09-07T09:00:59.5531051Z { 2025-09-07T09:00:59.5531296Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5531592Z "size": 108, 2025-09-07T09:00:59.5531877Z "digest": "sha256:2ed8e82748d4a1131f41d9e41322f47a6ffef67a5a2b7bf5392237db5c035c61" 2025-09-07T09:00:59.5532196Z }, 2025-09-07T09:00:59.5532328Z { 2025-09-07T09:00:59.5532554Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5532841Z "size": 54145663, 2025-09-07T09:00:59.5533127Z "digest": "sha256:c988fbcccd708fb158a81c429d32e1060a7e40924fc3c987c629fa69d9484717" 2025-09-07T09:00:59.5533456Z }, 2025-09-07T09:00:59.5533590Z { 2025-09-07T09:00:59.5533823Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T09:00:59.5534103Z "size": 32, 2025-09-07T09:00:59.5534383Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T09:00:59.5534715Z } 2025-09-07T09:00:59.5534846Z ] 2025-09-07T09:00:59.5534976Z } 2025-09-07T09:00:59.5535136Z + exit 0 2025-09-07T09:00:59.5558765Z ##[group]Run set -eux 2025-09-07T09:00:59.5558981Z set -eux 2025-09-07T09:00:59.5559287Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-09-07T09:00:59.5560109Z 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 2025-09-07T09:00:59.5575786Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:00:59.5576077Z env: 2025-09-07T09:00:59.5576243Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:00:59.5576440Z ##[endgroup] 2025-09-07T09:00:59.5626174Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-09-07T09:00:59.5626856Z + jq --raw-output .SecretString 2025-09-07T09:00:59.5628894Z + jq -r .docker_hub_readonly_token 2025-09-07T09:00:59.5630621Z + docker login --username pytorchbot --password-stdin 2025-09-07T09:01:00.1932945Z 2025-09-07T09:01:00.1934663Z An error occurred (AccessDeniedException) when calling the GetSecretValue operation: User: arn:aws:sts::308535385114:assumed-role/gh-ci-github-action-runners-runner-role/i-0b7d0f7dc0527ca9b is not authorized to perform: secretsmanager:GetSecretValue on resource: docker_hub_readonly_token because no identity-based policy allows the secretsmanager:GetSecretValue action 2025-09-07T09:01:00.2740909Z Error: Cannot perform an interactive login from a non TTY device 2025-09-07T09:01:00.2764382Z + true 2025-09-07T09:01:00.2833172Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T09:01:00.2833528Z tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T09:01:00.2833917Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-09-07T09:01:00.2851390Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:01:00.2851837Z env: 2025-09-07T09:01:00.2852009Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:01:00.2852742Z 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 2025-09-07T09:01:00.2853468Z ##[endgroup] 2025-09-07T09:01:00.2887999Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:01:00.2935967Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-09-07T09:01:00.2936365Z with: 2025-09-07T09:01:00.2937027Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:01:00.2938074Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:01:00.2938524Z env: 2025-09-07T09:01:00.2938689Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:01:00.2938884Z ##[endgroup] 2025-09-07T09:01:00.2953296Z ##[group]Run set -x 2025-09-07T09:01:00.2953523Z set -x 2025-09-07T09:01:00.2953693Z set +e 2025-09-07T09:01:00.2953850Z  2025-09-07T09:01:00.2954002Z login() { 2025-09-07T09:01:00.2954362Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T09:01:00.2954737Z } 2025-09-07T09:01:00.2954962Z  2025-09-07T09:01:00.2955185Z retry () { 2025-09-07T09:01:00.2955390Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T09:01:00.2955616Z } 2025-09-07T09:01:00.2955772Z  2025-09-07T09:01:00.2955941Z retry login "${DOCKER_REGISTRY}" 2025-09-07T09:01:00.2956163Z  2025-09-07T09:01:00.2956618Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-09-07T09:01:00.2957099Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-09-07T09:01:00.2957368Z  2025-09-07T09:01:00.2957541Z set -e 2025-09-07T09:01:00.2957887Z # ignore output since only exit code is used for conditional 2025-09-07T09:01:00.2958399Z # only pull docker image if it's not available locally 2025-09-07T09:01:00.2958923Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-09-07T09:01:00.2959530Z  retry docker pull "${DOCKER_IMAGE}" 2025-09-07T09:01:00.2959776Z fi 2025-09-07T09:01:00.2976369Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:01:00.2976723Z env: 2025-09-07T09:01:00.2976887Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:01:00.2977831Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:01:00.2978755Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:01:00.2979040Z ##[endgroup] 2025-09-07T09:01:00.3010193Z + set +e 2025-09-07T09:01:00.3010947Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:01:00.3011278Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:01:00.3015424Z + aws ecr get-login-password --region us-east-1 2025-09-07T09:01:00.3016280Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T09:01:01.1465350Z 2025-09-07T09:01:01.1465881Z WARNING! Your credentials are stored unencrypted in '/home/henry/.docker/config.json'. 2025-09-07T09:01:01.1466364Z Configure a credential helper to remove this warning. See 2025-09-07T09:01:01.1466719Z https://docs.docker.com/go/credential-store/ 2025-09-07T09:01:01.1466910Z 2025-09-07T09:01:01.1466995Z Login Succeeded 2025-09-07T09:01:01.1501022Z ++ 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 2025-09-07T09:01:01.1502485Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-09-07T09:01:01.6096168Z + IMAGE_SIZE=36183.606596946716 2025-09-07T09:01:01.6096536Z + echo 'Compressed size of image in MB: 36183.606596946716' 2025-09-07T09:01:01.6096868Z + set -e 2025-09-07T09:01:01.6098140Z + 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 2025-09-07T09:01:01.6099077Z Compressed size of image in MB: 36183.606596946716 2025-09-07T09:01:01.6227115Z + 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 2025-09-07T09:01:01.6228361Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:01:02.0359611Z pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image 2025-09-07T09:01:02.0360693Z e6fdc8487bfe: Pulling fs layer 2025-09-07T09:01:02.0360981Z 171dcef20c49: Pulling fs layer 2025-09-07T09:01:02.0361232Z 4c92b3f72f1d: Pulling fs layer 2025-09-07T09:01:02.0361466Z 744f9ba90a65: Pulling fs layer 2025-09-07T09:01:02.0361733Z d3c08322a332: Pulling fs layer 2025-09-07T09:01:02.0361981Z ffd43b71f3cc: Pulling fs layer 2025-09-07T09:01:02.0362223Z 830692b57f6e: Pulling fs layer 2025-09-07T09:01:02.0362464Z 5bad36d18468: Pulling fs layer 2025-09-07T09:01:02.0362708Z 0e34fdd9ac5c: Pulling fs layer 2025-09-07T09:01:02.0362942Z 744f9ba90a65: Waiting 2025-09-07T09:01:02.0363162Z 3c868a62868e: Pulling fs layer 2025-09-07T09:01:02.0363399Z 62170a22dd57: Pulling fs layer 2025-09-07T09:01:02.0363641Z 553c1d23b6c4: Pulling fs layer 2025-09-07T09:01:02.0363875Z 9408d557a804: Pulling fs layer 2025-09-07T09:01:02.0364098Z d3c08322a332: Waiting 2025-09-07T09:01:02.0364307Z df607cfc7c07: Pulling fs layer 2025-09-07T09:01:02.0364544Z ffd43b71f3cc: Waiting 2025-09-07T09:01:02.0364746Z 830692b57f6e: Waiting 2025-09-07T09:01:02.0364993Z 5bad36d18468: Waiting 2025-09-07T09:01:02.0365202Z 4f4fb700ef54: Pulling fs layer 2025-09-07T09:01:02.0365425Z 3c868a62868e: Waiting 2025-09-07T09:01:02.0365645Z 40a8e39faeda: Pulling fs layer 2025-09-07T09:01:02.0365862Z 62170a22dd57: Waiting 2025-09-07T09:01:02.0366058Z d895771c9fac: Pulling fs layer 2025-09-07T09:01:02.0366271Z 0e34fdd9ac5c: Waiting 2025-09-07T09:01:02.0366467Z c4ee04f39d49: Pulling fs layer 2025-09-07T09:01:02.0366682Z 4f4fb700ef54: Waiting 2025-09-07T09:01:02.0366863Z 9408d557a804: Waiting 2025-09-07T09:01:02.0367036Z 553c1d23b6c4: Waiting 2025-09-07T09:01:02.0367226Z 3690c9826e48: Pulling fs layer 2025-09-07T09:01:02.0367434Z d895771c9fac: Waiting 2025-09-07T09:01:02.0367617Z df607cfc7c07: Waiting 2025-09-07T09:01:02.0367797Z 40a8e39faeda: Waiting 2025-09-07T09:01:02.0367985Z c4ee04f39d49: Waiting 2025-09-07T09:01:02.0368182Z 57cbc5013733: Pulling fs layer 2025-09-07T09:01:02.0368875Z f5f4b06b58bb: Pulling fs layer 2025-09-07T09:01:02.0369082Z 3690c9826e48: Waiting 2025-09-07T09:01:02.0369276Z 57cbc5013733: Waiting 2025-09-07T09:01:02.0369472Z f59713ce4bf4: Pulling fs layer 2025-09-07T09:01:02.0369690Z fe0486521517: Pulling fs layer 2025-09-07T09:01:02.0369902Z f5f4b06b58bb: Waiting 2025-09-07T09:01:02.0370107Z 8c21cc3715a2: Pulling fs layer 2025-09-07T09:01:02.0370483Z d37c58456a6a: Pulling fs layer 2025-09-07T09:01:02.0370705Z d042f63abc13: Pulling fs layer 2025-09-07T09:01:02.0370918Z 621284a9c05a: Pulling fs layer 2025-09-07T09:01:02.0371127Z f59713ce4bf4: Waiting 2025-09-07T09:01:02.0371323Z 85f605d2dd3a: Pulling fs layer 2025-09-07T09:01:02.0371542Z 381b5539e598: Pulling fs layer 2025-09-07T09:01:02.0371745Z fe0486521517: Waiting 2025-09-07T09:01:02.0371933Z d042f63abc13: Waiting 2025-09-07T09:01:02.0372119Z 621284a9c05a: Waiting 2025-09-07T09:01:02.0372313Z a487c0c80029: Pulling fs layer 2025-09-07T09:01:02.0372518Z d37c58456a6a: Waiting 2025-09-07T09:01:02.0372712Z 8c21cc3715a2: Waiting 2025-09-07T09:01:02.0372905Z 48bcb81e2566: Pulling fs layer 2025-09-07T09:01:02.0373110Z 85f605d2dd3a: Waiting 2025-09-07T09:01:02.0373294Z 381b5539e598: Waiting 2025-09-07T09:01:02.0373488Z a487c0c80029: Waiting 2025-09-07T09:01:02.0373681Z e261928c0043: Pulling fs layer 2025-09-07T09:01:02.0373883Z 48bcb81e2566: Waiting 2025-09-07T09:01:02.0374343Z 0fea55428091: Pulling fs layer 2025-09-07T09:01:02.0374576Z b4291bccbb84: Pulling fs layer 2025-09-07T09:01:02.0374795Z ddc91b09189a: Pulling fs layer 2025-09-07T09:01:02.0374998Z 7540c7428627: Pulling fs layer 2025-09-07T09:01:02.0375185Z 003c4e2598fb: Pulling fs layer 2025-09-07T09:01:02.0375373Z 5687149362ae: Pulling fs layer 2025-09-07T09:01:02.0375577Z cdd2cf54eb2a: Pulling fs layer 2025-09-07T09:01:02.0375770Z d3ad4df1ba3a: Pulling fs layer 2025-09-07T09:01:02.0375973Z 3c9055753b4c: Pulling fs layer 2025-09-07T09:01:02.0376158Z 7540c7428627: Waiting 2025-09-07T09:01:02.0376324Z 003c4e2598fb: Waiting 2025-09-07T09:01:02.0376488Z e261928c0043: Waiting 2025-09-07T09:01:02.0376649Z 0fea55428091: Waiting 2025-09-07T09:01:02.0376809Z 5687149362ae: Waiting 2025-09-07T09:01:02.0376998Z 31cf8d0bd21c: Pulling fs layer 2025-09-07T09:01:02.0377190Z cdd2cf54eb2a: Waiting 2025-09-07T09:01:02.0377359Z b4291bccbb84: Waiting 2025-09-07T09:01:02.0377537Z ddc91b09189a: Waiting 2025-09-07T09:01:02.0377710Z d3ad4df1ba3a: Waiting 2025-09-07T09:01:02.0377878Z 6623ea814971: Pulling fs layer 2025-09-07T09:01:02.0378066Z 3c9055753b4c: Waiting 2025-09-07T09:01:02.0378236Z 31cf8d0bd21c: Waiting 2025-09-07T09:01:02.0378411Z 11696c3aa380: Pulling fs layer 2025-09-07T09:01:02.0378601Z ef4d544e35ca: Pulling fs layer 2025-09-07T09:01:02.0378795Z 5c5108865e5e: Pulling fs layer 2025-09-07T09:01:02.0378989Z 9e97578e9edf: Pulling fs layer 2025-09-07T09:01:02.0379173Z 6623ea814971: Waiting 2025-09-07T09:01:02.0379341Z da5a91b54cb5: Pulling fs layer 2025-09-07T09:01:02.0379527Z 11696c3aa380: Waiting 2025-09-07T09:01:02.0379690Z ef4d544e35ca: Waiting 2025-09-07T09:01:02.0379861Z 5c5108865e5e: Waiting 2025-09-07T09:01:02.0380031Z da5a91b54cb5: Waiting 2025-09-07T09:01:02.0380198Z 9e97578e9edf: Waiting 2025-09-07T09:01:02.0380512Z 1e93be219e89: Pulling fs layer 2025-09-07T09:01:02.0380709Z 136825afebb5: Pulling fs layer 2025-09-07T09:01:02.0380902Z 22b39805302d: Pulling fs layer 2025-09-07T09:01:02.0381107Z d12add675e35: Pulling fs layer 2025-09-07T09:01:02.0381305Z bc127046d33a: Pulling fs layer 2025-09-07T09:01:02.0381499Z 951e8ce83841: Pulling fs layer 2025-09-07T09:01:02.0381704Z 32340b97ae50: Pulling fs layer 2025-09-07T09:01:02.0381895Z 1e93be219e89: Waiting 2025-09-07T09:01:02.0382062Z bc127046d33a: Waiting 2025-09-07T09:01:02.0382223Z 136825afebb5: Waiting 2025-09-07T09:01:02.0382414Z 951e8ce83841: Waiting 2025-09-07T09:01:02.0382578Z 22b39805302d: Waiting 2025-09-07T09:01:02.0382751Z 5bbb04cd6b57: Pulling fs layer 2025-09-07T09:01:02.0383065Z 32340b97ae50: Waiting 2025-09-07T09:01:02.0383240Z d8c4b845cfc7: Pulling fs layer 2025-09-07T09:01:02.0383639Z b35c180f4d8d: Pulling fs layer 2025-09-07T09:01:02.0383839Z 5f967b3c303a: Pulling fs layer 2025-09-07T09:01:02.0384027Z 5bbb04cd6b57: Waiting 2025-09-07T09:01:02.0384189Z 04770904f012: Pulling fs layer 2025-09-07T09:01:02.0384387Z d8c4b845cfc7: Waiting 2025-09-07T09:01:02.0384555Z b35c180f4d8d: Waiting 2025-09-07T09:01:02.0384733Z 73373941fb32: Pulling fs layer 2025-09-07T09:01:02.0384929Z 9572e6cd907b: Pulling fs layer 2025-09-07T09:01:02.0385123Z 64a544aba233: Pulling fs layer 2025-09-07T09:01:02.0385318Z 73373941fb32: Waiting 2025-09-07T09:01:02.0385488Z 7e35418a2499: Pulling fs layer 2025-09-07T09:01:02.0385679Z 2ed8e82748d4: Pulling fs layer 2025-09-07T09:01:02.0385872Z c988fbcccd70: Pulling fs layer 2025-09-07T09:01:02.0386061Z 64a544aba233: Waiting 2025-09-07T09:01:02.0386224Z 7e35418a2499: Waiting 2025-09-07T09:01:02.0386381Z 2ed8e82748d4: Waiting 2025-09-07T09:01:02.0386545Z c988fbcccd70: Waiting 2025-09-07T09:01:02.2086076Z 171dcef20c49: Verifying Checksum 2025-09-07T09:01:02.2086373Z 171dcef20c49: Download complete 2025-09-07T09:01:02.3734860Z 744f9ba90a65: Verifying Checksum 2025-09-07T09:01:02.3735421Z 744f9ba90a65: Download complete 2025-09-07T09:01:02.5039771Z e6fdc8487bfe: Verifying Checksum 2025-09-07T09:01:02.5040057Z e6fdc8487bfe: Download complete 2025-09-07T09:01:02.5136275Z d3c08322a332: Verifying Checksum 2025-09-07T09:01:02.5136923Z d3c08322a332: Download complete 2025-09-07T09:01:02.6619618Z ffd43b71f3cc: Verifying Checksum 2025-09-07T09:01:02.6619923Z ffd43b71f3cc: Download complete 2025-09-07T09:01:02.6757186Z 830692b57f6e: Download complete 2025-09-07T09:01:02.8544874Z 5bad36d18468: Verifying Checksum 2025-09-07T09:01:02.8545208Z 5bad36d18468: Download complete 2025-09-07T09:01:03.0164420Z 3c868a62868e: Verifying Checksum 2025-09-07T09:01:03.0164720Z 3c868a62868e: Download complete 2025-09-07T09:01:03.1765962Z 62170a22dd57: Verifying Checksum 2025-09-07T09:01:03.1766250Z 62170a22dd57: Download complete 2025-09-07T09:01:03.2776294Z e6fdc8487bfe: Pull complete 2025-09-07T09:01:03.3207097Z 171dcef20c49: Pull complete 2025-09-07T09:01:03.3463769Z 553c1d23b6c4: Verifying Checksum 2025-09-07T09:01:03.3464119Z 553c1d23b6c4: Download complete 2025-09-07T09:01:03.5015994Z 9408d557a804: Verifying Checksum 2025-09-07T09:01:03.5016291Z 9408d557a804: Download complete 2025-09-07T09:01:03.9317338Z 0e34fdd9ac5c: Verifying Checksum 2025-09-07T09:01:03.9317692Z 0e34fdd9ac5c: Download complete 2025-09-07T09:01:03.9823677Z 4f4fb700ef54: Verifying Checksum 2025-09-07T09:01:03.9824042Z 4f4fb700ef54: Download complete 2025-09-07T09:01:04.1481643Z 40a8e39faeda: Verifying Checksum 2025-09-07T09:01:04.1481955Z 40a8e39faeda: Download complete 2025-09-07T09:01:04.8308749Z d895771c9fac: Verifying Checksum 2025-09-07T09:01:04.8309112Z d895771c9fac: Download complete 2025-09-07T09:01:05.0346949Z c4ee04f39d49: Download complete 2025-09-07T09:01:05.3077146Z 3690c9826e48: Download complete 2025-09-07T09:01:05.3181118Z 4c92b3f72f1d: Verifying Checksum 2025-09-07T09:01:05.3181421Z 4c92b3f72f1d: Download complete 2025-09-07T09:01:05.4826809Z 57cbc5013733: Verifying Checksum 2025-09-07T09:01:05.4827154Z 57cbc5013733: Download complete 2025-09-07T09:01:05.4952211Z f5f4b06b58bb: Verifying Checksum 2025-09-07T09:01:05.4952517Z f5f4b06b58bb: Download complete 2025-09-07T09:01:05.6486072Z f59713ce4bf4: Verifying Checksum 2025-09-07T09:01:05.6486462Z f59713ce4bf4: Download complete 2025-09-07T09:01:05.6646637Z fe0486521517: Download complete 2025-09-07T09:01:05.8304486Z d37c58456a6a: Verifying Checksum 2025-09-07T09:01:05.8304793Z d37c58456a6a: Download complete 2025-09-07T09:01:06.3359672Z d042f63abc13: Verifying Checksum 2025-09-07T09:01:06.3360020Z d042f63abc13: Download complete 2025-09-07T09:01:06.4693563Z 621284a9c05a: Verifying Checksum 2025-09-07T09:01:06.4693889Z 621284a9c05a: Download complete 2025-09-07T09:01:06.6226708Z 85f605d2dd3a: Verifying Checksum 2025-09-07T09:01:06.6227010Z 85f605d2dd3a: Download complete 2025-09-07T09:01:12.3114737Z 381b5539e598: Verifying Checksum 2025-09-07T09:01:12.3115093Z 381b5539e598: Download complete 2025-09-07T09:01:12.5484281Z a487c0c80029: Verifying Checksum 2025-09-07T09:01:12.5484634Z a487c0c80029: Download complete 2025-09-07T09:01:12.8309050Z 48bcb81e2566: Verifying Checksum 2025-09-07T09:01:12.8309375Z 48bcb81e2566: Download complete 2025-09-07T09:01:12.9924012Z e261928c0043: Download complete 2025-09-07T09:01:13.3682121Z 0fea55428091: Verifying Checksum 2025-09-07T09:01:13.3682653Z 0fea55428091: Download complete 2025-09-07T09:01:13.8685722Z b4291bccbb84: Download complete 2025-09-07T09:01:14.0356060Z ddc91b09189a: Verifying Checksum 2025-09-07T09:01:14.0356430Z ddc91b09189a: Download complete 2025-09-07T09:01:14.1921773Z 7540c7428627: Download complete 2025-09-07T09:01:14.3585293Z 003c4e2598fb: Download complete 2025-09-07T09:01:14.4928573Z 5687149362ae: Verifying Checksum 2025-09-07T09:01:14.4928954Z 5687149362ae: Download complete 2025-09-07T09:01:14.8998666Z cdd2cf54eb2a: Verifying Checksum 2025-09-07T09:01:14.8999272Z cdd2cf54eb2a: Download complete 2025-09-07T09:01:16.7168378Z 4c92b3f72f1d: Pull complete 2025-09-07T09:01:17.1029347Z 744f9ba90a65: Pull complete 2025-09-07T09:01:17.4550045Z d3c08322a332: Pull complete 2025-09-07T09:01:17.9871029Z ffd43b71f3cc: Pull complete 2025-09-07T09:01:18.7616640Z 830692b57f6e: Pull complete 2025-09-07T09:01:19.3139901Z 5bad36d18468: Pull complete 2025-09-07T09:01:21.0030597Z 0e34fdd9ac5c: Pull complete 2025-09-07T09:01:21.0272697Z 3c868a62868e: Pull complete 2025-09-07T09:01:21.0603559Z 62170a22dd57: Pull complete 2025-09-07T09:01:21.1878904Z 553c1d23b6c4: Pull complete 2025-09-07T09:01:21.4946039Z 9408d557a804: Pull complete 2025-09-07T09:01:36.3213719Z df607cfc7c07: Verifying Checksum 2025-09-07T09:01:36.3214115Z df607cfc7c07: Download complete 2025-09-07T09:01:36.4804848Z 3c9055753b4c: Verifying Checksum 2025-09-07T09:01:36.4805185Z 3c9055753b4c: Download complete 2025-09-07T09:01:40.1748134Z 31cf8d0bd21c: Verifying Checksum 2025-09-07T09:01:40.1748494Z 31cf8d0bd21c: Download complete 2025-09-07T09:02:20.2238907Z df607cfc7c07: Pull complete 2025-09-07T09:02:23.3098389Z 4f4fb700ef54: Pull complete 2025-09-07T09:02:25.2761633Z 8c21cc3715a2: Verifying Checksum 2025-09-07T09:02:25.2761959Z 8c21cc3715a2: Download complete 2025-09-07T09:02:25.4186667Z 11696c3aa380: Verifying Checksum 2025-09-07T09:02:25.4186966Z 11696c3aa380: Download complete 2025-09-07T09:02:25.5964822Z ef4d544e35ca: Verifying Checksum 2025-09-07T09:02:25.5965192Z ef4d544e35ca: Download complete 2025-09-07T09:02:25.7569105Z 5c5108865e5e: Verifying Checksum 2025-09-07T09:02:25.7569417Z 5c5108865e5e: Download complete 2025-09-07T09:02:26.0597727Z 9e97578e9edf: Verifying Checksum 2025-09-07T09:02:26.0598014Z 9e97578e9edf: Download complete 2025-09-07T09:02:26.2191219Z da5a91b54cb5: Verifying Checksum 2025-09-07T09:02:26.2191517Z da5a91b54cb5: Download complete 2025-09-07T09:02:26.3531593Z 40a8e39faeda: Pull complete 2025-09-07T09:02:26.5088526Z 1e93be219e89: Verifying Checksum 2025-09-07T09:02:26.5088815Z 1e93be219e89: Download complete 2025-09-07T09:02:26.7829726Z 136825afebb5: Verifying Checksum 2025-09-07T09:02:26.7830027Z 136825afebb5: Download complete 2025-09-07T09:02:27.0078372Z 22b39805302d: Verifying Checksum 2025-09-07T09:02:27.0078691Z 22b39805302d: Download complete 2025-09-07T09:02:27.1536943Z d12add675e35: Verifying Checksum 2025-09-07T09:02:27.1537266Z d12add675e35: Download complete 2025-09-07T09:02:27.3195012Z bc127046d33a: Verifying Checksum 2025-09-07T09:02:27.3195303Z bc127046d33a: Download complete 2025-09-07T09:02:27.6314206Z 951e8ce83841: Verifying Checksum 2025-09-07T09:02:27.6314477Z 951e8ce83841: Download complete 2025-09-07T09:02:27.7698617Z 32340b97ae50: Download complete 2025-09-07T09:02:28.0836750Z 5bbb04cd6b57: Verifying Checksum 2025-09-07T09:02:28.0837021Z 5bbb04cd6b57: Download complete 2025-09-07T09:02:28.2421619Z d8c4b845cfc7: Verifying Checksum 2025-09-07T09:02:28.2421911Z d8c4b845cfc7: Download complete 2025-09-07T09:02:30.2497877Z d895771c9fac: Pull complete 2025-09-07T09:02:30.9047969Z b35c180f4d8d: Verifying Checksum 2025-09-07T09:02:30.9048288Z b35c180f4d8d: Download complete 2025-09-07T09:02:31.2194502Z 5f967b3c303a: Verifying Checksum 2025-09-07T09:02:31.2194792Z 5f967b3c303a: Download complete 2025-09-07T09:02:31.4197417Z 04770904f012: Download complete 2025-09-07T09:02:31.7665593Z 73373941fb32: Verifying Checksum 2025-09-07T09:02:31.7665918Z 73373941fb32: Download complete 2025-09-07T09:02:32.1151970Z 9572e6cd907b: Verifying Checksum 2025-09-07T09:02:32.1152281Z 9572e6cd907b: Download complete 2025-09-07T09:02:32.4646403Z 64a544aba233: Verifying Checksum 2025-09-07T09:02:32.4646742Z 64a544aba233: Download complete 2025-09-07T09:02:32.8302883Z 7e35418a2499: Verifying Checksum 2025-09-07T09:02:32.8303205Z 7e35418a2499: Download complete 2025-09-07T09:02:33.1611416Z 2ed8e82748d4: Verifying Checksum 2025-09-07T09:02:33.1611801Z 2ed8e82748d4: Download complete 2025-09-07T09:02:33.6229688Z c4ee04f39d49: Pull complete 2025-09-07T09:02:34.1342897Z c988fbcccd70: Verifying Checksum 2025-09-07T09:02:34.1343249Z c988fbcccd70: Download complete 2025-09-07T09:02:38.3514486Z 3690c9826e48: Pull complete 2025-09-07T09:02:43.0591798Z 57cbc5013733: Pull complete 2025-09-07T09:02:45.7718970Z f5f4b06b58bb: Pull complete 2025-09-07T09:02:47.9099873Z 6623ea814971: Verifying Checksum 2025-09-07T09:02:47.9100550Z 6623ea814971: Download complete 2025-09-07T09:02:49.5673093Z f59713ce4bf4: Pull complete 2025-09-07T09:02:53.4461901Z fe0486521517: Pull complete 2025-09-07T09:03:59.8698204Z 8c21cc3715a2: Pull complete 2025-09-07T09:04:02.8955403Z d37c58456a6a: Pull complete 2025-09-07T09:04:07.8325036Z d042f63abc13: Pull complete 2025-09-07T09:04:12.7011550Z 621284a9c05a: Pull complete 2025-09-07T09:04:17.9036367Z 85f605d2dd3a: Pull complete 2025-09-07T09:04:21.2072914Z d3ad4df1ba3a: Verifying Checksum 2025-09-07T09:04:21.2073295Z d3ad4df1ba3a: Download complete 2025-09-07T09:04:32.1290871Z 381b5539e598: Pull complete 2025-09-07T09:04:35.5558914Z a487c0c80029: Pull complete 2025-09-07T09:04:39.4769391Z 48bcb81e2566: Pull complete 2025-09-07T09:13:49.2140829Z e261928c0043: Pull complete 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sha256:f30843ff9ea9e117a2c8e6d207e85c9e77dfe682f1dfcdfea5b94178d1bf00b3 2025-09-07T09:23:45.4959002Z 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 2025-09-07T09:23:45.7105489Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:23:45.7307536Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T09:23:45.7308292Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T09:23:45.7323119Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:23:45.7323407Z env: 2025-09-07T09:23:45.7323567Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:23:45.7323766Z ##[endgroup] 2025-09-07T09:23:45.9718727Z ##[group]Run echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T09:23:45.9719371Z echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T09:23:45.9733144Z shell: /usr/bin/bash -e {0} 2025-09-07T09:23:45.9733360Z env: 2025-09-07T09:23:45.9733520Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:23:45.9733717Z ##[endgroup] 2025-09-07T09:23:46.2158259Z ##[group]Run echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T09:23:46.2159009Z echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T09:23:46.2172676Z shell: /usr/bin/bash -e {0} 2025-09-07T09:23:46.2172892Z env: 2025-09-07T09:23:46.2173051Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:23:46.2173316Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:23:46.2173584Z ##[endgroup] 2025-09-07T09:23:46.2652487Z Prepare all required actions 2025-09-07T09:23:46.3061017Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-09-07T09:23:46.3061299Z with: 2025-09-07T09:23:46.3061969Z github-token: *** 2025-09-07T09:23:46.3062179Z env: 2025-09-07T09:23:46.3062352Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:23:46.3062709Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:23:46.3063088Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:23:46.3063398Z ##[endgroup] 2025-09-07T09:23:46.4243549Z ##[group]Run set -eux 2025-09-07T09:23:46.4243782Z set -eux 2025-09-07T09:23:46.4244162Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T09:23:46.4257360Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:23:46.4257646Z env: 2025-09-07T09:23:46.4257815Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:23:46.4258070Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:23:46.4258432Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:23:46.4258952Z GITHUB_TOKEN: *** 2025-09-07T09:23:46.4259136Z ##[endgroup] 2025-09-07T09:23:46.4604381Z + python3 .github/scripts/get_workflow_job_id.py 17525296438 i-0b7d0f7dc0527ca9b-1008 2025-09-07T09:23:47.2723445Z Setting output job-id=49775781863 2025-09-07T09:23:47.2723947Z Setting output job-name=test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:23:47.3220838Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T09:23:47.3221487Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T09:23:47.3222239Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-09-07T09:23:47.3222984Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-09-07T09:23:47.3237469Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:23:47.3238017Z env: 2025-09-07T09:23:47.3238195Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:23:47.3238457Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:23:47.3238795Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:23:47.3239083Z JOB_ID: 49775781863 2025-09-07T09:23:47.3239446Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:23:47.3239854Z WORKFLOW_NAME: inductor-perf-nightly-h100 2025-09-07T09:23:47.3240109Z WORKFLOW_RUN_ID: 17525296438 2025-09-07T09:23:47.3240513Z MONITOR_LOG_INTERVAL: 15 2025-09-07T09:23:47.3240738Z MONITOR_DATA_COLLECT_INTERVAL: 4 2025-09-07T09:23:47.3240954Z ##[endgroup] 2025-09-07T09:23:47.6437756Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T09:23:48.3579973Z Collecting psutil==5.9.8 2025-09-07T09:23:48.4730122Z 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) 2025-09-07T09:23:48.9649918Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 KB 817.9 kB/s eta 0:00:00 2025-09-07T09:23:49.4382292Z Collecting dataclasses_json==0.6.7 2025-09-07T09:23:49.4486482Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-09-07T09:23:50.6098585Z Collecting nvidia-ml-py==11.525.84 2025-09-07T09:23:50.6215585Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-09-07T09:23:52.0077273Z Collecting marshmallow<4.0.0,>=3.18.0 2025-09-07T09:23:52.0181865Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-09-07T09:23:52.5185797Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 50.9/50.9 KB 81.6 kB/s eta 0:00:00 2025-09-07T09:23:52.9236591Z Collecting typing-inspect<1,>=0.4.0 2025-09-07T09:23:52.9340903Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-09-07T09:23:53.8081766Z Collecting packaging>=17.0 2025-09-07T09:23:53.8184291Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-09-07T09:23:54.2380423Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 66.5/66.5 KB 134.7 kB/s eta 0:00:00 2025-09-07T09:23:54.6817861Z Collecting typing-extensions>=3.7.4 2025-09-07T09:23:54.6921271Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-09-07T09:23:55.0896649Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.6/44.6 KB 86.9 kB/s eta 0:00:00 2025-09-07T09:23:55.5087550Z Collecting mypy-extensions>=0.3.0 2025-09-07T09:23:55.5192247Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-09-07T09:23:55.9573546Z Installing collected packages: nvidia-ml-py, typing-extensions, psutil, packaging, mypy-extensions, typing-inspect, marshmallow, dataclasses_json 2025-09-07T09:24:04.2493004Z 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 2025-09-07T09:24:04.3056748Z Prepare all required actions 2025-09-07T09:24:04.3057105Z Getting action download info 2025-09-07T09:24:04.4772620Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-09-07T09:24:05.6378431Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-09-07T09:24:08.9491710Z ##[group]Run ./.github/actions/download-build-artifacts 2025-09-07T09:24:08.9492070Z with: 2025-09-07T09:24:08.9492327Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T09:24:08.9492596Z s3-bucket: gha-artifacts 2025-09-07T09:24:08.9492797Z env: 2025-09-07T09:24:08.9492980Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:08.9493241Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:08.9493580Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:08.9493873Z ##[endgroup] 2025-09-07T09:24:09.3977142Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T09:24:09.3977416Z with: 2025-09-07T09:24:09.3977610Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T09:24:09.3978117Z s3-bucket: gha-artifacts 2025-09-07T09:24:09.3978325Z region: us-east-1 2025-09-07T09:24:09.3978492Z env: 2025-09-07T09:24:09.3978655Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:09.3978916Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:09.3979274Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:09.3979575Z ##[endgroup] 2025-09-07T09:24:09.8059903Z (node:7934) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T09:24:09.8060528Z 2025-09-07T09:24:09.8060711Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T09:24:09.8061213Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T09:24:09.8061751Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T09:24:09.9236787Z Found 1 objects with prefix pytorch/pytorch/17525296438/linux-jammy-cuda12.8-py3.10-gcc9-sm90/ 2025-09-07T09:24:09.9237413Z Starting download (1/1): /home/henry/_work/pytorch/pytorch/artifacts.zip 2025-09-07T09:24:20.1950189Z Finished download (1/1): /home/henry/_work/pytorch/pytorch/artifacts.zip 2025-09-07T09:24:20.1958099Z Artifact download has finished successfully 2025-09-07T09:24:20.2307363Z ##[group]Run unzip -o artifacts.zip 2025-09-07T09:24:20.2307637Z unzip -o artifacts.zip 2025-09-07T09:24:20.2322314Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:20.2322592Z env: 2025-09-07T09:24:20.2322775Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:20.2323036Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:20.2323366Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:20.2323640Z ##[endgroup] 2025-09-07T09:24:20.2828283Z Archive: artifacts.zip 2025-09-07T09:24:20.2830708Z creating: dist/ 2025-09-07T09:24:22.0195594Z inflating: dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T09:24:22.0196052Z creating: dist/vision/ 2025-09-07T09:24:22.0305225Z inflating: dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:24:22.0305949Z creating: dist/audio/ 2025-09-07T09:24:22.0360649Z inflating: dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:24:22.0361083Z creating: dist/torchrec/ 2025-09-07T09:24:22.0384518Z inflating: dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:24:22.0384910Z creating: dist/fbgemm_gpu/ 2025-09-07T09:24:22.8676619Z inflating: dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:24:22.8677074Z creating: dist/ao/ 2025-09-07T09:24:22.8715198Z inflating: dist/ao/torchao-0.7.0+git51c87b6e-py3-none-any.whl 2025-09-07T09:24:22.8834325Z inflating: dist/.ninja_log 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build/bin/test_nativert 2025-09-07T09:24:30.9982160Z inflating: build/bin/test_dist_autograd 2025-09-07T09:24:31.0046385Z inflating: build/bin/test_cpp_rpc 2025-09-07T09:24:31.1113900Z inflating: build/bin/test_api 2025-09-07T09:24:31.1116042Z inflating: build/bin/parallel_benchmark 2025-09-07T09:24:31.1178175Z inflating: build/bin/ProcessGroupGlooTest 2025-09-07T09:24:31.1237609Z inflating: build/bin/ProcessGroupNCCLTest 2025-09-07T09:24:31.1292596Z inflating: build/bin/ProcessGroupGlooAsyncTest 2025-09-07T09:24:31.1350185Z inflating: build/bin/ProcessGroupNCCLErrorsTest 2025-09-07T09:24:31.2345766Z inflating: build/bin/test_jit 2025-09-07T09:24:31.2664921Z inflating: build/bin/test_lazy 2025-09-07T09:24:31.2668288Z inflating: build/bin/torch_shm_manager 2025-09-07T09:24:31.2668887Z creating: .additional_ci_files/ 2025-09-07T09:24:31.2748739Z inflating: .additional_ci_files/test-times.json 2025-09-07T09:24:31.3052254Z inflating: .additional_ci_files/test-class-times.json 2025-09-07T09:24:31.3149109Z ##[group]Run rm artifacts.zip 2025-09-07T09:24:31.3149384Z rm artifacts.zip 2025-09-07T09:24:31.3164063Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:31.3164370Z env: 2025-09-07T09:24:31.3164534Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:31.3164796Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:31.3165163Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:31.3165443Z ##[endgroup] 2025-09-07T09:24:31.6317161Z ##[group]Run df -H 2025-09-07T09:24:31.6317379Z df -H 2025-09-07T09:24:31.6331072Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:31.6331369Z env: 2025-09-07T09:24:31.6331538Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:31.6331800Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:31.6332134Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:31.6332410Z ##[endgroup] 2025-09-07T09:24:31.6762343Z Filesystem Size Used Avail Use% Mounted on 2025-09-07T09:24:31.6762668Z overlay 7.3T 639G 6.7T 9% / 2025-09-07T09:24:31.6762925Z tmpfs 68M 0 68M 0% /dev 2025-09-07T09:24:31.6763187Z shm 68M 0 68M 0% /dev/shm 2025-09-07T09:24:31.6763471Z /dev/root 7.3T 639G 6.7T 9% /home/henry/_work 2025-09-07T09:24:31.6763797Z tmpfs 215G 111k 215G 1% /run/docker.sock 2025-09-07T09:24:31.6764105Z tmpfs 1.1T 13k 1.1T 1% /proc/driver/nvidia 2025-09-07T09:24:31.6764480Z tmpfs 430G 2.9M 430G 1% /run/.ro3453729222/nvidia-persistenced/socket 2025-09-07T09:24:31.6764824Z tmpfs 1.1T 0 1.1T 0% /proc/acpi 2025-09-07T09:24:31.6765529Z tmpfs 1.1T 0 1.1T 0% /proc/scsi 2025-09-07T09:24:31.6765811Z tmpfs 1.1T 0 1.1T 0% /sys/firmware 2025-09-07T09:24:31.6792460Z Prepare all required actions 2025-09-07T09:24:31.6793158Z Getting action download info 2025-09-07T09:24:31.8558647Z ##[group]Run ./.github/actions/download-td-artifacts 2025-09-07T09:24:31.8558950Z with: 2025-09-07T09:24:31.8559129Z env: 2025-09-07T09:24:31.8559318Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:31.8559608Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:31.8559980Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:31.8560471Z ##[endgroup] 2025-09-07T09:24:31.9939793Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T09:24:31.9940069Z with: 2025-09-07T09:24:31.9940421Z name: td_results 2025-09-07T09:24:31.9940614Z s3-bucket: gha-artifacts 2025-09-07T09:24:31.9940821Z region: us-east-1 2025-09-07T09:24:31.9940989Z env: 2025-09-07T09:24:31.9941144Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:31.9941395Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:31.9941849Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:31.9942149Z ##[endgroup] 2025-09-07T09:24:32.4023671Z (node:7959) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T09:24:32.4024332Z 2025-09-07T09:24:32.4024601Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T09:24:32.4025338Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T09:24:32.4026085Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T09:24:32.5218189Z Found 0 objects with prefix pytorch/pytorch/17525296438/td_results/ 2025-09-07T09:24:32.5225211Z Artifact download has finished successfully 2025-09-07T09:24:32.5612950Z ##[group]Run mkdir -p .additional_ci_files 2025-09-07T09:24:32.5613269Z mkdir -p .additional_ci_files 2025-09-07T09:24:32.5613628Z mv td_results.json .additional_ci_files/td_results.json || true 2025-09-07T09:24:32.5628115Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:32.5628414Z env: 2025-09-07T09:24:32.5628584Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:32.5628838Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:32.5629193Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:32.5629481Z ##[endgroup] 2025-09-07T09:24:32.6067238Z mv: cannot stat 'td_results.json': No such file or directory 2025-09-07T09:24:32.7274312Z ##[group]Run .github/scripts/parse_ref.py 2025-09-07T09:24:32.7274672Z .github/scripts/parse_ref.py 2025-09-07T09:24:32.7289091Z shell: /usr/bin/bash -e {0} 2025-09-07T09:24:32.7289583Z env: 2025-09-07T09:24:32.7289757Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:32.7290030Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:32.7290529Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:32.7290827Z ##[endgroup] 2025-09-07T09:24:32.7901098Z Setting output branch=main 2025-09-07T09:24:32.7998556Z Prepare all required actions 2025-09-07T09:24:32.7998906Z Getting action download info 2025-09-07T09:24:32.9537161Z ##[group]Run ./.github/actions/filter-test-configs 2025-09-07T09:24:32.9537514Z with: 2025-09-07T09:24:32.9537975Z github-token: *** 2025-09-07T09:24:32.9542987Z test-matrix: {"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T09:24:32.9548056Z job-name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:24:32.9548403Z env: 2025-09-07T09:24:32.9548562Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:32.9548816Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:32.9549147Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:32.9549429Z ##[endgroup] 2025-09-07T09:24:33.0843801Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T09:24:33.0844051Z with: 2025-09-07T09:24:33.0844221Z shell: bash 2025-09-07T09:24:33.0844395Z timeout_minutes: 10 2025-09-07T09:24:33.0844579Z max_attempts: 5 2025-09-07T09:24:33.0844755Z retry_wait_seconds: 30 2025-09-07T09:24:33.0845349Z 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 2025-09-07T09:24:33.0845990Z polling_interval_seconds: 1 2025-09-07T09:24:33.0846203Z warning_on_retry: true 2025-09-07T09:24:33.0846399Z continue_on_error: false 2025-09-07T09:24:33.0846589Z env: 2025-09-07T09:24:33.0846751Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:33.0847212Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:33.0847555Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:33.0848019Z GITHUB_TOKEN: *** 2025-09-07T09:24:33.0848201Z ##[endgroup] 2025-09-07T09:24:33.1568661Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T09:24:33.4241492Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T09:24:34.5477723Z Collecting requests==2.27.1 2025-09-07T09:24:34.6091724Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-09-07T09:24:35.0787749Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 113.2 kB/s eta 0:00:00 2025-09-07T09:24:35.5722424Z Collecting pyyaml==6.0.2 2025-09-07T09:24:35.5843050Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-09-07T09:24:35.8086433Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 3.3 MB/s eta 0:00:00 2025-09-07T09:24:35.8193755Z Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.27.1) (2020.6.20) 2025-09-07T09:24:35.8199617Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.27.1) (1.26.5) 2025-09-07T09:24:36.8981721Z Collecting charset-normalizer~=2.0.0 2025-09-07T09:24:37.1928723Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-09-07T09:24:37.8904608Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.27.1) (3.3) 2025-09-07T09:24:37.9583884Z Installing collected packages: pyyaml, charset-normalizer, requests 2025-09-07T09:24:39.5968812Z WARNING: The script normalizer is installed in '/home/henry/.local/bin' which is not on PATH. 2025-09-07T09:24:39.5969594Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T09:24:41.3512373Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-09-07T09:24:42.1616198Z Command completed after 1 attempt(s). 2025-09-07T09:24:42.2155939Z ##[group]Run set -x 2025-09-07T09:24:42.2156186Z set -x 2025-09-07T09:24:42.2156383Z  2025-09-07T09:24:42.2156731Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T09:24:42.2157157Z # in runner workspace 2025-09-07T09:24:42.2157504Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-09-07T09:24:42.2172220Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:42.2172526Z env: 2025-09-07T09:24:42.2172691Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:42.2172938Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:42.2173267Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:42.2173553Z ##[endgroup] 2025-09-07T09:24:42.2647391Z + python3 /home/henry/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-09-07T09:24:42.2790837Z Setting output branch=main 2025-09-07T09:24:42.4013849Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T09:24:42.4014221Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T09:24:42.4014473Z echo "Job name: ${JOB_NAME}" 2025-09-07T09:24:42.4014718Z  2025-09-07T09:24:42.4015019Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T09:24:42.4015391Z # in runner workspace 2025-09-07T09:24:42.4015820Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-09-07T09:24:42.4016242Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-09-07T09:24:42.4016503Z  --job-name "${JOB_NAME}" \ 2025-09-07T09:24:42.4022100Z  --test-matrix "{"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]}" \ 2025-09-07T09:24:42.4027301Z  --selected-test-configs "" \ 2025-09-07T09:24:42.4027542Z  --pr-number "${PR_NUMBER}" \ 2025-09-07T09:24:42.4027776Z  --tag "${TAG}" \ 2025-09-07T09:24:42.4027987Z  --event-name "${EVENT_NAME}" \ 2025-09-07T09:24:42.4028217Z  --schedule "${SCHEDULE}" \ 2025-09-07T09:24:42.4028441Z  --branch "${HEAD_BRANCH}" 2025-09-07T09:24:42.4043256Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:42.4043571Z env: 2025-09-07T09:24:42.4043740Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:42.4043997Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:42.4044327Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:42.4044812Z GITHUB_TOKEN: *** 2025-09-07T09:24:42.4045134Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:24:42.4045496Z PR_NUMBER: 2025-09-07T09:24:42.4045658Z TAG: 2025-09-07T09:24:42.4045839Z EVENT_NAME: schedule 2025-09-07T09:24:42.4046021Z SCHEDULE: 0 7 * * 0 2025-09-07T09:24:42.4046201Z HEAD_BRANCH: main 2025-09-07T09:24:42.4046374Z ##[endgroup] 2025-09-07T09:24:42.4457446Z Workflow: inductor-perf-nightly-h100 2025-09-07T09:24:42.4457978Z Job name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:24:42.6598094Z Setting output keep-going=True 2025-09-07T09:24:42.6598394Z Setting output ci-verbose-test-logs=False 2025-09-07T09:24:42.6598715Z Setting output ci-test-showlocals=False 2025-09-07T09:24:42.6599021Z Setting output ci-no-test-timeout=False 2025-09-07T09:24:42.6599317Z Setting output ci-no-td=False 2025-09-07T09:24:42.6599580Z Setting output ci-td-distributed=False 2025-09-07T09:24:42.6599872Z Setting output is-unstable=False 2025-09-07T09:24:42.6600139Z Setting output reenabled-issues= 2025-09-07T09:24:42.6606622Z Setting output test-matrix={"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T09:24:42.6612662Z Setting output is-test-matrix-empty=False 2025-09-07T09:24:42.6997996Z ##[group]Run echo "Filtered matrix:" 2025-09-07T09:24:42.6998319Z echo "Filtered matrix:" 2025-09-07T09:24:42.7004213Z echo "{"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]}" 2025-09-07T09:24:42.7009278Z  2025-09-07T09:24:42.7009434Z echo 2025-09-07T09:24:42.7009640Z echo "Is the current job unstable? False" 2025-09-07T09:24:42.7009881Z  2025-09-07T09:24:42.7010024Z echo 2025-09-07T09:24:42.7010334Z echo "Is keep-going label set? True" 2025-09-07T09:24:42.7010574Z  2025-09-07T09:24:42.7010728Z echo 2025-09-07T09:24:42.7010907Z echo "Reenabled issues? " 2025-09-07T09:24:42.7024853Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:42.7025146Z env: 2025-09-07T09:24:42.7025315Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:42.7025559Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:42.7025889Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:42.7026171Z ##[endgroup] 2025-09-07T09:24:42.7455804Z Filtered matrix: 2025-09-07T09:24:42.7461851Z {include: [{config: inductor_huggingface_perf_cuda_h100, shard: 1, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 2, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 3, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 4, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 5, num_shards: 5, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 1, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 2, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 3, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 4, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 5, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 6, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 7, num_shards: 7, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 1, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 2, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 3, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 4, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 5, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 6, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 7, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 8, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 9, num_shards: 9, runner: linux.aws.h100}]} 2025-09-07T09:24:42.7467049Z 2025-09-07T09:24:42.7467150Z Is the current job unstable? False 2025-09-07T09:24:42.7467322Z 2025-09-07T09:24:42.7467416Z Is keep-going label set? True 2025-09-07T09:24:42.7467567Z 2025-09-07T09:24:42.7467640Z Reenabled issues? 2025-09-07T09:24:42.8306934Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T09:24:42.8307360Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T09:24:42.8320652Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:42.8320954Z env: 2025-09-07T09:24:42.8321129Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:42.8321607Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:42.8321936Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:42.8322212Z JOB_TIMEOUT: 1440 2025-09-07T09:24:42.8322384Z ##[endgroup] 2025-09-07T09:24:42.9058796Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T09:24:42.9059254Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T09:24:42.9059621Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T09:24:42.9074234Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T09:24:42.9074521Z env: 2025-09-07T09:24:42.9074686Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:42.9074940Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:42.9075270Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:42.9075554Z ##[endgroup] 2025-09-07T09:24:43.0704647Z ##[group]Run set -x 2025-09-07T09:24:43.0704942Z set -x 2025-09-07T09:24:43.0705132Z  2025-09-07T09:24:43.0705326Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-09-07T09:24:43.0705628Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-09-07T09:24:43.0705935Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-09-07T09:24:43.0706224Z  TEST_COMMAND=.ci/onnx/test.sh 2025-09-07T09:24:43.0706450Z else 2025-09-07T09:24:43.0706650Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T09:24:43.0706893Z fi 2025-09-07T09:24:43.0707057Z  2025-09-07T09:24:43.0707253Z # Leaving 1GB for the runner and other things 2025-09-07T09:24:43.0707696Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-09-07T09:24:43.0708366Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-09-07T09:24:43.0708902Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-09-07T09:24:43.0709310Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-09-07T09:24:43.0709632Z  2025-09-07T09:24:43.0709849Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T09:24:43.0710114Z  SHM_OPTS= 2025-09-07T09:24:43.0710493Z  JENKINS_USER= 2025-09-07T09:24:43.0710764Z  # ensure that docker container cleanly exits in 12 hours 2025-09-07T09:24:43.0711133Z  # if for some reason cleanup action doesn't stop container 2025-09-07T09:24:43.0711440Z  # when job is cancelled 2025-09-07T09:24:43.0711688Z  DOCKER_SHELL_CMD="sleep 12h" 2025-09-07T09:24:43.0711922Z else 2025-09-07T09:24:43.0712120Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-09-07T09:24:43.0712396Z  JENKINS_USER="--user jenkins" 2025-09-07T09:24:43.0712639Z  DOCKER_SHELL_CMD= 2025-09-07T09:24:43.0712842Z fi 2025-09-07T09:24:43.0713015Z  2025-09-07T09:24:43.0713266Z # detached container should get cleaned up by teardown_ec2_linux 2025-09-07T09:24:43.0713658Z # TODO: Stop building test binaries as part of the build phase 2025-09-07T09:24:43.0714090Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-09-07T09:24:43.0714470Z # shellcheck disable=SC2086,SC2090 2025-09-07T09:24:43.0714714Z container_name=$(docker run \ 2025-09-07T09:24:43.0714949Z  ${GPU_FLAG:-} \ 2025-09-07T09:24:43.0715182Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-09-07T09:24:43.0715433Z  -e BUILD_ENVIRONMENT \ 2025-09-07T09:24:43.0715654Z  -e PR_NUMBER \ 2025-09-07T09:24:43.0715856Z  -e GITHUB_ACTIONS \ 2025-09-07T09:24:43.0716071Z  -e GITHUB_REPOSITORY \ 2025-09-07T09:24:43.0716284Z  -e GITHUB_WORKFLOW \ 2025-09-07T09:24:43.0716490Z  -e GITHUB_JOB \ 2025-09-07T09:24:43.0716920Z  -e GITHUB_RUN_ID \ 2025-09-07T09:24:43.0717137Z  -e GITHUB_RUN_NUMBER \ 2025-09-07T09:24:43.0717354Z  -e GITHUB_RUN_ATTEMPT \ 2025-09-07T09:24:43.0717576Z  -e JOB_ID \ 2025-09-07T09:24:43.0717762Z  -e JOB_NAME \ 2025-09-07T09:24:43.0717954Z  -e BASE_SHA \ 2025-09-07T09:24:43.0718130Z  -e BRANCH \ 2025-09-07T09:24:43.0718308Z  -e SHA1 \ 2025-09-07T09:24:43.0718493Z  -e AWS_DEFAULT_REGION \ 2025-09-07T09:24:43.0718706Z  -e IN_WHEEL_TEST \ 2025-09-07T09:24:43.0718906Z  -e SHARD_NUMBER \ 2025-09-07T09:24:43.0719114Z  -e TEST_CONFIG \ 2025-09-07T09:24:43.0719311Z  -e NUM_TEST_SHARDS \ 2025-09-07T09:24:43.0719521Z  -e REENABLED_ISSUES \ 2025-09-07T09:24:43.0719734Z  -e CONTINUE_THROUGH_ERROR \ 2025-09-07T09:24:43.0720159Z  -e VERBOSE_TEST_LOGS \ 2025-09-07T09:24:43.0720535Z  -e TEST_SHOWLOCALS \ 2025-09-07T09:24:43.0720756Z  -e NO_TEST_TIMEOUT \ 2025-09-07T09:24:43.0720961Z  -e NO_TD \ 2025-09-07T09:24:43.0721154Z  -e TD_DISTRIBUTED \ 2025-09-07T09:24:43.0721360Z  -e PR_LABELS \ 2025-09-07T09:24:43.0721606Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-09-07T09:24:43.0721871Z  -e SCCACHE_BUCKET \ 2025-09-07T09:24:43.0722081Z  -e SCCACHE_REGION \ 2025-09-07T09:24:43.0722279Z  -e XLA_CUDA \ 2025-09-07T09:24:43.0722497Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-09-07T09:24:43.0722764Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-09-07T09:24:43.0723032Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-09-07T09:24:43.0723293Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-09-07T09:24:43.0723551Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-09-07T09:24:43.0723802Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-09-07T09:24:43.0724062Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-09-07T09:24:43.0724298Z  -e DASHBOARD_TAG \ 2025-09-07T09:24:43.0724513Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-09-07T09:24:43.0724777Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-09-07T09:24:43.0725076Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-09-07T09:24:43.0725365Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-09-07T09:24:43.0725638Z  --security-opt seccomp=unconfined \ 2025-09-07T09:24:43.0725884Z  --cap-add=SYS_PTRACE \ 2025-09-07T09:24:43.0726098Z  --ipc=host \ 2025-09-07T09:24:43.0726280Z  ${SHM_OPTS} \ 2025-09-07T09:24:43.0726470Z  --tty \ 2025-09-07T09:24:43.0726642Z  --detach \ 2025-09-07T09:24:43.0726836Z  --name="${container_name}" \ 2025-09-07T09:24:43.0727062Z  ${JENKINS_USER} \ 2025-09-07T09:24:43.0727309Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-09-07T09:24:43.0727600Z  -w /var/lib/jenkins/workspace \ 2025-09-07T09:24:43.0727829Z  "${DOCKER_IMAGE}" \ 2025-09-07T09:24:43.0728031Z  ${DOCKER_SHELL_CMD} 2025-09-07T09:24:43.0728217Z ) 2025-09-07T09:24:43.0728429Z # Propagate download.pytorch.org IP to container 2025-09-07T09:24:43.0728913Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-09-07T09:24:43.0729419Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-09-07T09:24:43.0729710Z  2025-09-07T09:24:43.0729892Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T09:24:43.0730450Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-09-07T09:24:43.0730822Z fi 2025-09-07T09:24:43.0730979Z  2025-09-07T09:24:43.0731333Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-09-07T09:24:43.0745271Z shell: /usr/bin/bash -e {0} 2025-09-07T09:24:43.0745490Z env: 2025-09-07T09:24:43.0745657Z GIT_DEFAULT_BRANCH: main 2025-09-07T09:24:43.0745909Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:24:43.0746242Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T09:24:43.0746591Z BUILD_ENVIRONMENT: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T09:24:43.0746865Z PR_NUMBER: 2025-09-07T09:24:43.0747052Z GITHUB_REPOSITORY: pytorch/pytorch 2025-09-07T09:24:43.0747305Z GITHUB_WORKFLOW: inductor-perf-nightly-h100 2025-09-07T09:24:43.0747558Z GITHUB_JOB: test 2025-09-07T09:24:43.0747737Z GITHUB_RUN_ID: 17525296438 2025-09-07T09:24:43.0747937Z GITHUB_RUN_NUMBER: 662 2025-09-07T09:24:43.0748128Z GITHUB_RUN_ATTEMPT: 1 2025-09-07T09:24:43.0748299Z JOB_ID: 49775781863 2025-09-07T09:24:43.0748784Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:24:43.0749151Z BRANCH: main 2025-09-07T09:24:43.0749341Z SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:24:43.0749606Z BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:24:43.0749879Z TEST_CONFIG: inductor_torchbench_perf_cuda_h100 2025-09-07T09:24:43.0750117Z SHARD_NUMBER: 8 2025-09-07T09:24:43.0750446Z NUM_TEST_SHARDS: 9 2025-09-07T09:24:43.0750613Z REENABLED_ISSUES: 2025-09-07T09:24:43.0750794Z CONTINUE_THROUGH_ERROR: True 2025-09-07T09:24:43.0751014Z VERBOSE_TEST_LOGS: False 2025-09-07T09:24:43.0751207Z TEST_SHOWLOCALS: False 2025-09-07T09:24:43.0751387Z NO_TEST_TIMEOUT: False 2025-09-07T09:24:43.0751561Z NO_TD: False 2025-09-07T09:24:43.0751722Z TD_DISTRIBUTED: False 2025-09-07T09:24:43.0751944Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-09-07T09:24:43.0752207Z SCCACHE_REGION: us-east-1 2025-09-07T09:24:43.0752393Z SHM_SIZE: 2g 2025-09-07T09:24:43.0753049Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T09:24:43.0753738Z XLA_CUDA: 2025-09-07T09:24:43.0753997Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:24:43.0754330Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-09-07T09:24:43.0754565Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-09-07T09:24:43.0755477Z 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 2025-09-07T09:24:43.0756543Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-09-07T09:24:43.0756849Z HUGGING_FACE_HUB_TOKEN: *** 2025-09-07T09:24:43.0757157Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-09-07T09:24:43.0757541Z ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T09:24:43.0757922Z ##[endgroup] 2025-09-07T09:24:43.2020118Z + [[ inductor_torchbench_perf_cuda_h100 == \m\u\l\t\i\g\p\u ]] 2025-09-07T09:24:43.2020934Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *onnx* ]] 2025-09-07T09:24:43.2021291Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T09:24:43.2026008Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-09-07T09:24:43.2039315Z + TOTAL_AVAILABLE_MEMORY_IN_GB='1998.949 ' 2025-09-07T09:24:43.2039618Z + TOTAL_MEMORY_WITH_SWAP=2001 2025-09-07T09:24:43.2039942Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *\s\3\9\0\x* ]] 2025-09-07T09:24:43.2040465Z + SHM_OPTS=--shm-size=2g 2025-09-07T09:24:43.2040704Z + JENKINS_USER='--user jenkins' 2025-09-07T09:24:43.2040940Z + DOCKER_SHELL_CMD= 2025-09-07T09:24:43.2050520Z +++ nproc --ignore=2 2025-09-07T09:24:43.3752657Z ++ docker run --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all -e SCCACHE_SERVER_PORT=5234 -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=22 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e VLLM_TEST_HUGGING_FACE_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=1998g --memory-swap=2001g --env-file=/tmp/github_env_17525296438 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=2g --tty --detach --name= --user jenkins -v /home/henry/_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 2025-09-07T09:31:26.1568953Z + container_name=89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T09:31:26.1572876Z + grep download.pytorch.org /etc/hosts 2025-09-07T09:31:26.1574152Z + docker exec -i 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 sudo bash -c '/bin/cat >> /etc/hosts' 2025-09-07T09:31:26.2354033Z + echo DOCKER_CONTAINER_ID=89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T09:31:26.2354640Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *\s\3\9\0\x* ]] 2025-09-07T09:31:26.2358634Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:26.2361386Z + docker exec -t 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-09-07T09:31:26.6272871Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d) 2025-09-07T09:31:26.9316444Z 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) 2025-09-07T09:31:26.9320969Z 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) 2025-09-07T09:31:26.9324594Z 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) 2025-09-07T09:31:26.9328647Z 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) 2025-09-07T09:31:26.9330928Z 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) 2025-09-07T09:31:26.9334759Z 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) 2025-09-07T09:31:26.9346816Z 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) 2025-09-07T09:31:26.9664389Z 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) 2025-09-07T09:31:26.9680567Z 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) 2025-09-07T09:31:26.9712221Z 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) 2025-09-07T09:31:27.7650143Z Installing collected packages: torch 2025-09-07T09:31:37.6226264Z 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. 2025-09-07T09:31:37.6227678Z dall-e 0.1 requires torchvision, which is not installed. 2025-09-07T09:31:37.6228358Z effdet 0.4.1 requires torchvision, which is not installed. 2025-09-07T09:31:37.6229104Z python-doctr 1.0.0 requires torchvision>=0.15.0, which is not installed. 2025-09-07T09:31:37.6229981Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed. 2025-09-07T09:31:37.6231766Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed. 2025-09-07T09:31:37.6232544Z timm 1.0.14 requires torchvision, which is not installed. 2025-09-07T09:31:37.6233442Z Successfully installed torch-2.9.0a0+git93fb23d 2025-09-07T09:31:37.7025571Z + export TERM=vt100 2025-09-07T09:31:37.7025823Z + TERM=vt100 2025-09-07T09:31:37.7028362Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:31:37.7037934Z + source .ci/pytorch/common.sh 2025-09-07T09:31:37.7040988Z +++ dirname .ci/pytorch/common.sh 2025-09-07T09:31:37.7047756Z ++ source .ci/pytorch/common_utils.sh 2025-09-07T09:31:37.7048836Z +++ declare -f -t trap_add 2025-09-07T09:31:37.7052724Z ++ set -ex -o pipefail 2025-09-07T09:31:37.7052994Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T09:31:37.7053287Z ++ BUILD_TEST_LIBTORCH=0 2025-09-07T09:31:37.7056682Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:31:37.7065580Z + source .ci/pytorch/common-build.sh 2025-09-07T09:31:37.7066798Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *win-* ]] 2025-09-07T09:31:37.7074596Z ++++ dirname .ci/pytorch/common-build.sh 2025-09-07T09:31:37.7085990Z +++ cd .ci/pytorch 2025-09-07T09:31:37.7086328Z +++ pwd -P 2025-09-07T09:31:37.7087601Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-09-07T09:31:37.7088018Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-pch* ]] 2025-09-07T09:31:37.7088310Z ++ which sccache 2025-09-07T09:31:37.7103402Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-09-07T09:31:37.7103675Z ++ sccache --stop-server 2025-09-07T09:31:37.7132632Z ++ true 2025-09-07T09:31:37.7132863Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-09-07T09:31:37.7143565Z ++ trap_add sccache_epilogue EXIT 2025-09-07T09:31:37.7143804Z ++ trap_add_cmd=sccache_epilogue 2025-09-07T09:31:37.7144019Z ++ shift 2025-09-07T09:31:37.7144193Z ++ for trap_add_name in "$@" 2025-09-07T09:31:37.7151841Z ++++ trap -p EXIT 2025-09-07T09:31:37.7154561Z +++ eval 'extract_trap_cmd ' 2025-09-07T09:31:37.7154848Z ++++ extract_trap_cmd 2025-09-07T09:31:37.7155064Z ++++ printf '%s\n' '' 2025-09-07T09:31:37.7155301Z +++ printf '%s\n' sccache_epilogue 2025-09-07T09:31:37.7157043Z ++ trap -- ' 2025-09-07T09:31:37.7157261Z sccache_epilogue' EXIT 2025-09-07T09:31:37.7157472Z ++ [[ -n 1 ]] 2025-09-07T09:31:37.7157816Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-09-07T09:31:37.7158329Z Skipping sccache server initialization, setting environment variables 2025-09-07T09:31:37.7158720Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:31:37.7158973Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:31:37.7159278Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:31:37.7159659Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:31:37.7160011Z ++ export RUST_LOG=sccache::server=error 2025-09-07T09:31:37.7160460Z ++ RUST_LOG=sccache::server=error 2025-09-07T09:31:37.7160712Z ++ sccache --zero-stats 2025-09-07T09:31:37.8658557Z Statistics zeroed. 2025-09-07T09:31:37.8667050Z ++ which ccache 2025-09-07T09:31:37.8679965Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *rocm* ]] 2025-09-07T09:31:37.8680475Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *s390x* ]] 2025-09-07T09:31:37.8680844Z + [[ -d /var/lib/jenkins/workspace ]] 2025-09-07T09:31:37.8682842Z ++ stat -c %u /var/lib/jenkins/workspace 2025-09-07T09:31:37.8694317Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-09-07T09:31:37.8694571Z + trap_add cleanup_workspace EXIT 2025-09-07T09:31:37.8694824Z + trap_add_cmd=cleanup_workspace 2025-09-07T09:31:37.8695044Z + shift 2025-09-07T09:31:37.8695221Z + for trap_add_name in "$@" 2025-09-07T09:31:37.8702868Z +++ trap -p EXIT 2025-09-07T09:31:37.8704934Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-09-07T09:31:37.8705214Z sccache_epilogue'\'' EXIT' 2025-09-07T09:31:37.8705457Z +++ extract_trap_cmd trap -- ' 2025-09-07T09:31:37.8705689Z sccache_epilogue' EXIT 2025-09-07T09:31:37.8705893Z +++ printf '%s\n' ' 2025-09-07T09:31:37.8706087Z sccache_epilogue' 2025-09-07T09:31:37.8706293Z ++ printf '%s\n' cleanup_workspace 2025-09-07T09:31:37.8708188Z + trap -- ' 2025-09-07T09:31:37.8708375Z sccache_epilogue 2025-09-07T09:31:37.8708577Z cleanup_workspace' EXIT 2025-09-07T09:31:37.8709168Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-09-07T09:31:40.2256025Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-09-07T09:31:40.2279842Z + echo 'Environment variables:' 2025-09-07T09:31:40.2280114Z Environment variables: 2025-09-07T09:31:40.2280568Z + env 2025-09-07T09:31:40.2290402Z GITHUB_WORKSPACE=/home/henry/_work/pytorch/pytorch 2025-09-07T09:31:40.2290778Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:31:40.2291072Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T09:31:40.2293400Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:31:40.2293683Z HOSTNAME=89b2388ff742 2025-09-07T09:31:40.2303284Z GITHUB_PATH=/home/henry/_work/_temp/_runner_file_commands/add_path_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2303766Z GITHUB_ACTION=__run_2 2025-09-07T09:31:40.2303996Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:31:40.2304235Z GITHUB_RUN_NUMBER=662 2025-09-07T09:31:40.2304479Z TEST_CONFIG=inductor_torchbench_perf_cuda_h100 2025-09-07T09:31:40.2304788Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:31:40.2305067Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:31:40.2305335Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:31:40.2305680Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:31:40.2305941Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-09-07T09:31:40.2306205Z GITHUB_REF_TYPE=branch 2025-09-07T09:31:40.2306451Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2306721Z XLA_CUDA= 2025-09-07T09:31:40.2306911Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:31:40.2307248Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:31:40.2307599Z *** 2025-09-07T09:31:40.2307780Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:31:40.2308007Z GITHUB_ACTIONS=true 2025-09-07T09:31:40.2308215Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:31:40.2308492Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:31:40.2308810Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2309109Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2309647Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-h100.yml@refs/heads/main 2025-09-07T09:31:40.2310132Z UCC_HOME=/usr 2025-09-07T09:31:40.2310464Z VERBOSE_TEST_LOGS=False 2025-09-07T09:31:40.2310671Z GITHUB_REF=refs/heads/main 2025-09-07T09:31:40.2310887Z SHARD_NUMBER=8 2025-09-07T09:31:40.2311082Z GITHUB_REF_PROTECTED=true 2025-09-07T09:31:40.2311333Z HOME=/var/lib/jenkins 2025-09-07T09:31:40.2311537Z SCCACHE_SERVER_PORT=5234 2025-09-07T09:31:40.2311783Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:31:40.2312075Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:31:40.2312359Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:31:40.2312635Z USE_SYSTEM_NCCL=1 2025-09-07T09:31:40.2312824Z NUM_TEST_SHARDS=9 2025-09-07T09:31:40.2313003Z UCX_HOME=/usr 2025-09-07T09:31:40.2313357Z GITHUB_STATE=/home/henry/_work/_temp/_runner_file_commands/save_state_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2313899Z JOB_NAME=test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:31:40.2314786Z GITHUB_ENV=/home/henry/_work/_temp/_runner_file_commands/set_env_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2315257Z GITHUB_EVENT_PATH=/home/henry/_work/_temp/_github_workflow/event.json 2025-09-07T09:31:40.2315567Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:31:40.2316476Z 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 2025-09-07T09:31:40.2317385Z GITHUB_RUN_ID=17525296438 2025-09-07T09:31:40.2317570Z INSTALLED_OPENBLAS= 2025-09-07T09:31:40.2317958Z GITHUB_STEP_SUMMARY=/home/henry/_work/_temp/_runner_file_commands/step_summary_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2318402Z GITHUB_ACTOR=pytorchmergebot 2025-09-07T09:31:40.2318611Z PR_NUMBER= 2025-09-07T09:31:40.2318770Z DESIRED_CUDA=12.8.1 2025-09-07T09:31:40.2319179Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:31:40.2319388Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:31:40.2319658Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:31:40.2319916Z TERM=vt100 2025-09-07T09:31:40.2320079Z INSTALLED_VISION=yes 2025-09-07T09:31:40.2320396Z BRANCH=main 2025-09-07T09:31:40.2320568Z SCCACHE_REGION=us-east-1 2025-09-07T09:31:40.2320767Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:31:40.2320976Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:31:40.2321296Z GITHUB_ACTION_PATH=/home/henry/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:31:40.2321671Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:31:40.2321938Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:31:40.2322190Z REENABLED_ISSUES= 2025-09-07T09:31:40.2322363Z DOCS= 2025-09-07T09:31:40.2322512Z SHLVL=1 2025-09-07T09:31:40.2322657Z MAX_JOBS=22 2025-09-07T09:31:40.2322818Z GITHUB_ACTOR_ID=97764156 2025-09-07T09:31:40.2323080Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2323357Z GITHUB_REF_NAME=main 2025-09-07T09:31:40.2323637Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:31:40.2323947Z GITHUB_JOB=test 2025-09-07T09:31:40.2324131Z NO_TEST_TIMEOUT=False 2025-09-07T09:31:40.2324319Z TD_DISTRIBUTED=False 2025-09-07T09:31:40.2324512Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:31:40.2324746Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:31:40.2324954Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:31:40.2325155Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:31:40.2325710Z 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 2025-09-07T09:31:40.2326275Z GITHUB_BASE_REF= 2025-09-07T09:31:40.2326443Z INSTALLED_ACL= 2025-09-07T09:31:40.2326772Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T09:31:40.2327134Z CI=true 2025-09-07T09:31:40.2327303Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:31:40.2327555Z RUST_LOG=sccache::server=error 2025-09-07T09:31:40.2327770Z JOB_ID=49775781863 2025-09-07T09:31:40.2327934Z GITHUB_HEAD_REF= 2025-09-07T09:31:40.2328099Z GITHUB_ACTION_REF= 2025-09-07T09:31:40.2328309Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:31:40.2328565Z TEST_SHOWLOCALS=False 2025-09-07T09:31:40.2328780Z GITHUB_WORKFLOW=inductor-perf-nightly-h100 2025-09-07T09:31:40.2329037Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:31:40.2329429Z GITHUB_OUTPUT=/home/henry/_work/_temp/_runner_file_commands/set_output_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2329824Z NO_TD=False 2025-09-07T09:31:40.2329993Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:31:40.2330334Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:31:40.2330574Z _=/usr/bin/env 2025-09-07T09:31:40.2330815Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-09-07T09:31:40.2567160Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-09-07T09:31:40.2567725Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-09-07T09:31:40.2568491Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-09-07T09:31:40.2569061Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-09-07T09:31:40.2569476Z + BUILD_DIR=build 2025-09-07T09:31:40.2569709Z + BUILD_RENAMED_DIR=build_renamed 2025-09-07T09:31:40.2569989Z + BUILD_BIN_DIR=build/bin 2025-09-07T09:31:40.2570395Z + SHARD_NUMBER=8 2025-09-07T09:31:40.2570629Z + NUM_TEST_SHARDS=9 2025-09-07T09:31:40.2570868Z + export TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:31:40.2571156Z + TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:31:40.2571403Z + export VALGRIND=ON 2025-09-07T09:31:40.2571632Z + VALGRIND=ON 2025-09-07T09:31:40.2571928Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *clang9* ]] 2025-09-07T09:31:40.2572291Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *xpu* ]] 2025-09-07T09:31:40.2572722Z + detect_cuda_arch 2025-09-07T09:31:40.2572969Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T09:31:40.2573271Z + command -v nvidia-smi 2025-09-07T09:31:40.2573481Z /usr/bin/nvidia-smi 2025-09-07T09:31:40.2580076Z ++ nvidia-smi --query-gpu=compute_cap --format=csv 2025-09-07T09:31:40.2581486Z ++ tail -n 1 2025-09-07T09:31:40.2807351Z + TORCH_CUDA_ARCH_LIST=9.0 2025-09-07T09:31:40.2807599Z + export TORCH_CUDA_ARCH_LIST 2025-09-07T09:31:40.2807901Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *s390x* ]] 2025-09-07T09:31:40.2808200Z + [[ 0 == \1 ]] 2025-09-07T09:31:40.2808388Z + [[ True == \1 ]] 2025-09-07T09:31:40.2808652Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *bazel* ]] 2025-09-07T09:31:40.2813268Z ++ realpath build/custom_test_artifacts 2025-09-07T09:31:40.2823797Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-09-07T09:31:40.2824204Z + [[ -n '' ]] 2025-09-07T09:31:40.2824423Z + echo 'Environment variables' 2025-09-07T09:31:40.2824689Z Environment variables 2025-09-07T09:31:40.2824888Z + env 2025-09-07T09:31:40.2833153Z GITHUB_WORKSPACE=/home/henry/_work/pytorch/pytorch 2025-09-07T09:31:40.2833489Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:31:40.2833814Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T09:31:40.2834389Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:31:40.2834649Z HOSTNAME=89b2388ff742 2025-09-07T09:31:40.2835078Z GITHUB_PATH=/home/henry/_work/_temp/_runner_file_commands/add_path_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2835554Z GITHUB_ACTION=__run_2 2025-09-07T09:31:40.2835787Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:31:40.2836047Z GITHUB_RUN_NUMBER=662 2025-09-07T09:31:40.2836292Z TEST_CONFIG=inductor_torchbench_perf_cuda_h100 2025-09-07T09:31:40.2836600Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:31:40.2836881Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:31:40.2837174Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:31:40.2837516Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:31:40.2837786Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-09-07T09:31:40.2838064Z GITHUB_REF_TYPE=branch 2025-09-07T09:31:40.2838292Z TORCH_CUDA_ARCH_LIST=9.0 2025-09-07T09:31:40.2838555Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2838836Z XLA_CUDA= 2025-09-07T09:31:40.2839034Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:31:40.2839393Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:31:40.2839818Z *** 2025-09-07T09:31:40.2840002Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:31:40.2840432Z GITHUB_ACTIONS=true 2025-09-07T09:31:40.2840665Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:31:40.2840958Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:31:40.2841289Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2841605Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2842173Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-h100.yml@refs/heads/main 2025-09-07T09:31:40.2842689Z UCC_HOME=/usr 2025-09-07T09:31:40.2842896Z TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:31:40.2843116Z VERBOSE_TEST_LOGS=False 2025-09-07T09:31:40.2843774Z GITHUB_REF=refs/heads/main 2025-09-07T09:31:40.2843985Z SHARD_NUMBER=8 2025-09-07T09:31:40.2844168Z GITHUB_REF_PROTECTED=true 2025-09-07T09:31:40.2844380Z HOME=/var/lib/jenkins 2025-09-07T09:31:40.2844585Z SCCACHE_SERVER_PORT=5234 2025-09-07T09:31:40.2844869Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:31:40.2845144Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:31:40.2845422Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:31:40.2845690Z USE_SYSTEM_NCCL=1 2025-09-07T09:31:40.2845876Z NUM_TEST_SHARDS=9 2025-09-07T09:31:40.2846060Z UCX_HOME=/usr 2025-09-07T09:31:40.2846444Z GITHUB_STATE=/home/henry/_work/_temp/_runner_file_commands/save_state_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2847032Z JOB_NAME=test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T09:31:40.2847803Z GITHUB_ENV=/home/henry/_work/_temp/_runner_file_commands/set_env_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2848353Z GITHUB_EVENT_PATH=/home/henry/_work/_temp/_github_workflow/event.json 2025-09-07T09:31:40.2848696Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:31:40.2849715Z 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 2025-09-07T09:31:40.2850904Z GITHUB_RUN_ID=17525296438 2025-09-07T09:31:40.2851116Z INSTALLED_OPENBLAS= 2025-09-07T09:31:40.2851544Z GITHUB_STEP_SUMMARY=/home/henry/_work/_temp/_runner_file_commands/step_summary_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2852039Z GITHUB_ACTOR=pytorchmergebot 2025-09-07T09:31:40.2852254Z PR_NUMBER= 2025-09-07T09:31:40.2852430Z DESIRED_CUDA=12.8.1 2025-09-07T09:31:40.2852606Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:31:40.2852786Z VALGRIND=ON 2025-09-07T09:31:40.2852947Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:31:40.2853197Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:31:40.2853456Z TERM=vt100 2025-09-07T09:31:40.2853638Z INSTALLED_VISION=yes 2025-09-07T09:31:40.2853851Z BRANCH=main 2025-09-07T09:31:40.2854017Z SCCACHE_REGION=us-east-1 2025-09-07T09:31:40.2854220Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:31:40.2854420Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:31:40.2854743Z GITHUB_ACTION_PATH=/home/henry/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:31:40.2855109Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:31:40.2855373Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:31:40.2855619Z REENABLED_ISSUES= 2025-09-07T09:31:40.2855778Z DOCS= 2025-09-07T09:31:40.2855930Z SHLVL=1 2025-09-07T09:31:40.2856079Z MAX_JOBS=22 2025-09-07T09:31:40.2856232Z GITHUB_ACTOR_ID=97764156 2025-09-07T09:31:40.2856480Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:31:40.2856750Z GITHUB_REF_NAME=main 2025-09-07T09:31:40.2857026Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:31:40.2857328Z GITHUB_JOB=test 2025-09-07T09:31:40.2857496Z NO_TEST_TIMEOUT=False 2025-09-07T09:31:40.2857676Z TD_DISTRIBUTED=False 2025-09-07T09:31:40.2857870Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:31:40.2858084Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:31:40.2858274Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:31:40.2858465Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:31:40.2859019Z 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 2025-09-07T09:31:40.2859591Z GITHUB_BASE_REF= 2025-09-07T09:31:40.2859752Z INSTALLED_ACL= 2025-09-07T09:31:40.2860087Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T09:31:40.2860577Z CI=true 2025-09-07T09:31:40.2860742Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:31:40.2860986Z RUST_LOG=sccache::server=error 2025-09-07T09:31:40.2861189Z JOB_ID=49775781863 2025-09-07T09:31:40.2861359Z GITHUB_HEAD_REF= 2025-09-07T09:31:40.2861702Z GITHUB_ACTION_REF= 2025-09-07T09:31:40.2861918Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:31:40.2862199Z TEST_SHOWLOCALS=False 2025-09-07T09:31:40.2862409Z GITHUB_WORKFLOW=inductor-perf-nightly-h100 2025-09-07T09:31:40.2862652Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:31:40.2863151Z GITHUB_OUTPUT=/home/henry/_work/_temp/_runner_file_commands/set_output_b164b478-b753-4525-8246-36ebd8691edb 2025-09-07T09:31:40.2863544Z NO_TD=False 2025-09-07T09:31:40.2863713Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:31:40.2863932Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:31:40.2864149Z _=/usr/bin/env 2025-09-07T09:31:40.2864319Z + echo 'Testing pytorch' 2025-09-07T09:31:40.2864506Z Testing pytorch 2025-09-07T09:31:40.2864687Z + export LANG=C.UTF-8 2025-09-07T09:31:40.2864866Z + LANG=C.UTF-8 2025-09-07T09:31:40.2865025Z + PR_NUMBER= 2025-09-07T09:31:40.2865392Z + [[ inductor_torchbench_perf_cuda_h100 == \d\e\f\a\u\l\t ]] 2025-09-07T09:31:40.2865736Z + [[ inductor_torchbench_perf_cuda_h100 == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-09-07T09:31:40.2866067Z + [[ inductor_torchbench_perf_cuda_h100 == \s\l\o\w ]] 2025-09-07T09:31:40.2866396Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *slow-gradcheck* ]] 2025-09-07T09:31:40.2866755Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T09:31:40.2867047Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:31:40.2867293Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:31:40.2867558Z + [[ inductor_torchbench_perf_cuda_h100 == *crossref* ]] 2025-09-07T09:31:40.2867855Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T09:31:40.2868152Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *xpu* ]] 2025-09-07T09:31:40.2868447Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *-bazel-* ]] 2025-09-07T09:31:40.2868715Z + pip_install ninja==1.10.2 2025-09-07T09:31:40.2868983Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:31:40.2869316Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-09-07T09:31:41.4999531Z Collecting ninja==1.10.2 2025-09-07T09:31:41.5399162Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-09-07T09:31:42.7821407Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-09-07T09:31:44.3020756Z Installing collected packages: ninja 2025-09-07T09:31:44.3021156Z Attempting uninstall: ninja 2025-09-07T09:31:44.3029378Z Found existing installation: ninja 1.11.1.3 2025-09-07T09:31:44.3050869Z Uninstalling ninja-1.11.1.3: 2025-09-07T09:31:44.8226293Z Successfully uninstalled ninja-1.11.1.3 2025-09-07T09:31:45.6841412Z Successfully installed ninja-1.10.2 2025-09-07T09:31:45.7559337Z + 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 2025-09-07T09:31:45.7561167Z + 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 2025-09-07T09:31:45.7562079Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *aarch64* ]] 2025-09-07T09:31:45.7562482Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *asan* ]] 2025-09-07T09:31:45.7562853Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-debug* ]] 2025-09-07T09:31:45.7563226Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *-bazel-* ]] 2025-09-07T09:31:45.7563783Z + echo 'We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm90. Expect the assertion to pass' 2025-09-07T09:31:45.7564442Z We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm90. Expect the assertion to pass 2025-09-07T09:31:45.7564859Z + cd test 2025-09-07T09:31:45.7565143Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-09-07T09:31:46.6736362Z /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. 2025-09-07T09:31:46.6738170Z import pynvml # type: ignore[import] 2025-09-07T09:31:47.6899279Z + [[ inductor_torchbench_perf_cuda_h100 == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-09-07T09:31:47.6899762Z + [[ inductor_torchbench_perf_cuda_h100 == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-09-07T09:31:47.6900528Z + [[ inductor_torchbench_perf_cuda_h100 == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-09-07T09:31:47.6903913Z + DYNAMO_BENCHMARK_FLAGS=() 2025-09-07T09:31:47.6904264Z + [[ inductor_torchbench_perf_cuda_h100 == *pr_time_benchmarks* ]] 2025-09-07T09:31:47.6904676Z + [[ inductor_torchbench_perf_cuda_h100 == *dynamo_eager* ]] 2025-09-07T09:31:47.6905054Z + [[ inductor_torchbench_perf_cuda_h100 == *aot_eager* ]] 2025-09-07T09:31:48.1416262Z + [[ inductor_torchbench_perf_cuda_h100 == *aot_inductor* ]] 2025-09-07T09:31:48.1416801Z + [[ inductor_torchbench_perf_cuda_h100 == *max_autotune_inductor* ]] 2025-09-07T09:31:48.1417220Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor* ]] 2025-09-07T09:31:48.1417532Z + [[ inductor_torchbench_perf_cuda_h100 != *perf* ]] 2025-09-07T09:31:48.1417816Z + [[ inductor_torchbench_perf_cuda_h100 == *dynamic* ]] 2025-09-07T09:31:48.1418097Z + [[ inductor_torchbench_perf_cuda_h100 == *cpu* ]] 2025-09-07T09:31:48.1418369Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-09-07T09:31:48.1418657Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *libtorch* ]] 2025-09-07T09:31:48.1418971Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-bazel-* ]] 2025-09-07T09:31:48.1419230Z + cd test 2025-09-07T09:31:48.1419452Z + python -c 'import torch; print(torch.__config__.show())' 2025-09-07T09:31:48.1811596Z /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. 2025-09-07T09:31:48.1812850Z import pynvml # type: ignore[import] 2025-09-07T09:31:49.8394173Z PyTorch built with: 2025-09-07T09:31:49.8394635Z - GCC 9.5 2025-09-07T09:31:49.8395016Z - C++ Version: 201703 2025-09-07T09:31:49.8395714Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:31:49.8396340Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:31:49.8396725Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:31:49.8397018Z - LAPACK is enabled (usually provided by MKL) 2025-09-07T09:31:49.8397302Z - NNPACK is enabled 2025-09-07T09:31:49.8397531Z - CPU capability usage: AVX2 2025-09-07T09:31:49.8397772Z - CUDA Runtime 12.8 2025-09-07T09:31:49.8398071Z - NVCC architecture flags: -gencode;arch=compute_90,code=sm_90 2025-09-07T09:31:49.8398418Z - CuDNN 90.8 2025-09-07T09:31:49.8402742Z - 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, 2025-09-07T09:31:49.8407087Z 2025-09-07T09:31:50.5020783Z + cd test 2025-09-07T09:31:50.5021366Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-09-07T09:31:50.9916427Z /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. 2025-09-07T09:31:50.9917708Z import pynvml # type: ignore[import] 2025-09-07T09:31:51.7199900Z ATen/Parallel: 2025-09-07T09:31:51.7200158Z at::get_num_threads() : 24 2025-09-07T09:31:51.7200554Z at::get_num_interop_threads() : 96 2025-09-07T09:31:51.7200840Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:31:51.7201407Z omp_get_max_threads() : 24 2025-09-07T09:31:51.7201915Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:31:51.7202440Z mkl_get_max_threads() : 24 2025-09-07T09:31:51.7202768Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:31:51.7203150Z std::thread::hardware_concurrency() : 192 2025-09-07T09:31:51.7203418Z Environment variables: 2025-09-07T09:31:51.7203642Z OMP_NUM_THREADS : [not set] 2025-09-07T09:31:51.7203876Z MKL_NUM_THREADS : [not set] 2025-09-07T09:31:51.7204113Z ATen parallel backend: OpenMP 2025-09-07T09:31:51.7204270Z 2025-09-07T09:31:51.9772864Z + [[ inductor_torchbench_perf_cuda_h100 == *numpy_2* ]] 2025-09-07T09:31:51.9773236Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *aarch64* ]] 2025-09-07T09:31:51.9773583Z + [[ inductor_torchbench_perf_cuda_h100 == *backward* ]] 2025-09-07T09:31:51.9773893Z + [[ inductor_torchbench_perf_cuda_h100 == *xla* ]] 2025-09-07T09:31:51.9774199Z + [[ inductor_torchbench_perf_cuda_h100 == *vllm* ]] 2025-09-07T09:31:51.9774520Z + [[ inductor_torchbench_perf_cuda_h100 == *executorch* ]] 2025-09-07T09:31:51.9774890Z + [[ inductor_torchbench_perf_cuda_h100 == \j\i\t\_\l\e\g\a\c\y ]] 2025-09-07T09:31:51.9775273Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *libtorch* ]] 2025-09-07T09:31:51.9775648Z + [[ inductor_torchbench_perf_cuda_h100 == distributed ]] 2025-09-07T09:31:51.9776003Z + [[ inductor_torchbench_perf_cuda_h100 == *operator_benchmark* ]] 2025-09-07T09:31:51.9776401Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_distributed* ]] 2025-09-07T09:31:51.9776792Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-halide* ]] 2025-09-07T09:31:51.9777181Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-triton-cpu* ]] 2025-09-07T09:31:51.9777605Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-micro-benchmark* ]] 2025-09-07T09:31:51.9777993Z + [[ inductor_torchbench_perf_cuda_h100 == *huggingface* ]] 2025-09-07T09:31:51.9778323Z + [[ inductor_torchbench_perf_cuda_h100 == *timm* ]] 2025-09-07T09:31:51.9778642Z + [[ inductor_torchbench_perf_cuda_h100 == cachebench ]] 2025-09-07T09:31:51.9778989Z + [[ inductor_torchbench_perf_cuda_h100 == verify_cachebench ]] 2025-09-07T09:31:51.9779337Z + [[ inductor_torchbench_perf_cuda_h100 == *torchbench* ]] 2025-09-07T09:31:51.9779627Z + install_torchaudio 2025-09-07T09:31:51.9779823Z + local commit 2025-09-07T09:31:51.9780017Z ++ get_pinned_commit audio 2025-09-07T09:31:51.9780560Z ++ cat .github/ci_commit_pins/audio.txt 2025-09-07T09:31:51.9794685Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:31:51.9795282Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio 2025-09-07T09:31:51.9795917Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:31:51.9796337Z + local wheel_dir=dist/audio 2025-09-07T09:31:51.9796528Z + local found_whl=0 2025-09-07T09:31:51.9796725Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:51.9797049Z + [[ -f dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:31:51.9797645Z + found_whl=1 2025-09-07T09:31:51.9797799Z + break 2025-09-07T09:31:51.9797947Z + '[' 1 == 0 ']' 2025-09-07T09:31:51.9798130Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:51.9798474Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:51.9798944Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:31:51.9799253Z + local args 2025-09-07T09:31:51.9799528Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:31:51.9799865Z + for path in "${args[@]}" 2025-09-07T09:31:51.9800329Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:31:51.9800809Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:51.9801495Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:52.3187721Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:52.3249382Z Installing collected packages: torchaudio 2025-09-07T09:31:52.5389939Z Successfully installed torchaudio-2.8.0a0+2e30055 2025-09-07T09:31:52.5735642Z + install_torchvision 2025-09-07T09:31:52.5736057Z + local orig_preload 2025-09-07T09:31:52.5736409Z + local commit 2025-09-07T09:31:52.5743411Z ++ get_pinned_commit vision 2025-09-07T09:31:52.5744210Z ++ cat .github/ci_commit_pins/vision.txt 2025-09-07T09:31:52.5758601Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:31:52.5758913Z + orig_preload= 2025-09-07T09:31:52.5759115Z + '[' -n '' ']' 2025-09-07T09:31:52.5759392Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T09:31:52.5759714Z + export FORCE_CUDA=1 2025-09-07T09:31:52.5759934Z + FORCE_CUDA=1 2025-09-07T09:31:52.5760143Z + export WITH_CUDA=1 2025-09-07T09:31:52.5760517Z + WITH_CUDA=1 2025-09-07T09:31:52.5761030Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-09-07T09:31:52.5761803Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:31:52.5762301Z + local wheel_dir=dist/vision 2025-09-07T09:31:52.5762546Z + local found_whl=0 2025-09-07T09:31:52.5762764Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:52.5763160Z + [[ -f dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:31:52.5763562Z + found_whl=1 2025-09-07T09:31:52.5763748Z + break 2025-09-07T09:31:52.5763915Z + '[' 1 == 0 ']' 2025-09-07T09:31:52.5764120Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:52.5764544Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:52.5765122Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:31:52.5765516Z + local args 2025-09-07T09:31:52.5765863Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:31:52.5766289Z + for path in "${args[@]}" 2025-09-07T09:31:52.5766693Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:31:52.5767238Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:52.5767868Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:52.9201581Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:52.9288846Z Installing collected packages: torchvision 2025-09-07T09:31:53.3675423Z Successfully installed torchvision-0.22.0a0+966da7e 2025-09-07T09:31:53.4035198Z + '[' -n '' ']' 2025-09-07T09:31:53.4035646Z + id=7 2025-09-07T09:31:53.4036081Z + pip_install opencv-python==4.8.0.74 2025-09-07T09:31:53.4036656Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:31:53.4037478Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74 2025-09-07T09:31:53.8565960Z Collecting opencv-python==4.8.0.74 2025-09-07T09:31:53.8950197Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB) 2025-09-07T09:31:53.9056306Z 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) 2025-09-07T09:31:53.9175727Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB) 2025-09-07T09:31:55.1079430Z Installing collected packages: opencv-python 2025-09-07T09:31:55.1079914Z Attempting uninstall: opencv-python 2025-09-07T09:31:55.1091132Z Found existing installation: opencv-python 4.11.0.86 2025-09-07T09:31:55.1176418Z Uninstalling opencv-python-4.11.0.86: 2025-09-07T09:31:55.2998505Z Successfully uninstalled opencv-python-4.11.0.86 2025-09-07T09:31:56.2006845Z Successfully installed opencv-python-4.8.0.74 2025-09-07T09:31:56.2958204Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_torchbench_smoketest_perf* ]] 2025-09-07T09:31:56.2959119Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_torchbench_cpu_smoketest_perf* ]] 2025-09-07T09:31:56.2959903Z + [[ inductor_torchbench_perf_cuda_h100 == *torchbench_gcp_smoketest* ]] 2025-09-07T09:31:56.2961003Z + [[ inductor_torchbench_perf_cuda_h100 != *cpu* ]] 2025-09-07T09:31:56.2961480Z + install_torchrec_and_fbgemm 2025-09-07T09:31:56.2961874Z + local torchrec_commit 2025-09-07T09:31:56.2965866Z ++ get_pinned_commit torchrec 2025-09-07T09:31:56.2966312Z ++ cat .github/ci_commit_pins/torchrec.txt 2025-09-07T09:31:56.2981082Z + torchrec_commit=6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:31:56.2981394Z + local fbgemm_commit 2025-09-07T09:31:56.2986558Z ++ get_pinned_commit fbgemm 2025-09-07T09:31:56.2986845Z ++ cat .github/ci_commit_pins/fbgemm.txt 2025-09-07T09:31:56.3001304Z + fbgemm_commit=de731af65b4f04696e85c729e3282450b51b95fd 2025-09-07T09:31:56.3001802Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T09:31:56.3002132Z + pip_uninstall torchrec-nightly 2025-09-07T09:31:56.3002414Z + pip3 uninstall -y torchrec-nightly 2025-09-07T09:31:56.6506974Z WARNING: Skipping torchrec-nightly as it is not installed. 2025-09-07T09:31:56.6784364Z + pip_uninstall fbgemm-gpu-nightly 2025-09-07T09:31:56.6784920Z + pip3 uninstall -y fbgemm-gpu-nightly 2025-09-07T09:31:57.0255865Z WARNING: Skipping fbgemm-gpu-nightly as it is not installed. 2025-09-07T09:31:57.0510838Z + pip_install setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:31:57.0511330Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:31:57.0511877Z + python3 -m pip install --progress-bar off setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:31:57.3878957Z Requirement already satisfied: setuptools-git-versioning in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (2.1.0) 2025-09-07T09:31:57.3881742Z Requirement already satisfied: scikit-build in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.18.1) 2025-09-07T09:31:57.3884170Z Requirement already satisfied: pyre-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.0.32) 2025-09-07T09:31:57.3895483Z Requirement already satisfied: packaging in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (25.0) 2025-09-07T09:31:57.3898650Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (80.9.0) 2025-09-07T09:31:57.3905093Z 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) 2025-09-07T09:31:57.3946773Z Requirement already satisfied: distro in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (1.9.0) 2025-09-07T09:31:57.3954970Z 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) 2025-09-07T09:31:57.3962298Z Requirement already satisfied: typing-inspect in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (0.9.0) 2025-09-07T09:31:57.3965129Z Requirement already satisfied: typing-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (4.15.0) 2025-09-07T09:31:57.4041361Z 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) 2025-09-07T09:31:58.2964449Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T09:31:58.2965592Z + pip_build_and_install git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 dist/torchrec 2025-09-07T09:31:58.2967596Z + local build_target=git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:31:58.2968284Z + local wheel_dir=dist/torchrec 2025-09-07T09:31:58.2968517Z + local found_whl=0 2025-09-07T09:31:58.2968729Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:58.2969031Z + [[ -f dist/torchrec/torchrec-0.3.2-py3-none-any.whl ]] 2025-09-07T09:31:58.2969325Z + found_whl=1 2025-09-07T09:31:58.2969498Z + break 2025-09-07T09:31:58.2969655Z + '[' 1 == 0 ']' 2025-09-07T09:31:58.2969845Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:58.2970155Z + pip_install_whl dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:31:58.2970855Z + args=('dist/torchrec/torchrec-0.3.2-py3-none-any.whl') 2025-09-07T09:31:58.2971147Z + local args 2025-09-07T09:31:58.2971394Z + [[ dist/torchrec/torchrec-0.3.2-py3-none-any.whl == *\ * ]] 2025-09-07T09:31:58.2971709Z + for path in "${args[@]}" 2025-09-07T09:31:58.2972005Z + echo 'Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl' 2025-09-07T09:31:58.2972397Z Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:31:58.2972853Z + python3 -mpip install --no-index --no-deps dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:31:58.6480971Z Processing ./dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:31:58.6542078Z Installing collected packages: torchrec 2025-09-07T09:31:58.9306375Z Successfully installed torchrec-0.3.2 2025-09-07T09:31:58.9654110Z + pip_build_and_install git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu dist/fbgemm_gpu 2025-09-07T09:31:58.9655169Z + local build_target=git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu 2025-09-07T09:31:58.9655795Z + local wheel_dir=dist/fbgemm_gpu 2025-09-07T09:31:58.9656057Z + local found_whl=0 2025-09-07T09:31:58.9656295Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:58.9656694Z + [[ -f dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:31:58.9657100Z + found_whl=1 2025-09-07T09:31:58.9657324Z + break 2025-09-07T09:31:58.9657519Z + '[' 1 == 0 ']' 2025-09-07T09:31:58.9657748Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:31:58.9658101Z + pip_install_whl dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:58.9658583Z + args=('dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:31:58.9658922Z + local args 2025-09-07T09:31:58.9659202Z + [[ dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:31:58.9659560Z + for path in "${args[@]}" 2025-09-07T09:31:58.9659907Z + echo 'Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:31:58.9660770Z Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:58.9661346Z + python3 -mpip install --no-index --no-deps dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:59.3092331Z Processing ./dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:31:59.4008155Z Installing collected packages: fbgemm-gpu 2025-09-07T09:32:01.1506567Z Successfully installed fbgemm-gpu-0.4.1.post421 2025-09-07T09:32:01.1805231Z + PYTHONPATH=/torchbench 2025-09-07T09:32:01.1805689Z + test_dynamo_benchmark torchbench 7 2025-09-07T09:32:01.1813412Z ++ pwd 2025-09-07T09:32:01.1816583Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:32:01.1816966Z + local suite=torchbench 2025-09-07T09:32:01.1817199Z + shift 2025-09-07T09:32:01.1817390Z + local shard_id=7 2025-09-07T09:32:01.1817595Z + shift 2025-09-07T09:32:01.1817866Z + [[ inductor_torchbench_perf_cuda_h100 == *perf_compare* ]] 2025-09-07T09:32:01.1818229Z + [[ inductor_torchbench_perf_cuda_h100 == *perf* ]] 2025-09-07T09:32:01.1818520Z + [[ inductor_torchbench_perf_cuda_h100 == *b200* ]] 2025-09-07T09:32:01.1818817Z + test_single_dynamo_benchmark dashboard torchbench 7 2025-09-07T09:32:01.1822467Z ++ pwd 2025-09-07T09:32:01.1825735Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:32:01.1826142Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:32:01.1847727Z + local name=dashboard 2025-09-07T09:32:01.1847992Z + shift 2025-09-07T09:32:01.1848212Z + local suite=torchbench 2025-09-07T09:32:01.1848464Z + shift 2025-09-07T09:32:01.1848652Z + local shard_id=7 2025-09-07T09:32:01.1848874Z + shift 2025-09-07T09:32:01.1849063Z + partition_flags=() 2025-09-07T09:32:01.1849287Z + local partition_flags 2025-09-07T09:32:01.1849517Z + [[ -n 9 ]] 2025-09-07T09:32:01.1849708Z + [[ -n 7 ]] 2025-09-07T09:32:01.1850073Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id") 2025-09-07T09:32:01.1850964Z + [[ inductor_torchbench_perf_cuda_h100 == *perf_compare* ]] 2025-09-07T09:32:01.1851337Z + [[ inductor_torchbench_perf_cuda_h100 == *perf* ]] 2025-09-07T09:32:01.1851813Z + test_perf_for_dashboard torchbench --device cuda --total-partitions 9 --partition-id 7 2025-09-07T09:32:01.1853392Z ++ pwd 2025-09-07T09:32:01.1856143Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:32:01.1856654Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:32:01.1873101Z + local suite=torchbench 2025-09-07T09:32:01.1873325Z + shift 2025-09-07T09:32:01.1873581Z + local backend=inductor 2025-09-07T09:32:01.1873787Z + modes=() 2025-09-07T09:32:01.1873974Z + local modes 2025-09-07T09:32:01.1875068Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *training-true* ]] 2025-09-07T09:32:01.1876233Z + modes+=(training) 2025-09-07T09:32:01.1877324Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *inference-true* ]] 2025-09-07T09:32:01.1878467Z + modes+=(inference) 2025-09-07T09:32:01.1878673Z + targets=('accuracy' 'performance') 2025-09-07T09:32:01.1878917Z + local targets 2025-09-07T09:32:01.1879099Z + local device=cuda 2025-09-07T09:32:01.1879315Z + [[ inductor_torchbench_perf_cuda_h100 == *cpu* ]] 2025-09-07T09:32:01.1879626Z + [[ inductor_torchbench_perf_cuda_h100 == *cuda_a10g* ]] 2025-09-07T09:32:01.1879942Z + [[ inductor_torchbench_perf_cuda_h100 == *h100* ]] 2025-09-07T09:32:01.1880331Z + device=cuda_h100 2025-09-07T09:32:01.1880525Z + for mode in "${modes[@]}" 2025-09-07T09:32:01.1880751Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:32:01.1881000Z + [[ training == \t\r\a\i\n\i\n\g ]] 2025-09-07T09:32:01.1881226Z + dtype=amp 2025-09-07T09:32:01.1881406Z + for target in "${targets[@]}" 2025-09-07T09:32:01.1881628Z + target_flag=('--accuracy') 2025-09-07T09:32:01.1881842Z + local target_flag 2025-09-07T09:32:01.1882043Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:32:01.1882293Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T09:32:01.1882550Z + target_flag+=(--no-translation-validation) 2025-09-07T09:32:01.1883924Z + [[ 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* ]] 2025-09-07T09:32:01.1885795Z + [[ 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* ]] 2025-09-07T09:32:01.1887799Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:32:01.6724459Z /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. 2025-09-07T09:32:01.6725484Z import pynvml # type: ignore[import] 2025-09-07T09:32:05.4829448Z /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. 2025-09-07T09:32:05.4835305Z import pynvml # type: ignore[import] 2025-09-07T09:32:07.9377871Z 2025-09-07T09:32:08.3352773Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/resnet50-0676ba61.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/resnet50-0676ba61.pth 2025-09-07T09:32:08.3527714Z 2025-09-07T09:32:08.3527724Z 2025-09-07T09:32:08.4531731Z 0% 0.00/97.8M [00:00 will be ignored 2025-09-07T09:32:54.9843983Z pass 2025-09-07T09:32:59.5403600Z /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. 2025-09-07T09:32:59.5406141Z import pynvml # type: ignore[import] 2025-09-07T09:33:01.9932631Z 2025-09-07T09:33:04.0706313Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:33:04.0706830Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:33:04.0707340Z cuda train resnet50_quantized_qat 2025-09-07T09:33:04.0708128Z Traceback (most recent call last): 2025-09-07T09:33:04.0708966Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:33:04.0709807Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:33:04.0711088Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:33:04.0712059Z pred = mod(*cloned_inputs) 2025-09-07T09:33:04.0712909Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:33:04.0713864Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:33:04.0714739Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:33:04.0716199Z raise e 2025-09-07T09:33:04.0716919Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:33:04.0717524Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:33:04.0718189Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:33:04.0718752Z return self._call_impl(*args, **kwargs) 2025-09-07T09:33:04.0719277Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:33:04.0719805Z return forward_call(*args, **kwargs) 2025-09-07T09:33:04.0720096Z File ".3", line 167, in forward 2025-09-07T09:33:04.0720896Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:33:04.0721601Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:33:04.0722179Z return self._call_impl(*args, **kwargs) 2025-09-07T09:33:04.0722719Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:33:04.0723250Z return forward_call(*args, **kwargs) 2025-09-07T09:33:04.0723800Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:33:04.0724383Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:33:04.0724737Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:33:04.0724974Z 2025-09-07T09:33:04.0725168Z The above exception was the direct cause of the following exception: 2025-09-07T09:33:04.0725446Z 2025-09-07T09:33:04.0725551Z Traceback (most recent call last): 2025-09-07T09:33:04.0725961Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:33:04.0726383Z ) = runner.load_model( 2025-09-07T09:33:04.0726803Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:33:04.0727287Z self.validate_model(model, example_inputs) 2025-09-07T09:33:04.0727675Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:33:04.0728075Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:33:04.0728339Z RuntimeError: Eager run failed 2025-09-07T09:33:04.0728473Z 2025-09-07T09:33:04.0728546Z eager_fail_to_run 2025-09-07T09:33:05.6627983Z /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. 2025-09-07T09:33:05.6629143Z import pynvml # type: ignore[import] 2025-09-07T09:33:08.1111275Z 2025-09-07T09:33:08.4926899Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/resnext50_32x4d-7cdf4587.pth 2025-09-07T09:33:08.5091348Z 2025-09-07T09:33:08.5091692Z 2025-09-07T09:33:08.6094003Z 0% 0.00/95.8M [00:00 will be ignored 2025-09-07T09:33:55.2290982Z pass 2025-09-07T09:33:59.8244334Z /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. 2025-09-07T09:33:59.8246177Z import pynvml # type: ignore[import] 2025-09-07T09:34:02.3147360Z 2025-09-07T09:34:09.7956895Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:34:09.7957232Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:34:09.7957515Z cuda train sam 2025-09-07T09:34:09.7968298Z Traceback (most recent call last): 2025-09-07T09:34:09.7969315Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:34:09.7969846Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:34:09.7970777Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:34:09.7971320Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:34:09.7971803Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:34:09.7972254Z torch.autograd.backward( 2025-09-07T09:34:09.7972715Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:34:09.7973183Z _engine_run_backward( 2025-09-07T09:34:09.7973657Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:34:09.7974366Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:34:09.7974951Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:34:09.7975266Z 2025-09-07T09:34:09.7975454Z The above exception was the direct cause of the following exception: 2025-09-07T09:34:09.7975722Z 2025-09-07T09:34:09.7975813Z Traceback (most recent call last): 2025-09-07T09:34:09.7976196Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:34:09.7976583Z ) = runner.load_model( 2025-09-07T09:34:09.7976983Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:34:09.7977430Z self.validate_model(model, example_inputs) 2025-09-07T09:34:09.7977876Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:34:09.7985691Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:34:09.7986041Z RuntimeError: Eager run failed 2025-09-07T09:34:09.7986196Z 2025-09-07T09:34:09.7986269Z eager_fail_to_run 2025-09-07T09:34:11.4646980Z /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. 2025-09-07T09:34:11.4648145Z import pynvml # type: ignore[import] 2025-09-07T09:34:13.9298285Z 2025-09-07T09:34:14.1166448Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/shufflenetv2_x1-5666bf0f80.pth 2025-09-07T09:34:14.1339218Z 2025-09-07T09:34:14.1339509Z 2025-09-07T09:34:14.1687430Z 0% 0.00/8.79M [00:00 will be ignored 2025-09-07T09:35:05.0277541Z pass 2025-09-07T09:35:07.8964305Z /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. 2025-09-07T09:35:07.8965439Z import pynvml # type: ignore[import] 2025-09-07T09:35:10.3629322Z 2025-09-07T09:35:11.7696471Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:11.7696777Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:35:11.7697054Z cuda train speech_transformer 2025-09-07T09:36:09.0420131Z pass 2025-09-07T09:36:12.5937942Z /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. 2025-09-07T09:36:12.5940405Z import pynvml # type: ignore[import] 2025-09-07T09:36:15.2542525Z 2025-09-07T09:36:15.4815419Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/squeezenet1_1-b8a52dc0.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/squeezenet1_1-b8a52dc0.pth 2025-09-07T09:36:15.5003179Z 2025-09-07T09:36:15.5003366Z 2025-09-07T09:36:15.5195962Z 0% 0.00/4.73M [00:00 will be ignored 2025-09-07T09:37:29.8901264Z pass 2025-09-07T09:37:34.4725404Z /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. 2025-09-07T09:37:34.4726835Z import pynvml # type: ignore[import] 2025-09-07T09:37:37.0597407Z 2025-09-07T09:37:39.2099329Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:37:39.2099872Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:37:39.2101021Z cuda train resnet50_quantized_qat 2025-09-07T09:37:39.2101566Z Traceback (most recent call last): 2025-09-07T09:37:39.2102385Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:37:39.2103409Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:37:39.2104359Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:37:39.2105258Z pred = mod(*cloned_inputs) 2025-09-07T09:37:39.2106045Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:37:39.2106540Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:37:39.2107000Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:37:39.2107428Z raise e 2025-09-07T09:37:39.2107794Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:37:39.2108311Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:37:39.2108880Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:37:39.2109367Z return self._call_impl(*args, **kwargs) 2025-09-07T09:37:39.2109808Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:37:39.2110429Z return forward_call(*args, **kwargs) 2025-09-07T09:37:39.2110694Z File ".3", line 167, in forward 2025-09-07T09:37:39.2111049Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:37:39.2111646Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:37:39.2112139Z return self._call_impl(*args, **kwargs) 2025-09-07T09:37:39.2112594Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:37:39.2113048Z return forward_call(*args, **kwargs) 2025-09-07T09:37:39.2113521Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:37:39.2114023Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:37:39.2114330Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:37:39.2114540Z 2025-09-07T09:37:39.2114705Z The above exception was the direct cause of the following exception: 2025-09-07T09:37:39.2114945Z 2025-09-07T09:37:39.2317742Z Traceback (most recent call last): 2025-09-07T09:37:39.2318188Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:37:39.2318615Z ) = runner.load_model( 2025-09-07T09:37:39.2319053Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:37:39.2319545Z self.validate_model(model, example_inputs) 2025-09-07T09:37:39.2320024Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:37:39.2320697Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:37:39.2321003Z RuntimeError: Eager run failed 2025-09-07T09:37:39.2321171Z 2025-09-07T09:37:39.2321249Z eager_fail_to_run 2025-09-07T09:37:41.1582813Z /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. 2025-09-07T09:37:41.1584156Z import pynvml # type: ignore[import] 2025-09-07T09:37:43.5979203Z 2025-09-07T09:37:45.9508293Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:37:45.9508631Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:37:45.9508916Z cuda train resnext50_32x4d 2025-09-07T09:38:08.3514689Z W0907 09:38:08.350000 8978 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:38:27.6222916Z pass 2025-09-07T09:38:32.0437114Z /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. 2025-09-07T09:38:32.0441658Z import pynvml # type: ignore[import] 2025-09-07T09:38:34.6831401Z 2025-09-07T09:38:42.7289219Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:42.7289611Z loading model: 0it [00:08, ?it/s] 2025-09-07T09:38:42.7289911Z cuda train sam 2025-09-07T09:38:42.7300783Z Traceback (most recent call last): 2025-09-07T09:38:42.7301234Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:38:42.7301685Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:38:42.7302174Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:38:42.7302746Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:38:42.7303165Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:38:42.7303590Z torch.autograd.backward( 2025-09-07T09:38:42.7304047Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:38:42.7304493Z _engine_run_backward( 2025-09-07T09:38:42.7304939Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:38:42.7305595Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:38:42.7306136Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:38:42.7306425Z 2025-09-07T09:38:42.7306586Z The above exception was the direct cause of the following exception: 2025-09-07T09:38:42.7306832Z 2025-09-07T09:38:42.7306925Z Traceback (most recent call last): 2025-09-07T09:38:42.7307284Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:38:42.7307659Z ) = runner.load_model( 2025-09-07T09:38:42.7308028Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:38:42.7308454Z self.validate_model(model, example_inputs) 2025-09-07T09:38:42.7308874Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:38:42.7309791Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:38:42.7310054Z RuntimeError: Eager run failed 2025-09-07T09:38:42.7310409Z 2025-09-07T09:38:42.7310486Z eager_fail_to_run 2025-09-07T09:38:44.4819097Z /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. 2025-09-07T09:38:44.4820697Z import pynvml # type: ignore[import] 2025-09-07T09:38:47.3429641Z 2025-09-07T09:38:48.8519771Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:48.8520124Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:38:48.8520809Z cuda train shufflenet_v2_x1_0 2025-09-07T09:39:19.2113751Z pass 2025-09-07T09:39:22.9103090Z /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. 2025-09-07T09:39:22.9104191Z import pynvml # type: ignore[import] 2025-09-07T09:39:25.5951861Z 2025-09-07T09:39:26.6866795Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:26.6867184Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:39:26.6867505Z cuda train soft_actor_critic 2025-09-07T09:39:30.6424531Z W0907 09:39:30.641000 9594 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:39:31.8201619Z pass 2025-09-07T09:39:34.5153652Z /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. 2025-09-07T09:39:34.5155267Z import pynvml # type: ignore[import] 2025-09-07T09:39:37.1441563Z 2025-09-07T09:39:38.6919815Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:38.6920759Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:39:38.6921120Z cuda train speech_transformer 2025-09-07T09:39:49.2864078Z W0907 09:39:49.285000 9804 site-packages/torch/_inductor/utils.py:2298] [9/0_1] DeviceCopy in input program 2025-09-07T09:39:50.8098293Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8098919Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8099407Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8099892Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8100893Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8101461Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8101949Z cudagraph partition due to non gpu ops 2025-09-07T09:39:50.8102452Z cudagraph partition due to DeviceCopy ops 2025-09-07T09:39:50.8514355Z cudagraph partition into 2 partitions 2025-09-07T09:40:12.5389733Z W0907 09:40:12.538000 9804 site-packages/torch/_inductor/utils.py:2298] [15/0_1] DeviceCopy in input program 2025-09-07T09:40:14.3523630Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3524174Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3524626Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3525048Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3525462Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3525866Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3526303Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3526739Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3527161Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3527588Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3528042Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3528462Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3529418Z cudagraph partition due to non gpu ops 2025-09-07T09:40:14.3529962Z cudagraph partition due to DeviceCopy ops 2025-09-07T09:40:14.4180953Z cudagraph partition into 2 partitions 2025-09-07T09:40:18.3652659Z W0907 09:40:18.364000 9804 site-packages/torch/_inductor/utils.py:2298] [15/0_1] DeviceCopy in input program 2025-09-07T09:40:21.2286833Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2287190Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2287462Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2287728Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2287985Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2288241Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2288509Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2288767Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2289430Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2289716Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2289990Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2290550Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2290817Z cudagraph partition due to non gpu ops 2025-09-07T09:40:21.2291085Z cudagraph partition due to DeviceCopy ops 2025-09-07T09:40:21.8001440Z cudagraph partition into 2 partitions 2025-09-07T09:40:24.6991345Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/torchbench/torchbenchmark/models/speech_transformer/speech_transformer/transformer/decoder.py", line 126, in torch_dynamo_resume_in_forward_at_120 2025-09-07T09:40:24.6992634Z self.tgt_word_emb(ys_in_pad) * self.x_logit_scale 2025-09-07T09:40:24.6992927Z 2025-09-07T09:40:24.6992932Z 2025-09-07T09:40:25.2977344Z Run failed with return code: -11 2025-09-07T09:40:25.2977654Z Output: None 2025-09-07T09:40:25.2977862Z Error: None 2025-09-07T09:40:25.7929812Z /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. 2025-09-07T09:40:25.7932301Z import pynvml # type: ignore[import] 2025-09-07T09:40:28.2898768Z 2025-09-07T09:40:29.6440392Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:40:29.6440757Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:40:29.6441042Z cuda train squeezenet1_1 2025-09-07T09:40:45.3693388Z pass 2025-09-07T09:40:47.9038138Z accuracy pass_rate=71.43% 2025-09-07T09:40:47.9049281Z calls_captured gmean=0.00x mean=345.857x 2025-09-07T09:40:47.9052923Z unique_graphs gmean=0.00x mean=2.000x 2025-09-07T09:40:47.9056356Z graph_breaks gmean=0.00x mean=4.571x 2025-09-07T09:40:47.9059778Z unique_graph_breaks gmean=0.00x mean=3.571x 2025-09-07T09:40:47.9063445Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:40:47.9066582Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:40:47.9069786Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:40:47.9071302Z compilation_latency mean=18.381 seconds 2025-09-07T09:40:48.7707901Z + [[ 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* ]] 2025-09-07T09:40:48.7711495Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:40:49.2699268Z /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. 2025-09-07T09:40:49.2701091Z import pynvml # type: ignore[import] 2025-09-07T09:40:53.1567700Z /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. 2025-09-07T09:40:53.1568969Z import pynvml # type: ignore[import] 2025-09-07T09:40:55.6134178Z 2025-09-07T09:40:57.7579491Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:40:57.7579857Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:40:57.7580154Z cuda train resnet50 2025-09-07T09:41:06.3651916Z W0907 09:41:06.364000 11569 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:41:09.9404370Z pass 2025-09-07T09:41:12.9080809Z /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. 2025-09-07T09:41:12.9082034Z import pynvml # type: ignore[import] 2025-09-07T09:41:15.4102482Z 2025-09-07T09:41:17.5126602Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:41:17.5127146Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:41:17.5127647Z cuda train resnet50_quantized_qat 2025-09-07T09:41:17.5128205Z Traceback (most recent call last): 2025-09-07T09:41:17.5129008Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:41:17.5129909Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:41:17.5131279Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:41:17.5132212Z pred = mod(*cloned_inputs) 2025-09-07T09:41:17.5133102Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:41:17.5134035Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:41:17.5134909Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:41:17.5135697Z raise e 2025-09-07T09:41:17.5136398Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:41:17.5137422Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:41:17.5138612Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:41:17.5139135Z return self._call_impl(*args, **kwargs) 2025-09-07T09:41:17.5139624Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:41:17.5140130Z return forward_call(*args, **kwargs) 2025-09-07T09:41:17.5140532Z File ".3", line 167, in forward 2025-09-07T09:41:17.5140905Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:41:17.5141525Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:41:17.5142041Z return self._call_impl(*args, **kwargs) 2025-09-07T09:41:17.5142537Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:41:17.5143105Z return forward_call(*args, **kwargs) 2025-09-07T09:41:17.5143613Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:41:17.5144161Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:41:17.5144498Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:41:17.5145116Z 2025-09-07T09:41:17.5145299Z The above exception was the direct cause of the following exception: 2025-09-07T09:41:17.5145571Z 2025-09-07T09:41:17.5145668Z Traceback (most recent call last): 2025-09-07T09:41:17.5146048Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:41:17.5146452Z ) = runner.load_model( 2025-09-07T09:41:17.5146853Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:41:17.5147315Z self.validate_model(model, example_inputs) 2025-09-07T09:41:17.5147764Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:41:17.5148224Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:41:17.5148510Z RuntimeError: Eager run failed 2025-09-07T09:41:17.5148662Z 2025-09-07T09:41:17.5148930Z eager_fail_to_run 2025-09-07T09:41:19.1847203Z /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. 2025-09-07T09:41:19.1848507Z import pynvml # type: ignore[import] 2025-09-07T09:41:21.6515484Z 2025-09-07T09:41:24.0768717Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:41:24.0769161Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:41:24.0769613Z cuda train resnext50_32x4d 2025-09-07T09:41:31.7184228Z W0907 09:41:31.717000 11923 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:41:35.2228813Z pass 2025-09-07T09:41:38.1813169Z /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. 2025-09-07T09:41:38.1815470Z import pynvml # type: ignore[import] 2025-09-07T09:41:40.6916562Z 2025-09-07T09:41:48.4660016Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:41:48.4660826Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:41:48.4661079Z cuda train sam 2025-09-07T09:41:48.4671741Z Traceback (most recent call last): 2025-09-07T09:41:48.4672210Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:41:48.4672671Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:41:48.4673301Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:41:48.4674141Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:41:48.4674875Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:41:48.4675513Z torch.autograd.backward( 2025-09-07T09:41:48.4675966Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:41:48.4676548Z _engine_run_backward( 2025-09-07T09:41:48.4677283Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:41:48.4678130Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:41:48.4678673Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:41:48.4679073Z 2025-09-07T09:41:48.4679344Z The above exception was the direct cause of the following exception: 2025-09-07T09:41:48.4679754Z 2025-09-07T09:41:48.4679893Z Traceback (most recent call last): 2025-09-07T09:41:48.4680502Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:41:48.4680857Z ) = runner.load_model( 2025-09-07T09:41:48.4681810Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:41:48.4682530Z self.validate_model(model, example_inputs) 2025-09-07T09:41:48.4683169Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:41:48.4683574Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:41:48.4683825Z RuntimeError: Eager run failed 2025-09-07T09:41:48.4683969Z 2025-09-07T09:41:48.4684033Z eager_fail_to_run 2025-09-07T09:41:50.3623679Z /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. 2025-09-07T09:41:50.3624915Z import pynvml # type: ignore[import] 2025-09-07T09:41:52.9523737Z 2025-09-07T09:41:54.4869400Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:41:54.4869740Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:41:54.4870431Z cuda train shufflenet_v2_x1_0 2025-09-07T09:42:04.1842999Z pass 2025-09-07T09:42:07.0165793Z /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. 2025-09-07T09:42:07.0166869Z import pynvml # type: ignore[import] 2025-09-07T09:42:09.4944756Z 2025-09-07T09:42:10.6518664Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:42:10.6519032Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:42:10.6519330Z cuda train soft_actor_critic 2025-09-07T09:42:14.9858117Z W0907 09:42:14.985000 12815 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:42:15.3205167Z pass 2025-09-07T09:42:18.7540017Z /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. 2025-09-07T09:42:18.7541259Z import pynvml # type: ignore[import] 2025-09-07T09:42:21.2696089Z 2025-09-07T09:42:22.7073613Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:42:22.7073944Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:42:22.7075087Z Traceback (most recent call last): 2025-09-07T09:42:22.7075575Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 508, in 2025-09-07T09:42:22.7076543Z torchbench_main() 2025-09-07T09:42:22.7076989Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T09:42:22.7077529Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T09:42:22.7077960Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T09:42:22.7081231Z process_entry(0, runner, original_dir, args) 2025-09-07T09:42:22.7081747Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T09:42:22.7084383Z result = run(runner, args, original_dir) 2025-09-07T09:42:22.7084780Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4251, in run 2025-09-07T09:42:22.7087957Z assert marked, f"nothing in example_inputs had a dim with {batch_size}" 2025-09-07T09:42:22.7088339Z AssertionError: nothing in example_inputs had a dim with 32 2025-09-07T09:42:23.6340714Z Run failed with return code: 1 2025-09-07T09:42:23.6341209Z Output: None 2025-09-07T09:42:23.6341537Z Error: None 2025-09-07T09:42:24.1764365Z /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. 2025-09-07T09:42:24.1766302Z import pynvml # type: ignore[import] 2025-09-07T09:42:26.8027932Z 2025-09-07T09:42:28.1734887Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:42:28.1735267Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:42:28.1735578Z cuda train squeezenet1_1 2025-09-07T09:42:33.7435658Z pass 2025-09-07T09:42:36.1256492Z accuracy pass_rate=71.43% 2025-09-07T09:42:36.1268607Z calls_captured gmean=0.00x mean=345.857x 2025-09-07T09:42:36.1272212Z unique_graphs gmean=0.00x mean=2.000x 2025-09-07T09:42:36.1275361Z graph_breaks gmean=0.00x mean=4.571x 2025-09-07T09:42:36.1278589Z unique_graph_breaks gmean=0.00x mean=3.571x 2025-09-07T09:42:36.1282089Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:42:36.1285286Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:42:36.1288810Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:42:36.1289609Z compilation_latency mean=5.235 seconds 2025-09-07T09:42:36.9977202Z + [[ 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* ]] 2025-09-07T09:42:36.9978512Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T09:42:36.9979838Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:42:37.5345645Z /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. 2025-09-07T09:42:37.5347476Z import pynvml # type: ignore[import] 2025-09-07T09:42:41.2413792Z /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. 2025-09-07T09:42:41.2415349Z import pynvml # type: ignore[import] 2025-09-07T09:42:43.7362648Z 2025-09-07T09:42:45.9822112Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:42:45.9822483Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:42:45.9822867Z cuda train resnet50 2025-09-07T09:43:35.5030783Z W0907 09:43:35.502000 13476 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:44:05.7747513Z pass 2025-09-07T09:44:10.8081368Z /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. 2025-09-07T09:44:10.8084806Z import pynvml # type: ignore[import] 2025-09-07T09:44:13.2982459Z 2025-09-07T09:44:15.3895767Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:44:15.3896116Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:44:15.3896418Z cuda train resnet50_quantized_qat 2025-09-07T09:44:15.3896761Z Traceback (most recent call last): 2025-09-07T09:44:15.3897247Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:44:15.3897782Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:44:15.3898367Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:44:15.3898977Z pred = mod(*cloned_inputs) 2025-09-07T09:44:15.3899564Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:44:15.3900768Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:44:15.3901274Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:44:15.3901716Z raise e 2025-09-07T09:44:15.3902101Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:44:15.3902756Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:44:15.3903367Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:44:15.3903884Z return self._call_impl(*args, **kwargs) 2025-09-07T09:44:15.3904607Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:44:15.3905111Z return forward_call(*args, **kwargs) 2025-09-07T09:44:15.3905390Z File ".3", line 167, in forward 2025-09-07T09:44:15.3905769Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:44:15.3906387Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:44:15.3906910Z return self._call_impl(*args, **kwargs) 2025-09-07T09:44:15.3907389Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:44:15.3907870Z return forward_call(*args, **kwargs) 2025-09-07T09:44:15.3908371Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:44:15.3908903Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:44:15.3909237Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:44:15.3909465Z 2025-09-07T09:44:15.3909640Z The above exception was the direct cause of the following exception: 2025-09-07T09:44:15.3909899Z 2025-09-07T09:44:15.3909991Z Traceback (most recent call last): 2025-09-07T09:44:15.3910492Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:44:15.3910843Z ) = runner.load_model( 2025-09-07T09:44:15.3911202Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:44:15.3911605Z self.validate_model(model, example_inputs) 2025-09-07T09:44:15.3911998Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:44:15.3912392Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:44:15.3912649Z RuntimeError: Eager run failed 2025-09-07T09:44:15.3912785Z 2025-09-07T09:44:15.3912857Z eager_fail_to_run 2025-09-07T09:44:16.9745038Z /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. 2025-09-07T09:44:16.9746091Z import pynvml # type: ignore[import] 2025-09-07T09:44:19.4297363Z 2025-09-07T09:44:21.5517031Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:44:21.5517373Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:44:21.5517656Z cuda train resnext50_32x4d 2025-09-07T09:45:03.6768952Z W0907 09:45:03.675000 14691 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:45:38.0458811Z pass 2025-09-07T09:45:42.8907520Z /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. 2025-09-07T09:45:42.8910957Z import pynvml # type: ignore[import] 2025-09-07T09:45:45.6332139Z 2025-09-07T09:45:53.3921369Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:45:53.3921774Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:45:53.3922090Z cuda train sam 2025-09-07T09:45:53.3932443Z Traceback (most recent call last): 2025-09-07T09:45:53.3932936Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:45:53.3933482Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:45:53.3934050Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:45:53.3934605Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:45:53.3935106Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:45:53.3936070Z torch.autograd.backward( 2025-09-07T09:45:53.3936581Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:45:53.3937117Z _engine_run_backward( 2025-09-07T09:45:53.3937629Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:45:53.3938383Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:45:53.3939018Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:45:53.3939359Z 2025-09-07T09:45:53.3939545Z The above exception was the direct cause of the following exception: 2025-09-07T09:45:53.3939827Z 2025-09-07T09:45:53.3939930Z Traceback (most recent call last): 2025-09-07T09:45:53.3940534Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:45:53.3940956Z ) = runner.load_model( 2025-09-07T09:45:53.3941386Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:45:53.3941879Z self.validate_model(model, example_inputs) 2025-09-07T09:45:53.3942354Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:45:53.3942928Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:45:53.3943231Z RuntimeError: Eager run failed 2025-09-07T09:45:53.3943396Z 2025-09-07T09:45:53.3943474Z eager_fail_to_run 2025-09-07T09:45:55.1672297Z /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. 2025-09-07T09:45:55.1673434Z import pynvml # type: ignore[import] 2025-09-07T09:45:57.8037200Z 2025-09-07T09:45:59.4305763Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:45:59.4306270Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:45:59.4306658Z cuda train shufflenet_v2_x1_0 2025-09-07T09:46:56.3948078Z pass 2025-09-07T09:47:00.5384281Z /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. 2025-09-07T09:47:00.5385323Z import pynvml # type: ignore[import] 2025-09-07T09:47:03.1219844Z 2025-09-07T09:47:04.2118586Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:04.2119008Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:47:04.2119315Z cuda train soft_actor_critic 2025-09-07T09:47:14.4535297Z W0907 09:47:14.452000 16543 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:47:17.1831659Z pass 2025-09-07T09:47:20.0997171Z /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. 2025-09-07T09:47:20.0999022Z import pynvml # type: ignore[import] 2025-09-07T09:47:22.7177661Z 2025-09-07T09:47:24.4186269Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:24.4186754Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:47:24.4187201Z cuda train speech_transformer 2025-09-07T09:48:52.1492269Z pass 2025-09-07T09:48:56.6404000Z /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. 2025-09-07T09:48:56.6408275Z import pynvml # type: ignore[import] 2025-09-07T09:48:59.4006749Z 2025-09-07T09:49:00.8680096Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:49:00.8680793Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:49:00.8681081Z cuda train squeezenet1_1 2025-09-07T09:49:24.3907119Z pass 2025-09-07T09:49:27.2006262Z accuracy pass_rate=75.00% 2025-09-07T09:49:27.2011266Z calls_captured gmean=0.00x mean=485.125x 2025-09-07T09:49:27.2014772Z unique_graphs gmean=0.00x mean=3.000x 2025-09-07T09:49:27.2017984Z graph_breaks gmean=0.00x mean=6.000x 2025-09-07T09:49:27.2028028Z unique_graph_breaks gmean=0.00x mean=4.000x 2025-09-07T09:49:27.2031608Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:49:27.2034840Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:49:27.2037803Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:49:27.2038826Z compilation_latency mean=41.310 seconds 2025-09-07T09:49:28.1000452Z + [[ 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* ]] 2025-09-07T09:49:28.1001860Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:49:28.1003124Z + [[ 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* ]] 2025-09-07T09:49:28.1004366Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:49:28.1005549Z + [[ 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* ]] 2025-09-07T09:49:28.1006729Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:49:28.1007901Z + [[ 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* ]] 2025-09-07T09:49:28.1009078Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T09:49:28.1010458Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:49:28.6251202Z /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. 2025-09-07T09:49:28.6252290Z import pynvml # type: ignore[import] 2025-09-07T09:49:32.6671911Z /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. 2025-09-07T09:49:32.9699956Z import pynvml # type: ignore[import] 2025-09-07T09:49:35.5679528Z 2025-09-07T09:49:37.7202936Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:49:37.7203450Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:49:37.7203869Z cuda train resnet50 2025-09-07T09:49:57.2921229Z Autotune Choices Stats: 2025-09-07T09:49:57.2922325Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_60", "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=4, num_warps=8", "best_time": 0.010080000385642052, "best_triton_pos": 0} 2025-09-07T09:49:57.3345417Z AUTOTUNE mm(12544x64, 64x256) 2025-09-07T09:49:57.3345686Z strides: [64, 1], [1, 64] 2025-09-07T09:49:57.3346434Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:57.3347120Z triton_mm_60 0.0101 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 2025-09-07T09:49:57.3348203Z triton_mm_63 0.0120 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=3, num_warps=4 2025-09-07T09:49:57.3349243Z triton_mm_54 0.0122 ms 82.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:49:57.3350200Z triton_mm_55 0.0162 ms 62.1% 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 2025-09-07T09:49:57.3351321Z triton_mm_67 0.0163 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=3, num_warps=4 2025-09-07T09:49:57.3352289Z triton_mm_62 0.0167 ms 60.3% 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=4, num_warps=4 2025-09-07T09:49:57.3353260Z triton_mm_65 0.0173 ms 58.2% 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 2025-09-07T09:49:57.3354226Z triton_mm_57 0.0174 ms 57.8% 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 2025-09-07T09:49:57.3355177Z triton_mm_59 0.0179 ms 56.5% 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 2025-09-07T09:49:57.3356134Z triton_mm_66 0.0186 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=3, num_warps=4 2025-09-07T09:49:57.3356981Z SingleProcess AUTOTUNE benchmarking takes 0.3603 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T09:49:59.2661547Z Autotune Choices Stats: 2025-09-07T09:49:59.2662744Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_168", "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": 0.011136000044643879, "best_triton_pos": 0} 2025-09-07T09:49:59.3038019Z AUTOTUNE mm(12544x256, 256x128) 2025-09-07T09:49:59.3038328Z strides: [256, 1], [1, 256] 2025-09-07T09:49:59.3038605Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:59.3039439Z triton_mm_168 0.0111 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 2025-09-07T09:49:59.3040925Z triton_mm_164 0.0115 ms 97.2% 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 2025-09-07T09:49:59.3042700Z triton_mm_175 0.0115 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=5, num_warps=8 2025-09-07T09:49:59.3043911Z triton_mm_174 0.0118 ms 94.3% 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 2025-09-07T09:49:59.3045110Z triton_mm_166 0.0118 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 2025-09-07T09:49:59.3046572Z triton_mm_167 0.0123 ms 90.4% 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 2025-09-07T09:49:59.3047791Z triton_mm_170 0.0126 ms 88.5% 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 2025-09-07T09:49:59.3049034Z triton_mm_173 0.0128 ms 87.2% 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 2025-09-07T09:49:59.3050122Z triton_mm_163 0.0141 ms 78.7% 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 2025-09-07T09:49:59.3051358Z triton_mm_165 0.0144 ms 77.5% 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 2025-09-07T09:49:59.3052284Z SingleProcess AUTOTUNE benchmarking takes 0.6514 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:50:00.1292032Z Autotune Choices Stats: 2025-09-07T09:50:00.1293070Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_246", "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": 0.008383999578654766, "best_triton_pos": 0} 2025-09-07T09:50:00.1320463Z AUTOTUNE mm(3136x128, 128x512) 2025-09-07T09:50:00.1320741Z strides: [128, 1], [1, 128] 2025-09-07T09:50:00.1321005Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:00.1321698Z triton_mm_246 0.0084 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 2025-09-07T09:50:00.1322732Z triton_mm_248 0.0085 ms 98.1% 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 2025-09-07T09:50:00.1323724Z triton_mm_242 0.0086 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=8 2025-09-07T09:50:00.1324340Z mm 0.0086 ms 97.4% 2025-09-07T09:50:00.1324929Z triton_mm_253 0.0086 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=5, num_warps=8 2025-09-07T09:50:00.1325934Z triton_mm_245 0.0087 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 2025-09-07T09:50:00.1326927Z triton_mm_252 0.0088 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 2025-09-07T09:50:00.1327910Z triton_mm_244 0.0088 ms 94.9% 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 2025-09-07T09:50:00.1328914Z triton_mm_243 0.0089 ms 94.6% 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 2025-09-07T09:50:00.1330492Z triton_mm_247 0.0089 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:00.1331350Z SingleProcess AUTOTUNE benchmarking takes 0.5093 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:50:01.5404591Z Autotune Choices Stats: 2025-09-07T09:50:01.5405904Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_15", "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": 0.0077760000713169575, "best_triton_pos": 0} 2025-09-07T09:50:01.5457886Z AUTOTUNE mm(12544x64, 64x64) 2025-09-07T09:50:01.5458226Z strides: [64, 1], [1, 64] 2025-09-07T09:50:01.5458491Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:01.5459097Z triton_mm_15 0.0078 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 2025-09-07T09:50:01.5460142Z triton_mm_13 0.0078 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:01.5461553Z triton_mm_10 0.0078 ms 99.2% 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 2025-09-07T09:50:01.5462527Z triton_mm_14 0.0078 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:01.5463562Z triton_mm_17 0.0079 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=3, num_warps=4 2025-09-07T09:50:01.5464511Z triton_mm_18 0.0079 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:01.5465456Z triton_mm_16 0.0080 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:01.5466423Z triton_mm_7 0.0081 ms 96.0% 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 2025-09-07T09:50:01.5467382Z triton_mm_22 0.0081 ms 96.0% 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 2025-09-07T09:50:01.5468378Z triton_mm_12 0.0081 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:01.5469241Z SingleProcess AUTOTUNE benchmarking takes 0.5549 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:50:02.1257715Z Autotune Choices Stats: 2025-09-07T09:50:02.1258895Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_86", "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": 0.010304000228643417, "best_triton_pos": 0} 2025-09-07T09:50:02.1296924Z AUTOTUNE mm(12544x256, 256x64) 2025-09-07T09:50:02.1297185Z strides: [256, 1], [1, 256] 2025-09-07T09:50:02.1297437Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:02.1298278Z triton_mm_86 0.0103 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 2025-09-07T09:50:02.1299693Z triton_mm_76 0.0103 ms 99.7% 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 2025-09-07T09:50:02.1300958Z triton_mm_80 0.0104 ms 99.4% 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=4 2025-09-07T09:50:02.1302054Z triton_mm_85 0.0106 ms 97.3% 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 2025-09-07T09:50:02.1303215Z triton_mm_70 0.0108 ms 95.5% 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 2025-09-07T09:50:02.1304504Z triton_mm_83 0.0111 ms 92.8% 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 2025-09-07T09:50:02.1305591Z triton_mm_82 0.0115 ms 89.9% 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 2025-09-07T09:50:02.1306636Z triton_mm_79 0.0117 ms 87.7% 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 2025-09-07T09:50:02.1307599Z triton_mm_71 0.0118 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 2025-09-07T09:50:02.1308564Z triton_mm_81 0.0120 ms 86.1% 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 2025-09-07T09:50:02.1309520Z SingleProcess AUTOTUNE benchmarking takes 0.2983 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:50:02.6414731Z Autotune Choices Stats: 2025-09-07T09:50:02.6416156Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010015999898314476, "best_triton_pos": 1, "best_triton_time": 0.01056000031530857, "best_triton_kernel": "triton_mm_356", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:50:02.7302431Z AUTOTUNE mm(3136x512, 512x256) 2025-09-07T09:50:02.7302913Z strides: [512, 1], [1, 512] 2025-09-07T09:50:02.7303250Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:02.7303504Z mm 0.0100 ms 100.0% 2025-09-07T09:50:02.7304204Z triton_mm_356 0.0106 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:02.7305331Z triton_mm_362 0.0110 ms 90.7% 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 2025-09-07T09:50:02.7306423Z triton_mm_351 0.0114 ms 88.2% 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 2025-09-07T09:50:02.7307453Z triton_mm_355 0.0116 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:02.7308543Z triton_mm_361 0.0118 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 2025-09-07T09:50:02.7309600Z triton_mm_352 0.0120 ms 83.5% 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 2025-09-07T09:50:02.7311044Z triton_mm_354 0.0121 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 2025-09-07T09:50:02.7312451Z triton_mm_358 0.0121 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=4, num_warps=8 2025-09-07T09:50:02.7313490Z triton_mm_345 0.0126 ms 79.6% 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 2025-09-07T09:50:02.7314390Z SingleProcess AUTOTUNE benchmarking takes 0.5500 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:50:03.7692712Z Autotune Choices Stats: 2025-09-07T09:50:03.7694539Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.00863999966531992, "best_triton_pos": 1, "best_triton_time": 0.008767999708652496, "best_triton_kernel": "triton_mm_436", "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=4, num_warps=8"} 2025-09-07T09:50:03.7749385Z AUTOTUNE mm(784x256, 256x1024) 2025-09-07T09:50:03.7749638Z strides: [256, 1], [1, 256] 2025-09-07T09:50:03.7749875Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:03.7750160Z mm 0.0086 ms 100.0% 2025-09-07T09:50:03.7751200Z triton_mm_436 0.0088 ms 98.5% 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 2025-09-07T09:50:03.7752361Z triton_mm_429 0.0088 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:03.7753502Z triton_mm_432 0.0089 ms 97.5% 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 2025-09-07T09:50:03.7754641Z triton_mm_434 0.0089 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:03.7755772Z triton_mm_433 0.0092 ms 93.4% 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 2025-09-07T09:50:03.7756911Z triton_mm_431 0.0095 ms 91.2% 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 2025-09-07T09:50:03.7758058Z triton_mm_440 0.0096 ms 90.3% 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 2025-09-07T09:50:03.7759215Z triton_mm_439 0.0097 ms 89.4% 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 2025-09-07T09:50:03.7760559Z triton_mm_435 0.0097 ms 89.1% 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 2025-09-07T09:50:03.7761392Z SingleProcess AUTOTUNE benchmarking takes 0.2425 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:50:05.1206635Z Autotune Choices Stats: 2025-09-07T09:50:05.1207853Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_217", "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": 0.009151999838650227, "best_triton_pos": 0} 2025-09-07T09:50:05.1406378Z AUTOTUNE mm(3136x512, 512x128) 2025-09-07T09:50:05.1406684Z strides: [512, 1], [1, 512] 2025-09-07T09:50:05.1406963Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:05.1407832Z triton_mm_217 0.0092 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 2025-09-07T09:50:05.1809488Z triton_mm_221 0.0097 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:05.1810116Z mm 0.0100 ms 92.0% 2025-09-07T09:50:05.1811167Z triton_mm_216 0.0100 ms 91.7% 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 2025-09-07T09:50:05.1812252Z triton_mm_220 0.0103 ms 89.1% 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 2025-09-07T09:50:05.1813533Z triton_mm_227 0.0107 ms 85.9% 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 2025-09-07T09:50:05.1814636Z triton_mm_212 0.0110 ms 83.1% 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 2025-09-07T09:50:05.1815752Z triton_mm_210 0.0111 ms 82.2% 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 2025-09-07T09:50:05.1816855Z triton_mm_219 0.0111 ms 82.2% 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 2025-09-07T09:50:05.1817944Z triton_mm_226 0.0112 ms 81.9% 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 2025-09-07T09:50:05.1818906Z SingleProcess AUTOTUNE benchmarking takes 0.2579 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:50:05.6788710Z Autotune Choices Stats: 2025-09-07T09:50:05.6789814Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_629", "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": 0.009568000212311745, "best_triton_pos": 0} 2025-09-07T09:50:05.6948070Z AUTOTUNE mm(784x1024, 1024x512) 2025-09-07T09:50:05.6948458Z strides: [1024, 1], [1, 1024] 2025-09-07T09:50:05.6948724Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:05.6949405Z triton_mm_629 0.0096 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 2025-09-07T09:50:05.6950041Z mm 0.0100 ms 95.5% 2025-09-07T09:50:05.6950895Z triton_mm_633 0.0106 ms 90.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:05.6951908Z triton_mm_625 0.0123 ms 78.1% 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 2025-09-07T09:50:05.6952889Z triton_mm_628 0.0123 ms 78.1% 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 2025-09-07T09:50:05.6953845Z triton_mm_632 0.0127 ms 75.5% 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 2025-09-07T09:50:05.6954813Z triton_mm_639 0.0127 ms 75.5% 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 2025-09-07T09:50:05.6955794Z triton_mm_638 0.0140 ms 68.4% 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 2025-09-07T09:50:05.6956763Z triton_mm_624 0.0141 ms 67.8% 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 2025-09-07T09:50:05.6958153Z triton_mm_622 0.0142 ms 67.3% 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 2025-09-07T09:50:05.6959015Z SingleProcess AUTOTUNE benchmarking takes 0.2548 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:50:06.2444893Z Autotune Choices Stats: 2025-09-07T09:50:06.2446041Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_711", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009312000125646591, "best_triton_pos": 0} 2025-09-07T09:50:06.2668292Z AUTOTUNE mm(196x512, 512x2048) 2025-09-07T09:50:06.2668632Z strides: [512, 1], [1, 512] 2025-09-07T09:50:06.2668929Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:06.2669616Z triton_mm_711 0.0093 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:06.2670461Z mm 0.0094 ms 99.0% 2025-09-07T09:50:06.2671168Z triton_mm_707 0.0094 ms 98.6% 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 2025-09-07T09:50:06.2672164Z triton_mm_706 0.0100 ms 93.0% 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 2025-09-07T09:50:06.2673133Z triton_mm_710 0.0102 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 2025-09-07T09:50:06.2674103Z triton_mm_703 0.0105 ms 88.7% 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 2025-09-07T09:50:06.2675076Z triton_mm_717 0.0105 ms 88.7% 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 2025-09-07T09:50:06.2676042Z triton_mm_716 0.0109 ms 85.6% 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 2025-09-07T09:50:06.2677010Z triton_mm_700 0.0109 ms 85.3% 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 2025-09-07T09:50:06.2677974Z triton_mm_713 0.0111 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 2025-09-07T09:50:06.2678824Z SingleProcess AUTOTUNE benchmarking takes 0.2946 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:50:07.5027726Z Autotune Choices Stats: 2025-09-07T09:50:07.5028824Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_400", "best_kernel_desc": "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", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:50:07.5238750Z AUTOTUNE mm(784x1024, 1024x256) 2025-09-07T09:50:07.5239145Z strides: [1024, 1], [1, 1024] 2025-09-07T09:50:07.5239391Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:07.5240078Z triton_mm_400 0.0092 ms 100.0% 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 2025-09-07T09:50:07.5241413Z triton_mm_404 0.0097 ms 95.4% 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 2025-09-07T09:50:07.5242626Z mm 0.0102 ms 90.6% 2025-09-07T09:50:07.5243356Z triton_mm_408 0.0108 ms 85.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:07.5244465Z triton_mm_399 0.0119 ms 77.2% 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 2025-09-07T09:50:07.5245568Z triton_mm_403 0.0123 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 2025-09-07T09:50:07.5246899Z triton_mm_398 0.0124 ms 74.4% 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 2025-09-07T09:50:07.5247847Z triton_mm_414 0.0127 ms 72.4% 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 2025-09-07T09:50:07.5248827Z triton_mm_407 0.0129 ms 71.6% 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 2025-09-07T09:50:07.5249834Z triton_mm_397 0.0133 ms 69.4% 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 2025-09-07T09:50:07.5250830Z SingleProcess AUTOTUNE benchmarking takes 0.3161 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:50:08.1288918Z Autotune Choices Stats: 2025-09-07T09:50:08.1290897Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010400000028312206, "best_triton_pos": 1, "best_triton_time": 0.010912000201642513, "best_triton_kernel": "triton_mm_677", "best_triton_kernel_desc": "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"} 2025-09-07T09:50:08.1538175Z AUTOTUNE mm(196x2048, 2048x512) 2025-09-07T09:50:08.1538473Z strides: [2048, 1], [1, 2048] 2025-09-07T09:50:08.1538778Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:08.1539058Z mm 0.0104 ms 100.0% 2025-09-07T09:50:08.1539695Z triton_mm_677 0.0109 ms 95.3% 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 2025-09-07T09:50:08.1540889Z triton_mm_681 0.0120 ms 86.7% 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 2025-09-07T09:50:08.1541972Z triton_mm_685 0.0137 ms 76.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:08.1543028Z triton_mm_691 0.0174 ms 59.6% 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 2025-09-07T09:50:08.1543994Z triton_mm_676 0.0178 ms 58.6% 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 2025-09-07T09:50:08.1544944Z triton_mm_675 0.0181 ms 57.3% 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 2025-09-07T09:50:08.1545910Z triton_mm_680 0.0189 ms 55.0% 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 2025-09-07T09:50:08.1546875Z triton_mm_674 0.0191 ms 54.3% 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 2025-09-07T09:50:08.1548260Z triton_mm_684 0.0193 ms 53.9% 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 2025-09-07T09:50:08.1549103Z SingleProcess AUTOTUNE benchmarking takes 0.2743 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:50:10.4654631Z Autotune Choices Stats: 2025-09-07T09:50:10.4656392Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.041439998894929886, "best_triton_pos": 1, "best_triton_time": 0.0732479989528656, "best_triton_kernel": "triton_convolution2d_0", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:10.4674264Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T09:50:10.4674723Z strides: [150528, 1, 672, 3], [147, 1, 21, 3] 2025-09-07T09:50:10.4675045Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:10.4675422Z convolution 0.0414 ms 100.0% 2025-09-07T09:50:10.4676245Z triton_convolution2d_0 0.0732 ms 56.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.4677684Z triton_convolution2d_3 0.0766 ms 54.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.4679115Z triton_convolution2d_4 0.0837 ms 49.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.4680807Z triton_convolution2d_2 0.1203 ms 34.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:10.4682100Z triton_convolution2d_5 0.1282 ms 32.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.4683265Z triton_convolution2d_1 0.2454 ms 16.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.4684270Z SingleProcess AUTOTUNE benchmarking takes 0.1632 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:50:10.5697183Z Autotune Choices Stats: 2025-09-07T09:50:10.5698786Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01408000010997057, "best_triton_pos": 1, "best_triton_time": 0.017152000218629837, "best_triton_kernel": "triton_convolution2d_29", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:50:10.5786689Z AUTOTUNE convolution(4x64x56x56, 64x64x3x3) 2025-09-07T09:50:10.5787003Z strides: [200704, 1, 3584, 64], [576, 1, 192, 64] 2025-09-07T09:50:10.5787295Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:10.5787550Z convolution 0.0141 ms 100.0% 2025-09-07T09:50:10.5788229Z triton_convolution2d_29 0.0172 ms 82.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.5789514Z triton_convolution2d_28 0.0175 ms 80.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.5791550Z triton_convolution2d_27 0.0183 ms 76.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.5792940Z triton_convolution2d_24 0.0214 ms 65.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.5794530Z triton_convolution2d_30 0.0236 ms 59.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.5796389Z triton_convolution2d_25 0.0303 ms 46.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.5797776Z triton_convolution2d_26 0.0507 ms 27.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:10.5798889Z SingleProcess AUTOTUNE benchmarking takes 0.1103 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:10.6952464Z Autotune Choices Stats: 2025-09-07T09:50:10.6953824Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012575999833643436, "best_triton_pos": 1, "best_triton_time": 0.0306560005992651, "best_triton_kernel": "triton_convolution2d_180", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:10.7055969Z AUTOTUNE convolution(4x128x56x56, 128x128x3x3) 2025-09-07T09:50:10.7056317Z strides: [401408, 1, 7168, 128], [1152, 1, 384, 128] 2025-09-07T09:50:10.7056613Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:10.7056872Z convolution 0.0126 ms 100.0% 2025-09-07T09:50:10.7057582Z triton_convolution2d_180 0.0307 ms 41.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.7058763Z triton_convolution2d_181 0.0344 ms 36.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.7059926Z triton_convolution2d_179 0.0372 ms 33.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.7061423Z triton_convolution2d_182 0.0375 ms 33.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.7062576Z triton_convolution2d_176 0.0466 ms 27.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.7063809Z triton_convolution2d_177 0.0515 ms 24.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.7064955Z triton_convolution2d_178 0.1036 ms 12.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:10.7066014Z SingleProcess AUTOTUNE benchmarking takes 0.1246 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:10.8034283Z Autotune Choices Stats: 2025-09-07T09:50:10.8036315Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01228800043463707, "best_triton_pos": 1, "best_triton_time": 0.01283199992030859, "best_triton_kernel": "triton_convolution2d_206", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:50:10.8313340Z AUTOTUNE convolution(4x256x56x56, 512x256x1x1) 2025-09-07T09:50:10.8313759Z strides: [802816, 1, 14336, 256], [256, 1, 256, 256] 2025-09-07T09:50:10.8314224Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:10.8314584Z convolution 0.0123 ms 100.0% 2025-09-07T09:50:10.8315917Z triton_convolution2d_206 0.0128 ms 95.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:10.8317447Z triton_convolution2d_205 0.0140 ms 87.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:10.8318923Z triton_convolution2d_208 0.0142 ms 86.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:10.8321221Z triton_convolution2d_207 0.0142 ms 86.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:10.8322632Z triton_convolution2d_203 0.0175 ms 70.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:10.8323907Z triton_convolution2d_202 0.0176 ms 69.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:10.8325320Z triton_convolution2d_204 0.0294 ms 41.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:50:10.8326211Z SingleProcess AUTOTUNE benchmarking takes 0.1248 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:10.9450856Z Autotune Choices Stats: 2025-09-07T09:50:10.9452409Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012191999703645706, "best_triton_pos": 1, "best_triton_time": 0.029472000896930695, "best_triton_kernel": "triton_convolution2d_232", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:10.9463332Z AUTOTUNE convolution(4x128x28x28, 128x128x3x3) 2025-09-07T09:50:10.9463792Z strides: [100352, 1, 3584, 128], [1152, 1, 384, 128] 2025-09-07T09:50:10.9464120Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:10.9464352Z convolution 0.0122 ms 100.0% 2025-09-07T09:50:10.9465234Z triton_convolution2d_232 0.0295 ms 41.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.9466568Z triton_convolution2d_233 0.0333 ms 36.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.9467920Z triton_convolution2d_231 0.0375 ms 32.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.9469714Z triton_convolution2d_234 0.0379 ms 32.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:10.9471161Z triton_convolution2d_228 0.0461 ms 26.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.9472235Z triton_convolution2d_229 0.0478 ms 25.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:10.9473674Z triton_convolution2d_230 0.0985 ms 12.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:10.9474504Z SingleProcess AUTOTUNE benchmarking takes 0.1141 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:11.0967213Z Autotune Choices Stats: 2025-09-07T09:50:11.0968619Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015519999898970127, "best_triton_pos": 1, "best_triton_time": 0.053408000618219376, "best_triton_kernel": "triton_convolution2d_367", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:11.1045652Z AUTOTUNE convolution(4x256x28x28, 256x256x3x3) 2025-09-07T09:50:11.1046024Z strides: [200704, 1, 7168, 256], [2304, 1, 768, 256] 2025-09-07T09:50:11.1046354Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:11.1046665Z convolution 0.0155 ms 100.0% 2025-09-07T09:50:11.1047482Z triton_convolution2d_367 0.0534 ms 29.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.1048849Z triton_convolution2d_369 0.0680 ms 22.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.1050191Z triton_convolution2d_366 0.0691 ms 22.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.1051708Z triton_convolution2d_368 0.0747 ms 20.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.1053032Z triton_convolution2d_364 0.0953 ms 16.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.1054195Z triton_convolution2d_363 0.0989 ms 15.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.1055334Z triton_convolution2d_365 0.1912 ms 8.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:11.1056250Z SingleProcess AUTOTUNE benchmarking takes 0.1556 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:11.2051734Z Autotune Choices Stats: 2025-09-07T09:50:11.2053156Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011071999557316303, "best_triton_pos": 1, "best_triton_time": 0.01651199907064438, "best_triton_kernel": "triton_convolution2d_393", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:50:11.2416729Z AUTOTUNE convolution(4x512x28x28, 1024x512x1x1) 2025-09-07T09:50:11.2417084Z strides: [401408, 1, 14336, 512], [512, 1, 512, 512] 2025-09-07T09:50:11.2417408Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:11.2417686Z convolution 0.0111 ms 100.0% 2025-09-07T09:50:11.2418450Z triton_convolution2d_393 0.0165 ms 67.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:11.2420014Z triton_convolution2d_392 0.0196 ms 56.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:11.2421678Z triton_convolution2d_395 0.0196 ms 56.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:11.2423023Z triton_convolution2d_394 0.0197 ms 56.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:11.2424161Z triton_convolution2d_390 0.0253 ms 43.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:11.2425304Z triton_convolution2d_389 0.0257 ms 43.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:11.2426438Z triton_convolution2d_391 0.0460 ms 24.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:50:11.2427346Z SingleProcess AUTOTUNE benchmarking takes 0.1360 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:11.3903042Z Autotune Choices Stats: 2025-09-07T09:50:11.3904479Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013856000266969204, "best_triton_pos": 1, "best_triton_time": 0.05238400027155876, "best_triton_kernel": "triton_convolution2d_419", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:11.3921923Z AUTOTUNE convolution(4x256x14x14, 256x256x3x3) 2025-09-07T09:50:11.3922346Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T09:50:11.3922652Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:11.3922989Z convolution 0.0139 ms 100.0% 2025-09-07T09:50:11.3923794Z triton_convolution2d_419 0.0524 ms 26.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.3925163Z triton_convolution2d_418 0.0695 ms 19.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.3926547Z triton_convolution2d_421 0.0708 ms 19.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.3927939Z triton_convolution2d_420 0.0744 ms 18.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.3929732Z triton_convolution2d_416 0.0905 ms 15.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.3931402Z triton_convolution2d_415 0.1026 ms 13.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.3932777Z triton_convolution2d_417 0.1895 ms 7.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:11.3933993Z SingleProcess AUTOTUNE benchmarking takes 0.1496 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:11.6043219Z Autotune Choices Stats: 2025-09-07T09:50:11.6044649Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.017216000705957413, "best_triton_pos": 1, "best_triton_time": 0.10915199667215347, "best_triton_kernel": "triton_convolution2d_644", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:11.6279509Z AUTOTUNE convolution(4x512x14x14, 512x512x3x3) 2025-09-07T09:50:11.6279844Z strides: [100352, 1, 7168, 512], [4608, 1, 1536, 512] 2025-09-07T09:50:11.6280155Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:11.6280828Z convolution 0.0172 ms 100.0% 2025-09-07T09:50:11.6281590Z triton_convolution2d_644 0.1092 ms 15.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.6282956Z triton_convolution2d_643 0.1320 ms 13.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.6284310Z triton_convolution2d_646 0.1321 ms 13.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.6285641Z triton_convolution2d_645 0.1427 ms 12.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.6286968Z triton_convolution2d_641 0.1971 ms 8.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.6288292Z triton_convolution2d_640 0.2160 ms 8.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.6289605Z triton_convolution2d_642 0.2514 ms 6.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:11.6290827Z SingleProcess AUTOTUNE benchmarking takes 0.2309 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:11.7358297Z Autotune Choices Stats: 2025-09-07T09:50:11.7359650Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01244799979031086, "best_triton_pos": 1, "best_triton_time": 0.02796800062060356, "best_triton_kernel": "triton_convolution2d_670", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:50:11.7611527Z AUTOTUNE convolution(4x1024x14x14, 2048x1024x1x1) 2025-09-07T09:50:11.7611924Z strides: [200704, 1, 14336, 1024], [1024, 1, 1024, 1024] 2025-09-07T09:50:11.7612286Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:11.7612579Z convolution 0.0124 ms 100.0% 2025-09-07T09:50:11.7613363Z triton_convolution2d_670 0.0280 ms 44.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:11.7614891Z triton_convolution2d_672 0.0328 ms 38.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:11.7616167Z triton_convolution2d_669 0.0331 ms 37.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:11.7617424Z triton_convolution2d_671 0.0338 ms 36.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:11.7618651Z triton_convolution2d_667 0.0452 ms 27.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:11.7619877Z triton_convolution2d_666 0.0464 ms 26.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:11.7621334Z triton_convolution2d_668 0.0591 ms 21.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:50:11.7622338Z SingleProcess AUTOTUNE benchmarking takes 0.1322 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:11.9618935Z Autotune Choices Stats: 2025-09-07T09:50:11.9620673Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.017216000705957413, "best_triton_pos": 1, "best_triton_time": 0.10844799876213074, "best_triton_kernel": "triton_convolution2d_696", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:11.9844927Z AUTOTUNE convolution(4x512x7x7, 512x512x3x3) 2025-09-07T09:50:11.9845309Z strides: [25088, 1, 3584, 512], [4608, 1, 1536, 512] 2025-09-07T09:50:11.9845649Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:11.9845955Z convolution 0.0172 ms 100.0% 2025-09-07T09:50:11.9846754Z triton_convolution2d_696 0.1084 ms 15.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.9848104Z triton_convolution2d_695 0.1338 ms 12.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.9849448Z triton_convolution2d_698 0.1381 ms 12.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.9850998Z triton_convolution2d_697 0.1412 ms 12.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:11.9852709Z triton_convolution2d_694 0.1744 ms 9.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:11.9853868Z triton_convolution2d_693 0.1940 ms 8.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.9855005Z triton_convolution2d_692 0.2044 ms 8.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:11.9855906Z SingleProcess AUTOTUNE benchmarking takes 0.2224 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:12.2349554Z Autotune Choices Stats: 2025-09-07T09:50:12.2350948Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_767", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.010879999957978725, "best_triton_pos": 0} 2025-09-07T09:50:12.2517295Z AUTOTUNE addmm(4x1000, 4x2048, 2048x1000) 2025-09-07T09:50:12.2517585Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T09:50:12.2517881Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:50:12.2518564Z triton_mm_767 0.0109 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:12.2519546Z triton_mm_771 0.0114 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:12.2520179Z bias_addmm 0.0116 ms 94.2% 2025-09-07T09:50:12.2520967Z triton_mm_775 0.0138 ms 79.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:12.2521588Z addmm 0.0150 ms 72.6% 2025-09-07T09:50:12.2522153Z triton_mm_779 0.0152 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:12.2523113Z triton_mm_766 0.0173 ms 62.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:12.2524038Z triton_mm_765 0.0182 ms 59.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:12.2524932Z triton_mm_770 0.0184 ms 59.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:12.2525822Z triton_mm_764 0.0188 ms 57.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:50:12.2526616Z SingleProcess AUTOTUNE benchmarking takes 0.2655 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:50:22.0750393Z Autotune Choices Stats: 2025-09-07T09:50:22.0751527Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_802", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.007007999811321497, "best_triton_pos": 0} 2025-09-07T09:50:22.1024204Z AUTOTUNE mm(1000x4, 4x2048) 2025-09-07T09:50:22.1024510Z strides: [1, 1000], [2048, 1] 2025-09-07T09:50:22.1024834Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:22.1025529Z triton_mm_802 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:22.1027025Z triton_mm_803 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:22.1028015Z triton_mm_804 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:22.1029002Z triton_mm_806 0.0071 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:22.1030620Z triton_mm_805 0.0072 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:22.1031628Z triton_mm_807 0.0072 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:22.1032619Z triton_mm_808 0.0072 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:22.1033596Z triton_mm_809 0.0072 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:22.1034584Z triton_mm_811 0.0072 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:22.1035619Z triton_mm_801 0.0072 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:22.1036364Z SingleProcess AUTOTUNE benchmarking takes 0.1839 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:50:22.7005883Z Autotune Choices Stats: 2025-09-07T09:50:22.7007991Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009696000255644321, "best_triton_pos": 1, "best_triton_time": 0.010400000028312206, "best_triton_kernel": "triton_mm_788", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:50:22.7553594Z AUTOTUNE mm(4x1000, 1000x2048) 2025-09-07T09:50:22.7553980Z strides: [1000, 1], [2048, 1] 2025-09-07T09:50:22.7554253Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:22.7554539Z mm 0.0097 ms 100.0% 2025-09-07T09:50:22.7555186Z triton_mm_788 0.0104 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:22.7556338Z triton_mm_792 0.0106 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:22.7557314Z triton_mm_784 0.0108 ms 89.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:22.7558285Z triton_mm_796 0.0119 ms 81.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:22.7559253Z triton_mm_782 0.0119 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:22.7560363Z triton_mm_783 0.0126 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:22.7561726Z triton_mm_787 0.0126 ms 76.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:22.7562699Z triton_mm_794 0.0134 ms 72.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:22.7563675Z triton_mm_791 0.0136 ms 71.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:22.7564519Z SingleProcess AUTOTUNE benchmarking takes 0.2368 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:50:29.4483453Z W0907 09:50:29.431000 18988 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:50:49.4964705Z pass 2025-09-07T09:50:54.4346016Z /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. 2025-09-07T09:50:54.4347653Z import pynvml # type: ignore[import] 2025-09-07T09:50:56.9157909Z 2025-09-07T09:50:58.9917838Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:50:58.9918170Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:50:58.9918440Z cuda train resnet50_quantized_qat 2025-09-07T09:50:58.9918747Z Traceback (most recent call last): 2025-09-07T09:50:58.9919201Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:50:58.9919665Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:50:58.9920581Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:50:58.9921116Z pred = mod(*cloned_inputs) 2025-09-07T09:50:58.9921594Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:50:58.9922111Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:50:58.9922594Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:50:58.9923046Z raise e 2025-09-07T09:50:58.9923432Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:50:58.9923989Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:50:58.9924593Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:50:58.9925118Z return self._call_impl(*args, **kwargs) 2025-09-07T09:50:58.9925592Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:50:58.9926082Z return forward_call(*args, **kwargs) 2025-09-07T09:50:58.9926351Z File ".3", line 167, in forward 2025-09-07T09:50:58.9926726Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:50:58.9927356Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:50:58.9927871Z return self._call_impl(*args, **kwargs) 2025-09-07T09:50:58.9928347Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:50:58.9928826Z return forward_call(*args, **kwargs) 2025-09-07T09:50:58.9929344Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:50:58.9929901Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:50:58.9930852Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:50:58.9931082Z 2025-09-07T09:50:58.9931254Z The above exception was the direct cause of the following exception: 2025-09-07T09:50:58.9931517Z 2025-09-07T09:50:58.9931609Z Traceback (most recent call last): 2025-09-07T09:50:58.9931991Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:50:58.9932374Z ) = runner.load_model( 2025-09-07T09:50:58.9932781Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:50:58.9933253Z self.validate_model(model, example_inputs) 2025-09-07T09:50:58.9933711Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:50:58.9934171Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:50:58.9934679Z RuntimeError: Eager run failed 2025-09-07T09:50:58.9934851Z 2025-09-07T09:50:58.9934923Z eager_fail_to_run 2025-09-07T09:51:00.7624736Z /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. 2025-09-07T09:51:00.7625923Z import pynvml # type: ignore[import] 2025-09-07T09:51:03.2079006Z 2025-09-07T09:51:05.8227736Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:05.8228148Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:51:05.8228462Z cuda train resnext50_32x4d 2025-09-07T09:51:19.5073434Z Autotune Choices Stats: 2025-09-07T09:51:19.5074957Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_3", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.03484800085425377, "best_triton_pos": 0} 2025-09-07T09:51:19.5098158Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T09:51:19.5098596Z strides: [150528, 50176, 224, 1], [147, 49, 7, 1] 2025-09-07T09:51:19.5098996Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:19.5100040Z triton_convolution2d_3 0.0348 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:19.5102120Z triton_convolution2d_5 0.0349 ms 99.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:19.5103979Z triton_convolution2d_1 0.0378 ms 92.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:19.5105606Z triton_convolution2d_0 0.0416 ms 83.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:19.5107228Z triton_convolution2d_4 0.0541 ms 64.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:19.5108219Z convolution 0.0561 ms 62.1% 2025-09-07T09:51:19.5109178Z triton_convolution2d_2 0.0957 ms 36.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:19.5110591Z SingleProcess AUTOTUNE benchmarking takes 0.1315 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:51:19.9882430Z Autotune Choices Stats: 2025-09-07T09:51:19.9884307Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_24", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.010015999898314476, "best_triton_pos": 0} 2025-09-07T09:51:19.9896366Z AUTOTUNE convolution(4x64x56x56, 256x64x1x1) 2025-09-07T09:51:19.9896769Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:51:19.9897163Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:19.9898173Z triton_convolution2d_24 0.0100 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:19.9900119Z triton_convolution2d_23 0.0106 ms 94.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:19.9902105Z triton_convolution2d_26 0.0111 ms 90.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:19.9903864Z triton_convolution2d_21 0.0119 ms 83.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:19.9905516Z triton_convolution2d_22 0.0130 ms 76.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:19.9907166Z triton_convolution2d_20 0.0168 ms 59.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:19.9908798Z triton_convolution2d_25 0.0191 ms 52.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:19.9909792Z conv1x1_via_mm 0.0502 ms 19.9% 2025-09-07T09:51:19.9910131Z convolution 0.0720 ms 13.9% 2025-09-07T09:51:19.9910890Z SingleProcess AUTOTUNE benchmarking takes 0.1501 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:20.5067828Z Autotune Choices Stats: 2025-09-07T09:51:20.5069339Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010463999584317207, "best_triton_pos": 1, "best_triton_time": 0.011680000461637974, "best_triton_kernel": "triton_convolution2d_38", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:20.6150445Z AUTOTUNE convolution(4x128x56x56, 256x128x1x1) 2025-09-07T09:51:20.6150776Z strides: [401408, 3136, 56, 1], [128, 1, 1, 1] 2025-09-07T09:51:20.6151058Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:20.6151319Z convolution 0.0105 ms 100.0% 2025-09-07T09:51:20.6151997Z triton_convolution2d_38 0.0117 ms 89.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:20.6153221Z triton_convolution2d_37 0.0131 ms 80.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:20.6154462Z triton_convolution2d_40 0.0136 ms 76.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:20.6155665Z triton_convolution2d_34 0.0143 ms 73.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:20.6157275Z triton_convolution2d_35 0.0155 ms 67.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:20.6158491Z triton_convolution2d_39 0.0174 ms 60.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:20.6159877Z triton_convolution2d_36 0.0178 ms 58.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:20.6160765Z conv1x1_via_mm 0.0582 ms 18.0% 2025-09-07T09:51:20.6161248Z SingleProcess AUTOTUNE benchmarking takes 0.2407 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:21.0414689Z Autotune Choices Stats: 2025-09-07T09:51:21.0416180Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011359999887645245, "best_triton_pos": 1, "best_triton_time": 0.014976000413298607, "best_triton_kernel": "triton_convolution2d_59", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:21.0857942Z AUTOTUNE convolution(4x256x56x56, 256x256x1x1) 2025-09-07T09:51:21.0858398Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:51:21.0858792Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:21.0859158Z convolution 0.0114 ms 100.0% 2025-09-07T09:51:21.0860169Z triton_convolution2d_59 0.0150 ms 75.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.0862071Z triton_convolution2d_58 0.0168 ms 67.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.0863925Z triton_convolution2d_61 0.0177 ms 64.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.0865555Z triton_convolution2d_55 0.0205 ms 55.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.0867205Z triton_convolution2d_56 0.0223 ms 51.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.0868845Z triton_convolution2d_60 0.0236 ms 48.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.0870870Z triton_convolution2d_57 0.0264 ms 43.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:21.0871896Z conv1x1_via_mm 0.0707 ms 16.1% 2025-09-07T09:51:21.0872535Z SingleProcess AUTOTUNE benchmarking takes 0.1777 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:21.5443263Z Autotune Choices Stats: 2025-09-07T09:51:21.5444790Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_11", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8", "best_time": 0.008799999952316284, "best_triton_pos": 0} 2025-09-07T09:51:21.5473133Z AUTOTUNE convolution(4x64x56x56, 128x64x1x1) 2025-09-07T09:51:21.5473536Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:51:21.5473922Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:21.5474936Z triton_convolution2d_11 0.0088 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.5476552Z triton_convolution2d_10 0.0090 ms 97.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.5477785Z convolution 0.0094 ms 93.9% 2025-09-07T09:51:21.5478744Z triton_convolution2d_6 0.0099 ms 88.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.5480499Z triton_convolution2d_12 0.0103 ms 85.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.5482127Z triton_convolution2d_9 0.0106 ms 82.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.5483752Z triton_convolution2d_7 0.0122 ms 72.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.5485359Z triton_convolution2d_8 0.0136 ms 64.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:21.5486353Z conv1x1_via_mm 0.0350 ms 25.1% 2025-09-07T09:51:21.5486986Z SingleProcess AUTOTUNE benchmarking takes 0.1426 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:21.9529217Z Autotune Choices Stats: 2025-09-07T09:51:21.9531251Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010879999957978725, "best_triton_pos": 1, "best_triton_time": 0.013952000066637993, "best_triton_kernel": "triton_convolution2d_31", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:21.9545781Z AUTOTUNE convolution(4x256x56x56, 128x256x1x1) 2025-09-07T09:51:21.9546110Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:51:21.9546444Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:21.9546764Z convolution 0.0109 ms 100.0% 2025-09-07T09:51:21.9547569Z triton_convolution2d_31 0.0140 ms 78.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.9548903Z triton_convolution2d_32 0.0141 ms 76.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.9550375Z triton_convolution2d_33 0.0165 ms 66.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.9551724Z triton_convolution2d_30 0.0170 ms 63.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:21.9553501Z triton_convolution2d_27 0.0175 ms 62.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.9554958Z triton_convolution2d_28 0.0216 ms 50.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:21.9556423Z triton_convolution2d_29 0.0239 ms 45.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:21.9557325Z conv1x1_via_mm 0.0533 ms 20.4% 2025-09-07T09:51:21.9558094Z SingleProcess AUTOTUNE benchmarking takes 0.1333 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:22.1735745Z Autotune Choices Stats: 2025-09-07T09:51:22.1736911Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_73", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.015263999812304974, "best_triton_pos": 0} 2025-09-07T09:51:22.1793255Z AUTOTUNE convolution(4x256x56x56, 512x256x1x1) 2025-09-07T09:51:22.1793604Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:51:22.1793918Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:22.1794766Z triton_convolution2d_73 0.0153 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:22.1796126Z triton_convolution2d_74 0.0168 ms 90.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:22.1797454Z triton_convolution2d_75 0.0216 ms 70.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:22.1798761Z triton_convolution2d_69 0.0228 ms 67.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:22.1800072Z triton_convolution2d_70 0.0234 ms 65.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:22.1801170Z convolution 0.0276 ms 55.4% 2025-09-07T09:51:22.1801952Z triton_convolution2d_71 0.0486 ms 31.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:22.1803279Z triton_convolution2d_72 0.0524 ms 29.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:22.1804192Z SingleProcess AUTOTUNE benchmarking takes 0.1719 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:22.7128600Z Autotune Choices Stats: 2025-09-07T09:51:22.7130191Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01017600018531084, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_convolution2d_87", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:22.7185041Z AUTOTUNE convolution(4x256x28x28, 512x256x1x1) 2025-09-07T09:51:22.7185391Z strides: [200704, 784, 28, 1], [256, 1, 1, 1] 2025-09-07T09:51:22.7193718Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:22.7194046Z convolution 0.0102 ms 100.0% 2025-09-07T09:51:22.7194852Z triton_convolution2d_87 0.0143 ms 71.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:22.7196197Z triton_convolution2d_86 0.0158 ms 64.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:22.7197874Z triton_convolution2d_89 0.0162 ms 63.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:22.7199229Z triton_convolution2d_88 0.0169 ms 60.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:22.7200732Z triton_convolution2d_83 0.0211 ms 48.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:22.7202048Z triton_convolution2d_84 0.0214 ms 47.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:22.7203379Z triton_convolution2d_85 0.0243 ms 42.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:22.7204200Z conv1x1_via_mm 0.0368 ms 27.6% 2025-09-07T09:51:22.7204602Z SingleProcess AUTOTUNE benchmarking takes 0.1506 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:51:23.1821739Z Autotune Choices Stats: 2025-09-07T09:51:23.1823996Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012128000147640705, "best_triton_pos": 1, "best_triton_time": 0.0191040001809597, "best_triton_kernel": "triton_convolution2d_122", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:23.1945149Z AUTOTUNE convolution(4x512x28x28, 512x512x1x1) 2025-09-07T09:51:23.1945646Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:51:23.1946111Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:23.1946523Z convolution 0.0121 ms 100.0% 2025-09-07T09:51:23.1947644Z triton_convolution2d_122 0.0191 ms 63.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:23.1949483Z triton_convolution2d_121 0.0230 ms 52.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:23.1951674Z triton_convolution2d_124 0.0231 ms 52.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:23.1953617Z triton_convolution2d_123 0.0244 ms 49.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:23.1955448Z triton_convolution2d_118 0.0328 ms 37.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:23.1957656Z triton_convolution2d_119 0.0338 ms 35.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:23.1959510Z triton_convolution2d_120 0.0389 ms 31.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:23.1960767Z conv1x1_via_mm 0.0437 ms 27.7% 2025-09-07T09:51:23.1961498Z SingleProcess AUTOTUNE benchmarking takes 0.1484 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:23.6500622Z Autotune Choices Stats: 2025-09-07T09:51:23.6501873Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010048000141978264, "best_triton_pos": 1, "best_triton_time": 0.018592000007629395, "best_triton_kernel": "triton_convolution2d_80", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:23.7043340Z AUTOTUNE convolution(4x512x28x28, 256x512x1x1) 2025-09-07T09:51:23.7044214Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:51:23.7044730Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:23.7045280Z convolution 0.0100 ms 100.0% 2025-09-07T09:51:23.7046992Z triton_convolution2d_80 0.0186 ms 54.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:23.7049285Z triton_convolution2d_79 0.0226 ms 44.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:23.7051995Z triton_convolution2d_82 0.0233 ms 43.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:23.7054563Z triton_convolution2d_81 0.0236 ms 42.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:23.7056103Z triton_convolution2d_76 0.0322 ms 31.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:23.7057478Z triton_convolution2d_77 0.0336 ms 29.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:23.7058236Z conv1x1_via_mm 0.0380 ms 26.5% 2025-09-07T09:51:23.7059595Z triton_convolution2d_78 0.0390 ms 25.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:23.7061517Z SingleProcess AUTOTUNE benchmarking takes 0.1963 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:24.0803098Z Autotune Choices Stats: 2025-09-07T09:51:24.0804945Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_136", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.020479999482631683, "best_triton_pos": 0} 2025-09-07T09:51:24.1475732Z AUTOTUNE convolution(4x512x28x28, 1024x512x1x1) 2025-09-07T09:51:24.1476478Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:51:24.1476879Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:24.1477898Z triton_convolution2d_136 0.0205 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:24.1478911Z convolution 0.0225 ms 91.0% 2025-09-07T09:51:24.1479872Z triton_convolution2d_137 0.0247 ms 82.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:24.1482069Z triton_convolution2d_135 0.0248 ms 82.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:24.1483725Z triton_convolution2d_138 0.0347 ms 59.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:24.1485214Z triton_convolution2d_132 0.0360 ms 56.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:24.1486668Z triton_convolution2d_133 0.0384 ms 53.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:24.1488126Z triton_convolution2d_134 0.0649 ms 31.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:24.1489291Z SingleProcess AUTOTUNE benchmarking takes 0.1707 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:24.6770697Z Autotune Choices Stats: 2025-09-07T09:51:24.6772242Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01648000068962574, "best_triton_pos": 1, "best_triton_time": 0.0191040001809597, "best_triton_kernel": "triton_convolution2d_150", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:24.7717050Z AUTOTUNE convolution(4x512x14x14, 1024x512x1x1) 2025-09-07T09:51:24.7717477Z strides: [100352, 196, 14, 1], [512, 1, 1, 1] 2025-09-07T09:51:24.7717888Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:24.7718213Z convolution 0.0165 ms 100.0% 2025-09-07T09:51:24.7719138Z triton_convolution2d_150 0.0191 ms 86.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:24.7720900Z triton_convolution2d_149 0.0230 ms 71.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:24.7722439Z triton_convolution2d_151 0.0235 ms 70.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:24.7723993Z triton_convolution2d_152 0.0236 ms 69.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:24.7724921Z conv1x1_via_mm 0.0283 ms 58.3% 2025-09-07T09:51:24.7725839Z triton_convolution2d_147 0.0290 ms 56.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:24.7727695Z triton_convolution2d_146 0.0328 ms 50.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:24.7729182Z triton_convolution2d_148 0.0423 ms 38.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:24.7730531Z SingleProcess AUTOTUNE benchmarking takes 0.2350 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:25.2832699Z Autotune Choices Stats: 2025-09-07T09:51:25.2834639Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_213", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.030527999624609947, "best_triton_pos": 0} 2025-09-07T09:51:25.3671649Z AUTOTUNE convolution(4x1024x14x14, 1024x1024x1x1) 2025-09-07T09:51:25.3672032Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:51:25.3672357Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:25.3673171Z triton_convolution2d_213 0.0305 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:25.3674084Z conv1x1_via_mm 0.0348 ms 87.7% 2025-09-07T09:51:25.3674897Z triton_convolution2d_212 0.0371 ms 82.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:25.3676240Z triton_convolution2d_214 0.0382 ms 80.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:25.3677585Z triton_convolution2d_215 0.0390 ms 78.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:25.3678918Z triton_convolution2d_210 0.0499 ms 61.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:25.3680392Z triton_convolution2d_209 0.0574 ms 53.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:25.3681233Z convolution 0.0672 ms 45.5% 2025-09-07T09:51:25.3682020Z triton_convolution2d_211 0.0770 ms 39.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:25.3683096Z SingleProcess AUTOTUNE benchmarking takes 0.2335 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:25.8279695Z Autotune Choices Stats: 2025-09-07T09:51:25.8281522Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01865600049495697, "best_triton_pos": 1, "best_triton_time": 0.030112000182271004, "best_triton_kernel": "triton_convolution2d_143", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:26.0086549Z AUTOTUNE convolution(4x1024x14x14, 512x1024x1x1) 2025-09-07T09:51:26.0086970Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:51:26.0087808Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:26.0088120Z convolution 0.0187 ms 100.0% 2025-09-07T09:51:26.0088949Z triton_convolution2d_143 0.0301 ms 62.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:26.0089809Z conv1x1_via_mm 0.0311 ms 60.0% 2025-09-07T09:51:26.0091010Z triton_convolution2d_142 0.0373 ms 50.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:26.0092375Z triton_convolution2d_144 0.0386 ms 48.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:26.0093996Z triton_convolution2d_145 0.0390 ms 47.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:26.0095339Z triton_convolution2d_140 0.0496 ms 37.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:26.0096564Z triton_convolution2d_139 0.0574 ms 32.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:26.0097793Z triton_convolution2d_141 0.0773 ms 24.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:26.0098787Z SingleProcess AUTOTUNE benchmarking takes 0.3254 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:26.4240412Z Autotune Choices Stats: 2025-09-07T09:51:26.4241907Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.041471999138593674, "best_triton_kernel": "triton_convolution2d_226", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:51:26.4782197Z AUTOTUNE convolution(4x1024x14x14, 2048x1024x1x1) 2025-09-07T09:51:26.4782591Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:51:26.4783003Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:26.4783307Z convolution 0.0205 ms 100.0% 2025-09-07T09:51:26.4784147Z triton_convolution2d_226 0.0415 ms 49.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:26.4785425Z triton_convolution2d_227 0.0502 ms 40.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:26.4786587Z triton_convolution2d_228 0.0528 ms 38.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:26.4787726Z triton_convolution2d_223 0.0627 ms 32.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:26.4788879Z triton_convolution2d_229 0.0673 ms 30.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:26.4790731Z triton_convolution2d_224 0.0728 ms 28.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:26.4791887Z triton_convolution2d_225 0.0862 ms 23.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:26.4792788Z SingleProcess AUTOTUNE benchmarking takes 0.1763 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:27.0002544Z Autotune Choices Stats: 2025-09-07T09:51:27.0004412Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02147199958562851, "best_triton_pos": 2, "best_triton_time": 0.03872000053524971, "best_triton_kernel": "triton_convolution2d_240", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:51:27.1743238Z AUTOTUNE convolution(4x1024x7x7, 2048x1024x1x1) 2025-09-07T09:51:27.1743788Z strides: [50176, 49, 7, 1], [1024, 1, 1, 1] 2025-09-07T09:51:27.1744287Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:27.1744742Z convolution 0.0215 ms 100.0% 2025-09-07T09:51:27.1745154Z conv1x1_via_mm 0.0347 ms 62.0% 2025-09-07T09:51:27.1745986Z triton_convolution2d_240 0.0387 ms 55.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:27.1747283Z triton_convolution2d_241 0.0400 ms 53.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:27.1748520Z triton_convolution2d_242 0.0489 ms 43.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:27.1749777Z triton_convolution2d_243 0.0552 ms 38.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:27.1751456Z triton_convolution2d_239 0.0559 ms 38.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:27.1752717Z triton_convolution2d_237 0.0579 ms 37.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:27.1753987Z triton_convolution2d_238 0.0684 ms 31.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:27.1755090Z SingleProcess AUTOTUNE benchmarking takes 0.3279 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:27.8669955Z Autotune Choices Stats: 2025-09-07T09:51:27.8672228Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02304000034928322, "best_triton_pos": 2, "best_triton_time": 0.06976000219583511, "best_triton_kernel": "triton_convolution2d_233", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:51:27.9903906Z AUTOTUNE convolution(4x2048x7x7, 1024x2048x1x1) 2025-09-07T09:51:27.9904510Z strides: [100352, 49, 7, 1], [2048, 1, 1, 1] 2025-09-07T09:51:27.9905051Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:27.9905697Z convolution 0.0230 ms 100.0% 2025-09-07T09:51:27.9905997Z conv1x1_via_mm 0.0331 ms 69.6% 2025-09-07T09:51:27.9906930Z triton_convolution2d_233 0.0698 ms 33.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:27.9908500Z triton_convolution2d_234 0.0708 ms 32.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:27.9910150Z triton_convolution2d_235 0.0899 ms 25.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:27.9912245Z triton_convolution2d_236 0.1022 ms 22.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:27.9913809Z triton_convolution2d_232 0.1022 ms 22.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:27.9915558Z triton_convolution2d_230 0.1097 ms 21.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:27.9917204Z triton_convolution2d_231 0.1266 ms 18.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:27.9918506Z SingleProcess AUTOTUNE benchmarking takes 0.3060 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:43.5080895Z W0907 09:51:43.507000 25364 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:52:04.6136064Z pass 2025-09-07T09:52:09.1572391Z /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. 2025-09-07T09:52:09.1573404Z import pynvml # type: ignore[import] 2025-09-07T09:52:11.9773930Z 2025-09-07T09:52:19.1800604Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:19.1800931Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:52:19.1801190Z cuda train sam 2025-09-07T09:52:19.1812018Z Traceback (most recent call last): 2025-09-07T09:52:19.1812568Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:52:19.1813083Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:52:19.1813683Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:52:19.1814240Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:52:19.1814756Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:52:19.1815218Z torch.autograd.backward( 2025-09-07T09:52:19.1815733Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:52:19.1816200Z _engine_run_backward( 2025-09-07T09:52:19.1816667Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:52:19.1817431Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:52:19.1818011Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:52:19.1818818Z 2025-09-07T09:52:19.1818994Z The above exception was the direct cause of the following exception: 2025-09-07T09:52:19.1819273Z 2025-09-07T09:52:19.1819362Z Traceback (most recent call last): 2025-09-07T09:52:19.1819824Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:52:19.1820392Z ) = runner.load_model( 2025-09-07T09:52:19.1820784Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:52:19.1821335Z self.validate_model(model, example_inputs) 2025-09-07T09:52:19.1821785Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:52:19.1822329Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:52:19.1822610Z RuntimeError: Eager run failed 2025-09-07T09:52:19.1822864Z 2025-09-07T09:52:19.1823190Z eager_fail_to_run 2025-09-07T09:52:20.8945812Z /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. 2025-09-07T09:52:20.8947448Z import pynvml # type: ignore[import] 2025-09-07T09:52:23.4207465Z 2025-09-07T09:52:25.0748879Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:25.0749243Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:52:25.0749558Z cuda train shufflenet_v2_x1_0 2025-09-07T09:52:41.8186239Z Autotune Choices Stats: 2025-09-07T09:52:41.8187443Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_24", "best_kernel_desc": "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", "best_time": 0.006624000146985054, "best_triton_pos": 0} 2025-09-07T09:52:41.8279344Z AUTOTUNE mm(12544x24, 24x58) 2025-09-07T09:52:41.8279740Z strides: [24, 1], [1, 24] 2025-09-07T09:52:41.8280058Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:41.8281447Z triton_mm_24 0.0066 ms 100.0% 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 2025-09-07T09:52:41.8282751Z triton_mm_33 0.0067 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:41.8284086Z triton_mm_26 0.0068 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:41.8285445Z triton_mm_30 0.0068 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:41.8286829Z triton_mm_28 0.0068 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:52:41.8287951Z triton_mm_31 0.0068 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:41.8289272Z triton_mm_36 0.0068 ms 97.6% 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=2, num_warps=8 2025-09-07T09:52:41.8290707Z triton_mm_23 0.0068 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:52:41.8292002Z triton_mm_25 0.0068 ms 97.2% 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 2025-09-07T09:52:41.8293280Z triton_mm_29 0.0068 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:52:41.8294711Z SingleProcess AUTOTUNE benchmarking takes 0.2098 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:52:42.6998403Z Autotune Choices Stats: 2025-09-07T09:52:42.6999760Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_187", "best_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", "best_time": 0.007424000184983015, "best_triton_pos": 0} 2025-09-07T09:52:42.7317740Z AUTOTUNE mm(3136x116, 116x116) 2025-09-07T09:52:42.7318055Z strides: [116, 1], [1, 116] 2025-09-07T09:52:42.7318322Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:42.7319429Z triton_mm_187 0.0074 ms 100.0% 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 2025-09-07T09:52:42.7320738Z triton_mm_195 0.0076 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:42.7321762Z triton_mm_190 0.0079 ms 93.9% 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 2025-09-07T09:52:42.7322754Z triton_mm_191 0.0079 ms 93.9% 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 2025-09-07T09:52:42.7323829Z triton_mm_186 0.0080 ms 92.8% 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 2025-09-07T09:52:42.7324884Z triton_mm_184 0.0081 ms 91.7% 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 2025-09-07T09:52:42.7325999Z triton_mm_185 0.0081 ms 91.7% 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 2025-09-07T09:52:42.7326992Z triton_mm_196 0.0083 ms 89.9% 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 2025-09-07T09:52:42.7327920Z triton_mm_193 0.0084 ms 88.9% 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 2025-09-07T09:52:42.7328842Z triton_mm_192 0.0084 ms 88.2% 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=3, num_warps=4 2025-09-07T09:52:42.7329667Z SingleProcess AUTOTUNE benchmarking takes 0.5873 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:52:43.2395946Z Autotune Choices Stats: 2025-09-07T09:52:43.2397160Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_67", "best_kernel_desc": "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=4", "best_time": 0.006496000103652477, "best_triton_pos": 0} 2025-09-07T09:52:43.2959240Z AUTOTUNE mm(3136x58, 58x58) 2025-09-07T09:52:43.2959619Z strides: [58, 1], [1, 58] 2025-09-07T09:52:43.2959878Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:43.2960997Z triton_mm_67 0.0065 ms 100.0% 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=4 2025-09-07T09:52:43.2962030Z triton_mm_57 0.0067 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:52:43.2963562Z triton_mm_68 0.0068 ms 96.2% 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=4, num_warps=4 2025-09-07T09:52:43.2964544Z triton_mm_59 0.0068 ms 94.9% 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 2025-09-07T09:52:43.2965516Z triton_mm_65 0.0069 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:43.2966561Z triton_mm_64 0.0069 ms 94.0% 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=5, num_warps=4 2025-09-07T09:52:43.2967732Z triton_mm_58 0.0069 ms 93.5% 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 2025-09-07T09:52:43.2968637Z triton_mm_63 0.0070 ms 92.3% 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 2025-09-07T09:52:43.2969609Z triton_mm_73 0.0071 ms 91.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:52:43.2970676Z triton_mm_56 0.0073 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:52:43.2971482Z SingleProcess AUTOTUNE benchmarking takes 0.2843 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:52:43.9017691Z Autotune Choices Stats: 2025-09-07T09:52:43.9018825Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_513", "best_kernel_desc": "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", "best_time": 0.00800000037997961, "best_triton_pos": 0} 2025-09-07T09:52:43.9248456Z AUTOTUNE mm(784x232, 232x232) 2025-09-07T09:52:43.9248778Z strides: [232, 1], [1, 232] 2025-09-07T09:52:43.9249039Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:43.9249957Z triton_mm_513 0.0080 ms 100.0% 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 2025-09-07T09:52:43.9251206Z triton_mm_509 0.0081 ms 99.2% 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 2025-09-07T09:52:43.9252301Z triton_mm_510 0.0082 ms 98.0% 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 2025-09-07T09:52:43.9253395Z triton_mm_508 0.0083 ms 96.5% 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 2025-09-07T09:52:43.9254353Z triton_mm_514 0.0083 ms 96.5% 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=5, num_warps=4 2025-09-07T09:52:43.9255439Z triton_mm_517 0.0086 ms 92.9% 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 2025-09-07T09:52:43.9256442Z triton_mm_507 0.0088 ms 90.6% 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 2025-09-07T09:52:43.9257585Z triton_mm_516 0.0088 ms 90.6% 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 2025-09-07T09:52:43.9258838Z triton_mm_520 0.0088 ms 90.6% 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 2025-09-07T09:52:43.9259993Z triton_mm_518 0.0091 ms 88.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:43.9261037Z SingleProcess AUTOTUNE benchmarking takes 0.2946 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:52:44.4662544Z Autotune Choices Stats: 2025-09-07T09:52:44.4664004Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_229", "best_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", "best_time": 0.0072639998979866505, "best_triton_pos": 0} 2025-09-07T09:52:44.4947616Z AUTOTUNE mm(784x116, 116x116) 2025-09-07T09:52:44.4947950Z strides: [116, 1], [1, 116] 2025-09-07T09:52:44.4948364Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:44.4949046Z triton_mm_229 0.0073 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 2025-09-07T09:52:44.4950668Z triton_mm_223 0.0074 ms 98.3% 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 2025-09-07T09:52:44.4951851Z triton_mm_224 0.0074 ms 97.8% 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 2025-09-07T09:52:44.4952996Z triton_mm_225 0.0075 ms 97.4% 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 2025-09-07T09:52:44.4954149Z triton_mm_230 0.0075 ms 97.0% 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 2025-09-07T09:52:44.4955299Z triton_mm_222 0.0076 ms 95.8% 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 2025-09-07T09:52:44.4956370Z triton_mm_228 0.0076 ms 95.8% 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 2025-09-07T09:52:44.4957327Z triton_mm_233 0.0076 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:44.4958354Z triton_mm_231 0.0076 ms 95.0% 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 2025-09-07T09:52:44.4959328Z triton_mm_235 0.0077 ms 93.8% 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=4, num_warps=8 2025-09-07T09:52:44.4960405Z SingleProcess AUTOTUNE benchmarking takes 0.2750 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:52:45.7802928Z Autotune Choices Stats: 2025-09-07T09:52:45.7804166Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_548", "best_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", "best_time": 0.0072639998979866505, "best_triton_pos": 0} 2025-09-07T09:52:45.7931256Z AUTOTUNE mm(196x232, 232x232) 2025-09-07T09:52:45.7931561Z strides: [232, 1], [1, 232] 2025-09-07T09:52:45.7931799Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:45.7932584Z triton_mm_548 0.0073 ms 100.0% 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 2025-09-07T09:52:45.7934173Z triton_mm_551 0.0075 ms 97.4% 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 2025-09-07T09:52:45.7935256Z triton_mm_547 0.0075 ms 96.6% 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 2025-09-07T09:52:45.7936304Z triton_mm_552 0.0076 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:45.7937448Z triton_mm_546 0.0076 ms 95.8% 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 2025-09-07T09:52:45.7938345Z mm 0.0078 ms 93.4% 2025-09-07T09:52:45.7938983Z triton_mm_545 0.0079 ms 91.9% 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 2025-09-07T09:52:45.7940072Z triton_mm_556 0.0082 ms 89.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:45.7941639Z triton_mm_555 0.0085 ms 85.7% 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 2025-09-07T09:52:45.7942804Z triton_mm_554 0.0089 ms 81.7% 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=4, num_warps=8 2025-09-07T09:52:45.7943758Z SingleProcess AUTOTUNE benchmarking takes 0.5005 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:52:46.9910991Z Autotune Choices Stats: 2025-09-07T09:52:46.9912435Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.011296000331640244, "best_triton_pos": 1, "best_triton_time": 0.015104000456631184, "best_triton_kernel": "triton_convolution2d_4", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:52:47.0015674Z AUTOTUNE convolution(4x3x224x224, 24x3x3x3) 2025-09-07T09:52:47.0016029Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T09:52:47.0016332Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:47.0016631Z convolution 0.0113 ms 100.0% 2025-09-07T09:52:47.0017499Z triton_convolution2d_4 0.0151 ms 74.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:52:47.0018672Z triton_convolution2d_2 0.0173 ms 65.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:52:47.0019823Z triton_convolution2d_0 0.0182 ms 62.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:52:47.0021135Z triton_convolution2d_3 0.0187 ms 60.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:52:47.0022284Z triton_convolution2d_1 0.0250 ms 45.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:52:47.0023528Z triton_convolution2d_5 0.0251 ms 45.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:52:47.0509028Z SingleProcess AUTOTUNE benchmarking takes 0.1019 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:52:47.2415581Z Autotune Choices Stats: 2025-09-07T09:52:47.2416856Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_7", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.00595200015231967, "best_triton_pos": 0} 2025-09-07T09:52:47.2824216Z AUTOTUNE mm(3136x24, 24x58) 2025-09-07T09:52:47.2824505Z strides: [24, 1], [1, 24] 2025-09-07T09:52:47.2824732Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:47.2825951Z triton_mm_7 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:52:47.2827443Z triton_mm_6 0.0060 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:52:47.2828691Z triton_mm_12 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:52:47.2829803Z triton_mm_8 0.0061 ms 97.4% 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 2025-09-07T09:52:47.2831428Z triton_mm_15 0.0061 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:47.2832732Z triton_mm_10 0.0062 ms 96.4% 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=4 2025-09-07T09:52:47.2833840Z triton_mm_13 0.0062 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:52:47.2834899Z triton_mm_16 0.0062 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:52:47.2835853Z triton_mm_9 0.0062 ms 95.4% 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 2025-09-07T09:52:47.2836809Z triton_mm_17 0.0063 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:47.2837677Z SingleProcess AUTOTUNE benchmarking takes 0.2799 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:52:47.6004584Z Autotune Choices Stats: 2025-09-07T09:52:47.6005680Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_666", "best_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", "best_time": 0.00800000037997961, "best_triton_pos": 0} 2025-09-07T09:52:47.6248286Z AUTOTUNE mm(196x464, 464x1024) 2025-09-07T09:52:47.6248556Z strides: [464, 1], [1, 464] 2025-09-07T09:52:47.6248883Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:47.6249596Z triton_mm_666 0.0080 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 2025-09-07T09:52:47.6251291Z triton_mm_662 0.0080 ms 99.6% 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 2025-09-07T09:52:47.6251961Z mm 0.0083 ms 96.5% 2025-09-07T09:52:47.6253008Z triton_mm_661 0.0089 ms 90.3% 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 2025-09-07T09:52:47.6254058Z triton_mm_665 0.0090 ms 88.7% 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 2025-09-07T09:52:47.6255050Z triton_mm_670 0.0091 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:47.6256202Z triton_mm_660 0.0092 ms 87.4% 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 2025-09-07T09:52:47.6257562Z triton_mm_659 0.0097 ms 82.2% 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 2025-09-07T09:52:47.6258568Z triton_mm_669 0.0100 ms 80.1% 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 2025-09-07T09:52:47.6259547Z triton_mm_672 0.0100 ms 79.6% 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 2025-09-07T09:52:47.6260446Z SingleProcess AUTOTUNE benchmarking takes 0.3303 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:52:47.8685647Z Autotune Choices Stats: 2025-09-07T09:52:47.8686880Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_681", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.008704000152647495, "best_triton_pos": 0} 2025-09-07T09:52:47.8978143Z AUTOTUNE addmm(4x1000, 4x1024, 1024x1000) 2025-09-07T09:52:47.8978470Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T09:52:47.8978748Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:52:47.8979362Z triton_mm_681 0.0087 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:52:47.8980738Z triton_mm_685 0.0092 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:47.8981316Z bias_addmm 0.0101 ms 86.3% 2025-09-07T09:52:47.8981862Z triton_mm_689 0.0106 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:47.8982806Z triton_mm_693 0.0109 ms 79.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:52:47.8983653Z triton_mm_680 0.0116 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:52:47.8984469Z triton_mm_679 0.0120 ms 72.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:47.8985305Z triton_mm_678 0.0123 ms 70.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:52:47.8986134Z triton_mm_684 0.0123 ms 70.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:47.8986979Z triton_mm_688 0.0127 ms 68.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:47.8988185Z SingleProcess AUTOTUNE benchmarking takes 0.2722 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:53:01.7410558Z Autotune Choices Stats: 2025-09-07T09:53:01.7411569Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_713", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.0063680000603199005, "best_triton_pos": 0} 2025-09-07T09:53:01.7431794Z AUTOTUNE mm(1000x4, 4x1024) 2025-09-07T09:53:01.7432051Z strides: [1, 1000], [1024, 1] 2025-09-07T09:53:01.7432303Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:01.7433523Z triton_mm_713 0.0064 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:01.7434576Z triton_mm_719 0.0064 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:01.7435577Z triton_mm_715 0.0064 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:01.7436569Z triton_mm_722 0.0064 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:01.7437569Z triton_mm_716 0.0065 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:01.7438550Z triton_mm_718 0.0065 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:01.7439513Z triton_mm_714 0.0065 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:01.7440635Z triton_mm_717 0.0065 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:53:01.7441624Z triton_mm_720 0.0065 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:01.7442582Z triton_mm_721 0.0066 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:01.7443322Z SingleProcess AUTOTUNE benchmarking takes 0.1822 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:53:02.7781498Z Autotune Choices Stats: 2025-09-07T09:53:02.7782974Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.008767999708652496, "best_triton_pos": 1, "best_triton_time": 0.009568000212311745, "best_triton_kernel": "triton_mm_702", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:53:03.0144822Z AUTOTUNE mm(4x1000, 1000x1024) 2025-09-07T09:53:03.0145364Z strides: [1000, 1], [1024, 1] 2025-09-07T09:53:03.0145815Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:03.0146263Z mm 0.0088 ms 100.0% 2025-09-07T09:53:03.0147289Z triton_mm_702 0.0096 ms 91.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:03.0148956Z triton_mm_698 0.0098 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:03.0152497Z triton_mm_706 0.0101 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:03.0153555Z triton_mm_696 0.0114 ms 77.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:03.0154530Z triton_mm_710 0.0115 ms 76.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:03.0155502Z triton_mm_697 0.0116 ms 75.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:03.0156707Z triton_mm_701 0.0116 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:03.0157685Z triton_mm_708 0.0127 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:03.0158659Z triton_mm_705 0.0131 ms 67.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:03.0159503Z SingleProcess AUTOTUNE benchmarking takes 0.4195 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:53:14.9212192Z pass 2025-09-07T09:53:19.1297082Z /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. 2025-09-07T09:53:19.1298194Z import pynvml # type: ignore[import] 2025-09-07T09:53:21.7235481Z 2025-09-07T09:53:22.7064451Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:22.7064997Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:22.7065469Z cuda train soft_actor_critic 2025-09-07T09:53:28.7627401Z Autotune Choices Stats: 2025-09-07T09:53:28.7628463Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_2", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.00598399993032217, "best_triton_pos": 0} 2025-09-07T09:53:28.8261705Z AUTOTUNE mm(256x3, 3x1024) 2025-09-07T09:53:28.8262016Z strides: [3, 1], [1, 3] 2025-09-07T09:53:28.8262245Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:28.8263506Z triton_mm_2 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:28.8264512Z triton_mm_0 0.0060 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:53:28.8265444Z triton_mm_4 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:28.8266338Z triton_mm_1 0.0062 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:28.8267228Z triton_mm_6 0.0062 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:53:28.8268115Z triton_mm_7 0.0062 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:28.8269383Z triton_mm_3 0.0062 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:28.8270499Z triton_mm_5 0.0062 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:28.8271309Z triton_mm_9 0.0064 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:28.8272129Z triton_mm_10 0.0064 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:28.8273111Z SingleProcess AUTOTUNE benchmarking takes 0.2211 seconds and 0.0127 seconds precompiling for 17 choices 2025-09-07T09:53:31.2765516Z Autotune Choices Stats: 2025-09-07T09:53:31.2767282Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_20", "best_kernel_desc": "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", "best_time": 0.009279999881982803, "best_triton_pos": 0} 2025-09-07T09:53:31.2894922Z AUTOTUNE mm(256x1024, 1024x1024) 2025-09-07T09:53:31.2895391Z strides: [1024, 1], [1, 1024] 2025-09-07T09:53:31.2895808Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:31.2896865Z triton_mm_20 0.0093 ms 100.0% 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 2025-09-07T09:53:31.2898589Z triton_mm_24 0.0097 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:31.2899602Z mm 0.0101 ms 91.8% 2025-09-07T09:53:31.2901186Z triton_mm_28 0.0106 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:31.2902108Z triton_mm_19 0.0123 ms 75.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:31.2903081Z triton_mm_34 0.0125 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 2025-09-07T09:53:31.2904005Z triton_mm_23 0.0127 ms 73.2% 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 2025-09-07T09:53:31.2904904Z triton_mm_27 0.0128 ms 72.3% 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 2025-09-07T09:53:31.2905792Z triton_mm_18 0.0130 ms 71.3% 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 2025-09-07T09:53:31.2906679Z triton_mm_17 0.0135 ms 68.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:31.2907466Z SingleProcess AUTOTUNE benchmarking takes 0.7205 seconds and 1.3773 seconds precompiling for 20 choices 2025-09-07T09:53:32.9631506Z Autotune Choices Stats: 2025-09-07T09:53:32.9632586Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_39", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00825599953532219, "best_triton_pos": 0} 2025-09-07T09:53:32.9739664Z AUTOTUNE addmm(256x2, 256x1024, 1024x2) 2025-09-07T09:53:32.9741318Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T09:53:32.9741839Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:53:32.9743115Z triton_mm_39 0.0083 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:32.9744769Z triton_mm_45 0.0085 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:32.9746366Z triton_mm_50 0.0098 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:32.9748303Z triton_mm_37 0.0109 ms 75.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:32.9749853Z triton_mm_42 0.0111 ms 74.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:32.9751768Z triton_mm_38 0.0113 ms 73.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:32.9752811Z triton_mm_36 0.0117 ms 70.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:53:32.9753851Z triton_mm_49 0.0117 ms 70.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:32.9754886Z triton_mm_44 0.0127 ms 64.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:32.9755543Z bias_addmm 0.0133 ms 61.9% 2025-09-07T09:53:32.9756053Z SingleProcess AUTOTUNE benchmarking takes 0.4325 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:53:37.5427633Z Autotune Choices Stats: 2025-09-07T09:53:37.5429342Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_115", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.008128000423312187, "best_triton_pos": 0} 2025-09-07T09:53:37.6663047Z AUTOTUNE mm(1024x256, 256x1024) 2025-09-07T09:53:37.6663433Z strides: [1, 1024], [1024, 1] 2025-09-07T09:53:37.6663714Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:37.6664466Z triton_mm_115 0.0081 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:37.6665148Z mm 0.0084 ms 97.3% 2025-09-07T09:53:37.6665741Z triton_mm_114 0.0084 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=3, num_warps=4 2025-09-07T09:53:37.6666731Z triton_mm_117 0.0084 ms 96.2% 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 2025-09-07T09:53:37.6667730Z triton_mm_113 0.0086 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 2025-09-07T09:53:37.6668712Z triton_mm_110 0.0087 ms 93.4% 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 2025-09-07T09:53:37.6669708Z triton_mm_121 0.0090 ms 90.1% 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 2025-09-07T09:53:37.6674996Z triton_mm_120 0.0091 ms 89.8% 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 2025-09-07T09:53:37.6675984Z triton_mm_116 0.0091 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:37.6676975Z triton_mm_112 0.0092 ms 88.5% 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 2025-09-07T09:53:37.6677828Z SingleProcess AUTOTUNE benchmarking takes 0.6104 seconds and 0.8009 seconds precompiling for 20 choices 2025-09-07T09:53:38.6518534Z Autotune Choices Stats: 2025-09-07T09:53:38.6520641Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_53", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.00598399993032217, "best_triton_pos": 0} 2025-09-07T09:53:38.8316216Z AUTOTUNE mm(256x2, 2x1024) 2025-09-07T09:53:38.8316561Z strides: [2, 1], [1024, 1] 2025-09-07T09:53:38.8316890Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:38.8317755Z triton_mm_53 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:38.8319062Z triton_mm_51 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:53:38.8320711Z triton_mm_52 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:38.8322011Z triton_mm_54 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:38.8323271Z triton_mm_55 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:38.8324529Z triton_mm_56 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:38.8325807Z triton_mm_58 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:38.8327074Z triton_mm_57 0.0061 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:53:38.8328365Z triton_mm_59 0.0063 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:38.8329639Z triton_mm_60 0.0063 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:38.8330912Z SingleProcess AUTOTUNE benchmarking takes 0.4048 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:53:39.5842321Z Autotune Choices Stats: 2025-09-07T09:53:39.5843899Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_88", "best_kernel_desc": "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", "best_time": 0.00902399979531765, "best_triton_pos": 0} 2025-09-07T09:53:39.6043021Z AUTOTUNE mm(256x1024, 1024x1024) 2025-09-07T09:53:39.6043886Z strides: [1024, 1], [1024, 1] 2025-09-07T09:53:39.6044300Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:39.6045371Z triton_mm_88 0.0090 ms 100.0% 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 2025-09-07T09:53:39.6046419Z mm 0.0091 ms 99.3% 2025-09-07T09:53:39.6047358Z triton_mm_92 0.0097 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:39.6048974Z triton_mm_96 0.0108 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:39.6051174Z triton_mm_87 0.0117 ms 76.8% 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 2025-09-07T09:53:39.6052789Z triton_mm_91 0.0119 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 2025-09-07T09:53:39.6054044Z triton_mm_86 0.0122 ms 74.0% 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 2025-09-07T09:53:39.6055326Z triton_mm_102 0.0125 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=5, num_warps=8 2025-09-07T09:53:39.6056610Z triton_mm_95 0.0127 ms 71.2% 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 2025-09-07T09:53:39.6057881Z triton_mm_94 0.0137 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 2025-09-07T09:53:39.6059005Z SingleProcess AUTOTUNE benchmarking takes 0.5473 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:53:40.1335900Z Autotune Choices Stats: 2025-09-07T09:53:40.1337119Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_132", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.007840000092983246, "best_triton_pos": 0} 2025-09-07T09:53:40.2939357Z AUTOTUNE mm(1024x256, 256x3) 2025-09-07T09:53:40.2939789Z strides: [1, 1024], [3, 1] 2025-09-07T09:53:40.2940172Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:40.2941677Z triton_mm_132 0.0078 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:40.2943668Z triton_mm_126 0.0079 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:40.2944992Z triton_mm_123 0.0085 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:53:40.2946284Z triton_mm_129 0.0088 ms 89.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:40.2947576Z triton_mm_137 0.0092 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:40.2948879Z triton_mm_136 0.0094 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:40.2950177Z triton_mm_124 0.0099 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:40.2951583Z mm 0.0101 ms 77.8% 2025-09-07T09:53:40.2952343Z triton_mm_125 0.0106 ms 74.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:40.2953564Z triton_mm_131 0.0106 ms 73.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:40.2954479Z SingleProcess AUTOTUNE benchmarking takes 0.6717 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:53:41.0580696Z Autotune Choices Stats: 2025-09-07T09:53:41.0582275Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_75", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.007135999854654074, "best_triton_pos": 0} 2025-09-07T09:53:41.0800708Z AUTOTUNE mm(2x256, 256x1024) 2025-09-07T09:53:41.0801034Z strides: [1, 2], [1024, 1] 2025-09-07T09:53:41.0801337Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:41.0802121Z triton_mm_75 0.0071 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:41.0803283Z triton_mm_71 0.0072 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:41.0804428Z triton_mm_69 0.0074 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:41.0805568Z triton_mm_70 0.0074 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:41.0806708Z triton_mm_74 0.0075 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:41.0807830Z triton_mm_81 0.0075 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:41.0808956Z triton_mm_83 0.0077 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:41.0810105Z triton_mm_68 0.0080 ms 89.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:53:41.0811398Z triton_mm_78 0.0080 ms 89.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:41.0812534Z triton_mm_77 0.0080 ms 89.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:41.0813512Z SingleProcess AUTOTUNE benchmarking takes 0.5263 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:53:42.8061938Z W0907 09:53:42.805000 34347 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:53:44.0988360Z pass 2025-09-07T09:53:47.0002970Z /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. 2025-09-07T09:53:47.0207724Z import pynvml # type: ignore[import] 2025-09-07T09:53:49.5471804Z 2025-09-07T09:53:50.9353526Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:50.9354002Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:53:50.9354405Z cuda train speech_transformer 2025-09-07T09:54:01.5873273Z W0907 09:54:01.586000 36605 site-packages/torch/_inductor/utils.py:2298] [9/0_1] DeviceCopy in input program 2025-09-07T09:54:07.8748549Z Autotune Choices Stats: 2025-09-07T09:54:07.8749896Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.014015999622642994, "best_triton_pos": 1, "best_triton_time": 0.014527999795973301, "best_triton_kernel": "triton_mm_149", "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"} 2025-09-07T09:54:08.0756540Z AUTOTUNE mm(2040x512, 512x2048) 2025-09-07T09:54:08.0756838Z strides: [512, 1], [1, 512] 2025-09-07T09:54:08.0757107Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:08.0757375Z mm 0.0140 ms 100.0% 2025-09-07T09:54:08.0757978Z triton_mm_149 0.0145 ms 96.5% 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 2025-09-07T09:54:08.0758984Z triton_mm_148 0.0164 ms 85.4% 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 2025-09-07T09:54:08.0759969Z triton_mm_143 0.0178 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 2025-09-07T09:54:08.0761283Z triton_mm_141 0.0181 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=3, num_warps=4 2025-09-07T09:54:08.0762183Z triton_mm_145 0.0185 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=3, num_warps=4 2025-09-07T09:54:08.0763090Z triton_mm_142 0.0187 ms 74.9% 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 2025-09-07T09:54:08.0763988Z triton_mm_146 0.0192 ms 72.9% 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 2025-09-07T09:54:08.0764882Z triton_mm_138 0.0199 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 2025-09-07T09:54:08.0765792Z triton_mm_150 0.0199 ms 70.3% 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 2025-09-07T09:54:08.0766581Z SingleProcess AUTOTUNE benchmarking takes 0.6472 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:54:10.7467591Z Autotune Choices Stats: 2025-09-07T09:54:10.7469295Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_7", "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": 0.00940799992531538, "best_triton_pos": 0} 2025-09-07T09:54:10.7716731Z AUTOTUNE addmm(2040x512, 2040x320, 320x512) 2025-09-07T09:54:10.7717087Z strides: [0, 1], [320, 1], [1, 320] 2025-09-07T09:54:10.7717397Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:54:10.7718080Z triton_mm_7 0.0094 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 2025-09-07T09:54:10.7719082Z triton_mm_11 0.0095 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=3, num_warps=4 2025-09-07T09:54:10.7720709Z triton_mm_12 0.0097 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:10.7721739Z triton_mm_14 0.0099 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:10.7722365Z bias_addmm 0.0101 ms 93.3% 2025-09-07T09:54:10.7722944Z triton_mm_10 0.0102 ms 92.5% 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 2025-09-07T09:54:10.7724082Z triton_mm_17 0.0103 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 2025-09-07T09:54:10.7724981Z triton_mm_18 0.0103 ms 91.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:10.7725869Z triton_mm_9 0.0110 ms 85.7% 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 2025-09-07T09:54:10.7726754Z triton_mm_8 0.0111 ms 85.0% 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 2025-09-07T09:54:10.7727552Z SingleProcess AUTOTUNE benchmarking takes 0.3401 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T09:54:11.1514134Z Autotune Choices Stats: 2025-09-07T09:54:11.1515369Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009247999638319016, "best_triton_pos": 1, "best_triton_time": 0.00940799992531538, "best_triton_kernel": "triton_mm_31", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:54:11.2130508Z AUTOTUNE mm(2040x512, 512x512) 2025-09-07T09:54:11.2131251Z strides: [512, 1], [1, 512] 2025-09-07T09:54:11.2131992Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:11.2132644Z mm 0.0092 ms 100.0% 2025-09-07T09:54:11.2133504Z triton_mm_31 0.0094 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:11.2134950Z triton_mm_30 0.0101 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 2025-09-07T09:54:11.2136381Z triton_mm_26 0.0103 ms 90.0% 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 2025-09-07T09:54:11.2137810Z triton_mm_37 0.0105 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 2025-09-07T09:54:11.2139085Z triton_mm_36 0.0108 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 2025-09-07T09:54:11.2140605Z triton_mm_29 0.0109 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=4, num_warps=8 2025-09-07T09:54:11.2142054Z triton_mm_33 0.0110 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:11.2143511Z triton_mm_27 0.0113 ms 81.6% 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 2025-09-07T09:54:11.2145258Z triton_mm_28 0.0124 ms 74.7% 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 2025-09-07T09:54:11.2146411Z SingleProcess AUTOTUNE benchmarking takes 0.4407 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:54:11.6158088Z Autotune Choices Stats: 2025-09-07T09:54:11.6159131Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_85", "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": 0.01104000024497509, "best_triton_pos": 0} 2025-09-07T09:54:11.6264589Z AUTOTUNE bmm(80x204x64, 80x64x204) 2025-09-07T09:54:11.6265080Z strides: [13056, 64, 1], [13056, 1, 64] 2025-09-07T09:54:11.6266203Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:11.6267326Z triton_bmm_85 0.0110 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 2025-09-07T09:54:11.6268988Z triton_bmm_92 0.0114 ms 96.6% 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 2025-09-07T09:54:11.6270863Z triton_bmm_89 0.0120 ms 91.8% 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 2025-09-07T09:54:11.6272691Z triton_bmm_83 0.0121 ms 91.0% 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 2025-09-07T09:54:11.6273655Z triton_bmm_84 0.0122 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:11.6274620Z triton_bmm_86 0.0123 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=4, num_warps=8 2025-09-07T09:54:11.6275574Z triton_bmm_87 0.0126 ms 87.3% 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 2025-09-07T09:54:11.6276536Z triton_bmm_88 0.0127 ms 87.1% 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 2025-09-07T09:54:11.6277510Z triton_bmm_90 0.0127 ms 86.7% 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 2025-09-07T09:54:11.6278470Z triton_bmm_82 0.0128 ms 86.0% 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 2025-09-07T09:54:11.6279314Z SingleProcess AUTOTUNE benchmarking takes 0.4100 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:54:12.0682625Z Autotune Choices Stats: 2025-09-07T09:54:12.0683611Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_106", "best_kernel_desc": "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=4", "best_time": 0.011648000217974186, "best_triton_pos": 0} 2025-09-07T09:54:12.0949034Z AUTOTUNE bmm(80x204x204, 80x204x64) 2025-09-07T09:54:12.0949390Z strides: [41664, 204, 1], [13056, 64, 1] 2025-09-07T09:54:12.0949733Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.0950927Z triton_bmm_106 0.0116 ms 100.0% 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=4 2025-09-07T09:54:12.0952151Z triton_bmm_104 0.0119 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:12.0953747Z triton_bmm_105 0.0121 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:12.0954950Z triton_bmm_102 0.0123 ms 94.5% 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 2025-09-07T09:54:12.0956138Z triton_bmm_108 0.0124 ms 94.3% 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 2025-09-07T09:54:12.0957631Z triton_bmm_109 0.0125 ms 93.1% 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 2025-09-07T09:54:12.0958841Z triton_bmm_101 0.0136 ms 85.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:54:12.0960053Z triton_bmm_97 0.0138 ms 84.7% 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 2025-09-07T09:54:12.0961411Z triton_bmm_110 0.0141 ms 82.4% 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=2, num_warps=8 2025-09-07T09:54:12.0962598Z triton_bmm_111 0.0144 ms 81.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:12.0963619Z SingleProcess AUTOTUNE benchmarking takes 0.4679 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:54:12.3907359Z Autotune Choices Stats: 2025-09-07T09:54:12.3908480Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_159", "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": 0.019840000197291374, "best_triton_pos": 0} 2025-09-07T09:54:12.4275823Z AUTOTUNE mm(2040x2048, 2048x512) 2025-09-07T09:54:12.4276111Z strides: [2048, 1], [1, 2048] 2025-09-07T09:54:12.4276374Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.4277033Z triton_mm_159 0.0198 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 2025-09-07T09:54:12.4278031Z triton_mm_158 0.0218 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 2025-09-07T09:54:12.4279022Z triton_mm_162 0.0220 ms 90.4% 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 2025-09-07T09:54:12.4280012Z triton_mm_163 0.0221 ms 89.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:12.4281171Z triton_mm_169 0.0225 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 2025-09-07T09:54:12.4282160Z triton_mm_161 0.0256 ms 77.6% 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 2025-09-07T09:54:12.4283122Z triton_mm_165 0.0261 ms 76.0% 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 2025-09-07T09:54:12.4284025Z triton_mm_168 0.0285 ms 69.5% 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 2025-09-07T09:54:12.4285362Z triton_mm_155 0.0290 ms 68.5% 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 2025-09-07T09:54:12.4286267Z triton_mm_164 0.0324 ms 61.1% 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 2025-09-07T09:54:12.4287049Z SingleProcess AUTOTUNE benchmarking takes 0.3305 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:54:12.4896208Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4896655Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4897041Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4897915Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4898194Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4898442Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4898794Z cudagraph partition due to non gpu ops 2025-09-07T09:54:12.4899213Z cudagraph partition due to DeviceCopy ops 2025-09-07T09:54:12.5397215Z cudagraph partition into 2 partitions 2025-09-07T09:54:34.2337878Z W0907 09:54:34.233000 36605 site-packages/torch/_inductor/utils.py:2298] [15/0_1] DeviceCopy in input program 2025-09-07T09:54:39.7669486Z Autotune Choices Stats: 2025-09-07T09:54:39.7671062Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1139", "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": 0.008927999995648861, "best_triton_pos": 0} 2025-09-07T09:54:39.9228903Z AUTOTUNE mm(220x512, 512x2048) 2025-09-07T09:54:39.9229201Z strides: [512, 1], [1, 512] 2025-09-07T09:54:39.9229505Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:39.9230790Z triton_mm_1139 0.0089 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 2025-09-07T09:54:39.9231439Z mm 0.0090 ms 98.9% 2025-09-07T09:54:39.9232027Z triton_mm_1143 0.0095 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:39.9233009Z triton_mm_1138 0.0100 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=8 2025-09-07T09:54:39.9233981Z triton_mm_1142 0.0101 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 2025-09-07T09:54:39.9234962Z triton_mm_1135 0.0104 ms 86.1% 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 2025-09-07T09:54:39.9235938Z triton_mm_1134 0.0106 ms 84.5% 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 2025-09-07T09:54:39.9236914Z triton_mm_1149 0.0108 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:39.9237893Z triton_mm_1145 0.0109 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 2025-09-07T09:54:39.9238867Z triton_mm_1132 0.0109 ms 81.8% 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 2025-09-07T09:54:39.9239730Z SingleProcess AUTOTUNE benchmarking takes 0.3795 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:54:41.0479581Z Autotune Choices Stats: 2025-09-07T09:54:41.0481593Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_929", "best_kernel_desc": "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", "best_time": 0.00774399982765317, "best_triton_pos": 0} 2025-09-07T09:54:41.1573834Z AUTOTUNE mm(220x512, 512x512) 2025-09-07T09:54:41.1574159Z strides: [512, 1], [1, 512] 2025-09-07T09:54:41.1574473Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:41.1575287Z triton_mm_929 0.0077 ms 100.0% 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 2025-09-07T09:54:41.1577059Z triton_mm_933 0.0078 ms 98.8% 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 2025-09-07T09:54:41.1578386Z triton_mm_937 0.0083 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:41.1579608Z triton_mm_928 0.0089 ms 87.4% 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 2025-09-07T09:54:41.1581336Z triton_mm_936 0.0090 ms 85.8% 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 2025-09-07T09:54:41.1582639Z triton_mm_932 0.0092 ms 84.6% 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 2025-09-07T09:54:41.1584005Z triton_mm_927 0.0092 ms 84.3% 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 2025-09-07T09:54:41.1585303Z triton_mm_926 0.0092 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 2025-09-07T09:54:41.1586604Z triton_mm_943 0.0098 ms 78.8% 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 2025-09-07T09:54:41.1587905Z triton_mm_939 0.0100 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=4, num_warps=8 2025-09-07T09:54:41.1589043Z SingleProcess AUTOTUNE benchmarking takes 0.3453 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:54:41.2860879Z Autotune Choices Stats: 2025-09-07T09:54:41.2862178Z {"num_choices": 11, "num_triton_choices": 10, "best_kernel": "triton_bmm_983", "best_kernel_desc": "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", "best_time": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T09:54:41.3948859Z AUTOTUNE bmm(80x22x64, 80x64x22) 2025-09-07T09:54:41.3949200Z strides: [1408, 64, 1], [1408, 1, 64] 2025-09-07T09:54:41.3949565Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:41.3950843Z triton_bmm_983 0.0061 ms 100.0% 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 2025-09-07T09:54:41.3952168Z triton_bmm_985 0.0062 ms 99.5% 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=5, num_warps=4 2025-09-07T09:54:41.3953466Z triton_bmm_988 0.0063 ms 98.0% 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=3, num_warps=4 2025-09-07T09:54:41.3954747Z triton_bmm_989 0.0063 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:41.3956281Z triton_bmm_991 0.0063 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:41.3957563Z triton_bmm_984 0.0065 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:41.3958846Z triton_bmm_990 0.0065 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:41.3960437Z triton_bmm_987 0.0069 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:54:41.3961643Z triton_bmm_986 0.0074 ms 83.5% 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=2, num_warps=4 2025-09-07T09:54:41.3962797Z triton_bmm_982 0.0074 ms 83.1% 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 2025-09-07T09:54:41.3963803Z SingleProcess AUTOTUNE benchmarking takes 0.2349 seconds and 0.0002 seconds precompiling for 11 choices 2025-09-07T09:54:41.5458506Z Autotune Choices Stats: 2025-09-07T09:54:41.5459722Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_bmm_1003", "best_kernel_desc": "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=2, num_warps=8", "best_time": 0.006175999995321035, "best_triton_pos": 0} 2025-09-07T09:54:41.6301334Z AUTOTUNE bmm(80x22x22, 80x22x64) 2025-09-07T09:54:41.6301670Z strides: [484, 22, 1], [1408, 64, 1] 2025-09-07T09:54:41.6302003Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:41.6302824Z triton_bmm_1003 0.0062 ms 100.0% 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=2, num_warps=8 2025-09-07T09:54:41.6304194Z triton_bmm_995 0.0062 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:41.6305413Z triton_bmm_998 0.0063 ms 98.0% 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=3, num_warps=8 2025-09-07T09:54:41.6306631Z triton_bmm_993 0.0063 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:54:41.6307863Z triton_bmm_1001 0.0065 ms 95.5% 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=4, num_warps=8 2025-09-07T09:54:41.6309096Z triton_bmm_1000 0.0067 ms 92.8% 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=3, num_warps=4 2025-09-07T09:54:41.6310585Z triton_bmm_1002 0.0067 ms 92.8% 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=4, num_warps=4 2025-09-07T09:54:41.6311961Z triton_bmm_997 0.0067 ms 92.3% 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=2, num_warps=4 2025-09-07T09:54:41.6313266Z triton_bmm_996 0.0068 ms 91.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:54:41.6314793Z triton_bmm_999 0.0068 ms 91.0% 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=4 2025-09-07T09:54:41.6315942Z SingleProcess AUTOTUNE benchmarking takes 0.2345 seconds and 0.0003 seconds precompiling for 13 choices 2025-09-07T09:54:42.0140966Z Autotune Choices Stats: 2025-09-07T09:54:42.0142174Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_1084", "best_kernel_desc": "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=5, num_warps=4", "best_time": 0.007679999805986881, "best_triton_pos": 0} 2025-09-07T09:54:42.1518115Z AUTOTUNE bmm(80x22x64, 80x64x204) 2025-09-07T09:54:42.1518450Z strides: [1408, 64, 1], [13056, 1, 64] 2025-09-07T09:54:42.1518772Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:42.1519804Z triton_bmm_1084 0.0077 ms 100.0% 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=5, num_warps=4 2025-09-07T09:54:42.1521297Z triton_bmm_1087 0.0077 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:54:42.1522343Z triton_bmm_1088 0.0078 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:42.1523382Z triton_bmm_1081 0.0079 ms 97.6% 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 2025-09-07T09:54:42.1524432Z triton_bmm_1083 0.0079 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:42.1525482Z triton_bmm_1092 0.0080 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:42.1526548Z triton_bmm_1093 0.0080 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:42.1527579Z triton_bmm_1086 0.0081 ms 95.2% 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=2, num_warps=4 2025-09-07T09:54:42.1528614Z triton_bmm_1094 0.0081 ms 95.2% 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=4, num_warps=8 2025-09-07T09:54:42.1529649Z triton_bmm_1082 0.0081 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:42.1530691Z SingleProcess AUTOTUNE benchmarking takes 0.5168 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:54:42.3376108Z Autotune Choices Stats: 2025-09-07T09:54:42.3377116Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_1100", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00825599953532219, "best_triton_pos": 0} 2025-09-07T09:54:42.3926398Z AUTOTUNE bmm(80x22x204, 80x204x64) 2025-09-07T09:54:42.3926699Z strides: [4544, 204, 1], [13056, 64, 1] 2025-09-07T09:54:42.3927015Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:42.3927779Z triton_bmm_1100 0.0083 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:42.3928947Z triton_bmm_1105 0.0084 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:42.3930784Z triton_bmm_1109 0.0085 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:42.3931881Z triton_bmm_1111 0.0085 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:42.3932932Z triton_bmm_1107 0.0085 ms 96.6% 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=4, num_warps=8 2025-09-07T09:54:42.3933990Z triton_bmm_1108 0.0086 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:42.3935219Z triton_bmm_1099 0.0086 ms 95.9% 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 2025-09-07T09:54:42.3936287Z triton_bmm_1104 0.0087 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:54:42.3937342Z triton_bmm_1101 0.0089 ms 92.5% 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=5, num_warps=4 2025-09-07T09:54:42.3938399Z triton_bmm_1098 0.0091 ms 90.5% 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 2025-09-07T09:54:42.3939312Z SingleProcess AUTOTUNE benchmarking takes 0.2403 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T09:54:42.6356385Z Autotune Choices Stats: 2025-09-07T09:54:42.6357693Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010304000228643417, "best_triton_pos": 1, "best_triton_time": 0.010751999914646149, "best_triton_kernel": "triton_mm_1154", "best_triton_kernel_desc": "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"} 2025-09-07T09:54:42.7422856Z AUTOTUNE mm(220x2048, 2048x512) 2025-09-07T09:54:42.7423192Z strides: [2048, 1], [1, 2048] 2025-09-07T09:54:42.7423450Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:42.7423748Z mm 0.0103 ms 100.0% 2025-09-07T09:54:42.7424360Z triton_mm_1154 0.0108 ms 95.8% 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 2025-09-07T09:54:42.7425367Z triton_mm_1158 0.0117 ms 88.0% 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 2025-09-07T09:54:42.7426397Z triton_mm_1162 0.0134 ms 77.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:42.7427387Z triton_mm_1168 0.0174 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 2025-09-07T09:54:42.7428374Z triton_mm_1153 0.0177 ms 58.2% 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 2025-09-07T09:54:42.7429340Z triton_mm_1152 0.0182 ms 56.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:42.7430654Z triton_mm_1157 0.0188 ms 54.9% 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 2025-09-07T09:54:42.7432015Z triton_mm_1151 0.0190 ms 54.3% 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 2025-09-07T09:54:42.7433066Z triton_mm_1161 0.0191 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 2025-09-07T09:54:43.0342801Z SingleProcess AUTOTUNE benchmarking takes 0.3481 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:54:43.0343423Z Autotune Choices Stats: 2025-09-07T09:54:43.0344674Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2393", "best_kernel_desc": "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", "best_time": 0.007840000092983246, "best_triton_pos": 0} 2025-09-07T09:54:43.1453640Z AUTOTUNE mm(220x512, 512x1014) 2025-09-07T09:54:43.1453918Z strides: [512, 1], [1, 512] 2025-09-07T09:54:43.1454170Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:43.1454843Z triton_mm_2393 0.0078 ms 100.0% 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 2025-09-07T09:54:43.1455865Z triton_mm_2397 0.0084 ms 93.9% 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 2025-09-07T09:54:43.1456873Z triton_mm_2392 0.0091 ms 86.0% 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 2025-09-07T09:54:43.1457913Z triton_mm_2401 0.0092 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:43.1458901Z triton_mm_2396 0.0094 ms 83.3% 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 2025-09-07T09:54:43.1459873Z triton_mm_2391 0.0094 ms 83.1% 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 2025-09-07T09:54:43.1462480Z triton_mm_2390 0.0095 ms 82.8% 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 2025-09-07T09:54:43.1463457Z triton_mm_2400 0.0099 ms 79.3% 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 2025-09-07T09:54:43.1464366Z triton_mm_2407 0.0107 ms 73.6% 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 2025-09-07T09:54:43.1465276Z triton_mm_2399 0.0108 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=4, num_warps=8 2025-09-07T09:54:43.1466063Z SingleProcess AUTOTUNE benchmarking takes 0.3398 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:54:43.1776137Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1776449Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1776747Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1777029Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1777308Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1777588Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1777883Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1778162Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1778439Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1778729Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1779274Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1779554Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1779833Z cudagraph partition due to non gpu ops 2025-09-07T09:54:43.1780132Z cudagraph partition due to DeviceCopy ops 2025-09-07T09:54:43.2367878Z cudagraph partition into 2 partitions 2025-09-07T09:54:46.8595780Z W0907 09:54:46.858000 36605 site-packages/torch/_inductor/utils.py:2298] [15/0_1] DeviceCopy in input program 2025-09-07T09:54:57.5144644Z Autotune Choices Stats: 2025-09-07T09:54:57.5146165Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2477", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.0080960001796484, "best_triton_pos": 0} 2025-09-07T09:54:57.5180891Z AUTOTUNE mm(512x220, 220x2048) 2025-09-07T09:54:57.5181692Z strides: [1, 512], [2048, 1] 2025-09-07T09:54:57.5181985Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:57.5182703Z triton_mm_2477 0.0081 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:57.5183828Z triton_mm_2479 0.0081 ms 99.6% 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 2025-09-07T09:54:57.5184830Z triton_mm_2475 0.0082 ms 99.2% 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 2025-09-07T09:54:57.5185807Z triton_mm_2476 0.0082 ms 99.2% 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 2025-09-07T09:54:57.5186677Z triton_mm_2472 0.0083 ms 97.7% 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 2025-09-07T09:54:57.5187243Z mm 0.0084 ms 96.6% 2025-09-07T09:54:57.5187741Z triton_mm_2474 0.0087 ms 92.7% 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 2025-09-07T09:54:57.5188595Z triton_mm_2478 0.0087 ms 92.7% 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=3, num_warps=4 2025-09-07T09:54:57.5189443Z triton_mm_2483 0.0089 ms 91.3% 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=5, num_warps=8 2025-09-07T09:54:57.5190627Z triton_mm_2482 0.0091 ms 88.8% 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 2025-09-07T09:54:57.5191412Z SingleProcess AUTOTUNE benchmarking takes 0.1945 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:54:57.7544407Z Autotune Choices Stats: 2025-09-07T09:54:57.7545369Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2515", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.00800000037997961, "best_triton_pos": 0} 2025-09-07T09:54:57.7601020Z AUTOTUNE mm(2048x220, 220x512) 2025-09-07T09:54:57.7601278Z strides: [1, 2048], [512, 1] 2025-09-07T09:54:57.7601534Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:57.7602202Z triton_mm_2515 0.0080 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:57.7603225Z triton_mm_2513 0.0081 ms 99.2% 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 2025-09-07T09:54:57.7604577Z triton_mm_2514 0.0081 ms 99.2% 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 2025-09-07T09:54:57.7605210Z mm 0.0081 ms 98.8% 2025-09-07T09:54:57.7605786Z triton_mm_2517 0.0082 ms 98.0% 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 2025-09-07T09:54:57.7606762Z triton_mm_2510 0.0083 ms 96.2% 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 2025-09-07T09:54:57.7607930Z triton_mm_2512 0.0086 ms 92.6% 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=3, num_warps=4 2025-09-07T09:54:57.7608911Z triton_mm_2516 0.0088 ms 90.6% 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 2025-09-07T09:54:57.7609899Z triton_mm_2521 0.0089 ms 89.9% 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=5, num_warps=8 2025-09-07T09:54:57.7611208Z triton_mm_2520 0.0091 ms 88.3% 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 2025-09-07T09:54:57.7612077Z SingleProcess AUTOTUNE benchmarking takes 0.1930 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:54:58.0954756Z Autotune Choices Stats: 2025-09-07T09:54:58.0956175Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009056000038981438, "best_triton_pos": 1, "best_triton_time": 0.00940799992531538, "best_triton_kernel": "triton_mm_4596", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:54:58.1536198Z AUTOTUNE mm(2040x512, 512x512) 2025-09-07T09:54:58.1536485Z strides: [512, 1], [512, 1] 2025-09-07T09:54:58.1536757Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:58.1537039Z mm 0.0091 ms 100.0% 2025-09-07T09:54:58.1537686Z triton_mm_4596 0.0094 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:58.1538745Z triton_mm_4595 0.0099 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 2025-09-07T09:54:58.1539734Z triton_mm_4591 0.0101 ms 89.3% 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 2025-09-07T09:54:58.1542222Z triton_mm_4602 0.0103 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=5, num_warps=8 2025-09-07T09:54:58.1543302Z triton_mm_4594 0.0104 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 2025-09-07T09:54:58.1544285Z triton_mm_4598 0.0107 ms 85.0% 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 2025-09-07T09:54:58.1545318Z triton_mm_4601 0.0108 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:58.1546228Z triton_mm_4592 0.0111 ms 81.6% 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 2025-09-07T09:54:58.1547465Z triton_mm_4593 0.0119 ms 76.3% 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 2025-09-07T09:54:58.1548255Z SingleProcess AUTOTUNE benchmarking takes 0.2518 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:17.9315367Z Autotune Choices Stats: 2025-09-07T09:55:17.9316413Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2415", "best_kernel_desc": "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", "best_time": 0.007807999849319458, "best_triton_pos": 0} 2025-09-07T09:55:17.9345289Z AUTOTUNE mm(1014x220, 220x512) 2025-09-07T09:55:17.9345571Z strides: [1, 1014], [512, 1] 2025-09-07T09:55:17.9346398Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:17.9347119Z triton_mm_2415 0.0078 ms 100.0% 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 2025-09-07T09:55:17.9348193Z triton_mm_2416 0.0083 ms 94.6% 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 2025-09-07T09:55:17.9349210Z triton_mm_2419 0.0084 ms 93.5% 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 2025-09-07T09:55:17.9351268Z triton_mm_2418 0.0084 ms 93.1% 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 2025-09-07T09:55:17.9352284Z triton_mm_2422 0.0084 ms 93.1% 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 2025-09-07T09:55:17.9353276Z triton_mm_2410 0.0084 ms 92.4% 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 2025-09-07T09:55:17.9354252Z triton_mm_2417 0.0087 ms 89.4% 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=3, num_warps=4 2025-09-07T09:55:17.9355242Z triton_mm_2420 0.0090 ms 86.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:17.9356234Z triton_mm_2411 0.0092 ms 84.7% 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 2025-09-07T09:55:17.9356860Z mm 0.0096 ms 81.6% 2025-09-07T09:55:17.9357316Z SingleProcess AUTOTUNE benchmarking takes 0.1882 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:18.3336891Z Autotune Choices Stats: 2025-09-07T09:55:18.3337970Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2454", "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": 0.008895999751985073, "best_triton_pos": 0} 2025-09-07T09:55:18.3605456Z AUTOTUNE mm(220x512, 512x2048) 2025-09-07T09:55:18.3605914Z strides: [512, 1], [2048, 1] 2025-09-07T09:55:18.3606203Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:18.3606959Z triton_mm_2454 0.0089 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 2025-09-07T09:55:18.3607662Z mm 0.0089 ms 99.6% 2025-09-07T09:55:18.3608325Z triton_mm_2458 0.0092 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:18.3609925Z triton_mm_2453 0.0097 ms 91.4% 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 2025-09-07T09:55:18.3611416Z triton_mm_2457 0.0101 ms 88.3% 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 2025-09-07T09:55:18.3612326Z triton_mm_2464 0.0102 ms 87.1% 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 2025-09-07T09:55:18.3613220Z triton_mm_2449 0.0103 ms 86.1% 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 2025-09-07T09:55:18.3614380Z triton_mm_2450 0.0104 ms 85.3% 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 2025-09-07T09:55:18.3615295Z triton_mm_2460 0.0104 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=4, num_warps=8 2025-09-07T09:55:18.3616200Z triton_mm_2456 0.0108 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=4, num_warps=8 2025-09-07T09:55:18.3616988Z SingleProcess AUTOTUNE benchmarking takes 0.2165 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:18.8194179Z Autotune Choices Stats: 2025-09-07T09:55:18.8195239Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2549", "best_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", "best_time": 0.006976000033318996, "best_triton_pos": 0} 2025-09-07T09:55:18.8667005Z AUTOTUNE mm(512x220, 220x512) 2025-09-07T09:55:18.8667347Z strides: [1, 512], [512, 1] 2025-09-07T09:55:18.8667615Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:18.8668326Z triton_mm_2549 0.0070 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 2025-09-07T09:55:18.8669383Z triton_mm_2545 0.0073 ms 95.2% 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 2025-09-07T09:55:18.8670873Z triton_mm_2544 0.0076 ms 91.6% 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 2025-09-07T09:55:18.8672012Z triton_mm_2543 0.0077 ms 90.8% 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 2025-09-07T09:55:18.8672638Z mm 0.0077 ms 90.5% 2025-09-07T09:55:18.8673214Z triton_mm_2551 0.0077 ms 90.1% 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 2025-09-07T09:55:18.8674204Z triton_mm_2548 0.0078 ms 89.7% 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 2025-09-07T09:55:18.8675189Z triton_mm_2552 0.0078 ms 89.0% 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 2025-09-07T09:55:18.8676179Z triton_mm_2553 0.0079 ms 87.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:18.8677187Z triton_mm_2555 0.0080 ms 86.9% 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=4, num_warps=8 2025-09-07T09:55:18.8678403Z SingleProcess AUTOTUNE benchmarking takes 0.2318 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:19.2747923Z Autotune Choices Stats: 2025-09-07T09:55:19.2749203Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011231999844312668, "best_triton_pos": 1, "best_triton_time": 0.011839999817311764, "best_triton_kernel": "triton_mm_2651", "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"} 2025-09-07T09:55:19.3219903Z AUTOTUNE mm(512x2040, 2040x512) 2025-09-07T09:55:19.3220178Z strides: [1, 512], [512, 1] 2025-09-07T09:55:19.3220609Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:19.3220877Z mm 0.0112 ms 100.0% 2025-09-07T09:55:19.3221906Z triton_mm_2651 0.0118 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 2025-09-07T09:55:19.3223026Z triton_mm_2647 0.0122 ms 92.4% 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 2025-09-07T09:55:19.3224034Z triton_mm_2655 0.0142 ms 79.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:19.3225015Z triton_mm_2646 0.0178 ms 63.0% 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 2025-09-07T09:55:19.3225991Z triton_mm_2645 0.0184 ms 61.0% 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 2025-09-07T09:55:19.3226977Z triton_mm_2661 0.0184 ms 60.9% 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=5, num_warps=8 2025-09-07T09:55:19.3227965Z triton_mm_2650 0.0189 ms 59.4% 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 2025-09-07T09:55:19.3228934Z triton_mm_2654 0.0194 ms 58.0% 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 2025-09-07T09:55:19.3229932Z triton_mm_2660 0.0212 ms 52.9% 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 2025-09-07T09:55:19.3230997Z SingleProcess AUTOTUNE benchmarking takes 0.2709 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:20.2342733Z Autotune Choices Stats: 2025-09-07T09:55:20.2344577Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_5352", "best_kernel_desc": "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", "best_time": 0.007455999962985516, "best_triton_pos": 0} 2025-09-07T09:55:20.2768762Z AUTOTUNE mm(220x512, 512x512) 2025-09-07T09:55:20.2769181Z strides: [512, 1], [512, 1] 2025-09-07T09:55:20.2769595Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:20.2771172Z triton_mm_5352 0.0075 ms 100.0% 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 2025-09-07T09:55:20.2772606Z triton_mm_5356 0.0076 ms 97.9% 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 2025-09-07T09:55:20.2773232Z mm 0.0078 ms 95.5% 2025-09-07T09:55:20.2773842Z triton_mm_5360 0.0085 ms 87.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:20.2775278Z triton_mm_5355 0.0086 ms 86.3% 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 2025-09-07T09:55:20.2776250Z triton_mm_5351 0.0087 ms 86.0% 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 2025-09-07T09:55:20.2777217Z triton_mm_5350 0.0089 ms 84.1% 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 2025-09-07T09:55:20.2778413Z triton_mm_5359 0.0090 ms 82.6% 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 2025-09-07T09:55:20.2779397Z triton_mm_5349 0.0095 ms 78.2% 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 2025-09-07T09:55:20.2780551Z triton_mm_5358 0.0095 ms 78.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:20.2781457Z SingleProcess AUTOTUNE benchmarking takes 0.2295 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:22.2942293Z Autotune Choices Stats: 2025-09-07T09:55:22.2943479Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_2431", "best_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", "best_time": 0.011071999557316303, "best_triton_pos": 0} 2025-09-07T09:55:22.3401306Z AUTOTUNE mm(220x1014, 1014x512) 2025-09-07T09:55:22.3401618Z strides: [1014, 1], [512, 1] 2025-09-07T09:55:22.3401922Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:22.3402817Z triton_mm_2431 0.0111 ms 100.0% 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 2025-09-07T09:55:22.3404054Z triton_mm_2435 0.0113 ms 98.3% 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 2025-09-07T09:55:22.3405191Z triton_mm_2429 0.0118 ms 94.0% 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 2025-09-07T09:55:22.3406314Z triton_mm_2438 0.0133 ms 83.0% 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 2025-09-07T09:55:22.3407029Z mm 0.0134 ms 82.6% 2025-09-07T09:55:22.3407693Z triton_mm_2428 0.0134 ms 82.4% 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 2025-09-07T09:55:22.3408825Z triton_mm_2439 0.0138 ms 80.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:22.3409945Z triton_mm_2434 0.0140 ms 78.8% 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 2025-09-07T09:55:22.3411472Z triton_mm_2437 0.0142 ms 77.8% 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 2025-09-07T09:55:22.3412649Z triton_mm_2430 0.0146 ms 75.9% 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 2025-09-07T09:55:22.3413858Z SingleProcess AUTOTUNE benchmarking takes 0.2493 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:22.5596254Z Autotune Choices Stats: 2025-09-07T09:55:22.5597470Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01017600018531084, "best_triton_pos": 1, "best_triton_time": 0.010591999627649784, "best_triton_kernel": "triton_mm_2488", "best_triton_kernel_desc": "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"} 2025-09-07T09:55:22.5694748Z AUTOTUNE mm(220x2048, 2048x512) 2025-09-07T09:55:22.5695005Z strides: [2048, 1], [512, 1] 2025-09-07T09:55:22.5695266Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:22.5695543Z mm 0.0102 ms 100.0% 2025-09-07T09:55:22.5696516Z triton_mm_2488 0.0106 ms 96.1% 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 2025-09-07T09:55:22.5697549Z triton_mm_2492 0.0111 ms 91.6% 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 2025-09-07T09:55:22.5698598Z triton_mm_2496 0.0135 ms 75.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:22.5699662Z triton_mm_2487 0.0173 ms 58.8% 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 2025-09-07T09:55:22.5701062Z triton_mm_2486 0.0175 ms 58.1% 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 2025-09-07T09:55:22.5702094Z triton_mm_2502 0.0178 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:22.5703214Z triton_mm_2495 0.0184 ms 55.3% 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 2025-09-07T09:55:22.5704114Z triton_mm_2491 0.0184 ms 55.2% 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 2025-09-07T09:55:22.5705011Z triton_mm_2485 0.0203 ms 50.1% 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 2025-09-07T09:55:22.5705800Z SingleProcess AUTOTUNE benchmarking takes 0.2289 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:22.6912909Z Autotune Choices Stats: 2025-09-07T09:55:22.6913914Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_bmm_2800", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006047999951988459, "best_triton_pos": 0} 2025-09-07T09:55:22.7563247Z AUTOTUNE bmm(80x64x22, 80x22x22) 2025-09-07T09:55:22.7563643Z strides: [1408, 1, 64], [484, 22, 1] 2025-09-07T09:55:22.7563927Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:22.7564641Z triton_bmm_2800 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:22.7565700Z triton_bmm_2799 0.0061 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:22.7566703Z triton_bmm_2802 0.0061 ms 99.0% 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=4 2025-09-07T09:55:22.7568045Z triton_bmm_2804 0.0061 ms 99.0% 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=2, num_warps=4 2025-09-07T09:55:22.7569065Z triton_bmm_2807 0.0061 ms 98.4% 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=4, num_warps=8 2025-09-07T09:55:22.7570041Z triton_bmm_2801 0.0062 ms 97.4% 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 2025-09-07T09:55:22.7571353Z triton_bmm_2808 0.0062 ms 96.9% 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=4, num_warps=4 2025-09-07T09:55:22.7572599Z triton_bmm_2805 0.0063 ms 96.4% 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=3, num_warps=8 2025-09-07T09:55:22.7573519Z triton_bmm_2806 0.0063 ms 96.4% 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=3, num_warps=4 2025-09-07T09:55:22.7574421Z triton_bmm_2809 0.0063 ms 95.9% 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=2, num_warps=8 2025-09-07T09:55:22.7575206Z SingleProcess AUTOTUNE benchmarking takes 0.1799 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:55:22.8745757Z Autotune Choices Stats: 2025-09-07T09:55:22.8746743Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_bmm_2782", "best_kernel_desc": "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=3, num_warps=8", "best_time": 0.006111999973654747, "best_triton_pos": 0} 2025-09-07T09:55:22.8908255Z AUTOTUNE bmm(80x22x22, 80x22x64) 2025-09-07T09:55:22.8908534Z strides: [484, 1, 22], [1408, 64, 1] 2025-09-07T09:55:22.8908813Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:22.8909467Z triton_bmm_2782 0.0061 ms 100.0% 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=3, num_warps=8 2025-09-07T09:55:22.8910803Z triton_bmm_2784 0.0061 ms 99.5% 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=3, num_warps=4 2025-09-07T09:55:22.8911807Z triton_bmm_2785 0.0061 ms 99.5% 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=4, num_warps=8 2025-09-07T09:55:22.8912959Z triton_bmm_2787 0.0061 ms 99.5% 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=2, num_warps=8 2025-09-07T09:55:22.8913944Z triton_bmm_2778 0.0062 ms 98.5% 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 2025-09-07T09:55:22.8914924Z triton_bmm_2779 0.0062 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:22.8915901Z triton_bmm_2777 0.0063 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:22.8916881Z triton_bmm_2781 0.0063 ms 97.4% 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=2, num_warps=4 2025-09-07T09:55:22.8917862Z triton_bmm_2783 0.0063 ms 97.4% 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=4 2025-09-07T09:55:22.8919046Z triton_bmm_2786 0.0063 ms 97.0% 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=4, num_warps=4 2025-09-07T09:55:22.8919895Z SingleProcess AUTOTUNE benchmarking takes 0.1311 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:55:23.1081502Z Autotune Choices Stats: 2025-09-07T09:55:23.1082925Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_2570", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8", "best_time": 0.006912000011652708, "best_triton_pos": 0} 2025-09-07T09:55:23.1227059Z AUTOTUNE bmm(80x204x22, 80x22x64) 2025-09-07T09:55:23.1227432Z strides: [4544, 1, 204], [1408, 64, 1] 2025-09-07T09:55:23.1228082Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:23.1228978Z triton_bmm_2570 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:23.1230472Z triton_bmm_2567 0.0069 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:23.1231798Z triton_bmm_2569 0.0069 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:23.1233106Z triton_bmm_2566 0.0070 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:23.1234409Z triton_bmm_2571 0.0070 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:23.1235723Z triton_bmm_2562 0.0070 ms 98.2% 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 2025-09-07T09:55:23.1237066Z triton_bmm_2563 0.0071 ms 97.7% 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 2025-09-07T09:55:23.1238402Z triton_bmm_2564 0.0071 ms 97.3% 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=4 2025-09-07T09:55:23.1239722Z triton_bmm_2568 0.0071 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:23.1241180Z triton_bmm_2574 0.0071 ms 97.3% 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=2, num_warps=8 2025-09-07T09:55:23.1242353Z SingleProcess AUTOTUNE benchmarking takes 0.1652 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:55:23.2731092Z Autotune Choices Stats: 2025-09-07T09:55:23.2732394Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_2605", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.007104000076651573, "best_triton_pos": 0} 2025-09-07T09:55:23.2987971Z AUTOTUNE bmm(80x64x22, 80x22x204) 2025-09-07T09:55:23.2988301Z strides: [1408, 1, 64], [4544, 204, 1] 2025-09-07T09:55:23.2988630Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:23.2989453Z triton_bmm_2605 0.0071 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:23.2991019Z triton_bmm_2595 0.0072 ms 99.1% 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 2025-09-07T09:55:23.2992720Z triton_bmm_2601 0.0072 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:23.2994019Z triton_bmm_2606 0.0072 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:23.2995318Z triton_bmm_2600 0.0072 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:23.2996770Z triton_bmm_2594 0.0073 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:23.2998057Z triton_bmm_2599 0.0073 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:23.2999362Z triton_bmm_2597 0.0073 ms 97.4% 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=4 2025-09-07T09:55:23.3000797Z triton_bmm_2607 0.0073 ms 97.4% 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=2, num_warps=8 2025-09-07T09:55:23.3002106Z triton_bmm_2596 0.0073 ms 96.9% 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 2025-09-07T09:55:23.3003250Z SingleProcess AUTOTUNE benchmarking takes 0.1756 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:55:23.3786290Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3786703Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3787090Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3787473Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3787854Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3788232Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3788607Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3788987Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3789358Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3789728Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3790098Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3790663Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3791042Z cudagraph partition due to non gpu ops 2025-09-07T09:55:23.3791429Z cudagraph partition due to DeviceCopy ops 2025-09-07T09:55:23.4708282Z cudagraph partition into 2 partitions 2025-09-07T09:55:27.0261292Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/torchbench/torchbenchmark/models/speech_transformer/speech_transformer/transformer/decoder.py", line 126, in torch_dynamo_resume_in_forward_at_120 2025-09-07T09:55:27.0263458Z self.tgt_word_emb(ys_in_pad) * self.x_logit_scale 2025-09-07T09:55:27.0264018Z 2025-09-07T09:55:27.0264025Z 2025-09-07T09:55:28.1841805Z Run failed with return code: -11 2025-09-07T09:55:28.1842147Z Output: None 2025-09-07T09:55:28.1842345Z Error: None 2025-09-07T09:55:28.6759068Z /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. 2025-09-07T09:55:28.6760145Z import pynvml # type: ignore[import] 2025-09-07T09:55:31.1528994Z 2025-09-07T09:55:32.4792539Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:32.4792908Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:55:32.4793881Z cuda train squeezenet1_1 2025-09-07T09:55:41.9163107Z Autotune Choices Stats: 2025-09-07T09:55:41.9164184Z {"num_choices": 17, "num_triton_choices": 15, "best_kernel": "triton_mm_68", "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=4, num_warps=8", "best_time": 0.006560000125318766, "best_triton_pos": 0} 2025-09-07T09:55:41.9446925Z AUTOTUNE addmm(12100x64, 12100x16, 16x64) 2025-09-07T09:55:41.9447386Z strides: [0, 1], [16, 1], [1, 16] 2025-09-07T09:55:41.9447891Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:41.9449022Z triton_mm_68 0.0066 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=4, num_warps=8 2025-09-07T09:55:41.9452131Z triton_mm_60 0.0068 ms 97.2% 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=2, num_warps=4 2025-09-07T09:55:41.9453741Z triton_mm_61 0.0068 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:41.9455258Z triton_mm_69 0.0068 ms 96.7% 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=4, num_warps=4 2025-09-07T09:55:41.9456772Z triton_mm_65 0.0068 ms 96.2% 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=3, num_warps=8 2025-09-07T09:55:41.9458576Z triton_mm_66 0.0068 ms 96.2% 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=5, num_warps=4 2025-09-07T09:55:41.9459545Z triton_mm_64 0.0068 ms 95.8% 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 2025-09-07T09:55:41.9460654Z triton_mm_63 0.0070 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:41.9461615Z triton_mm_62 0.0070 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:41.9462571Z triton_mm_59 0.0071 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 2025-09-07T09:55:41.9463475Z SingleProcess AUTOTUNE benchmarking takes 0.2609 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:55:42.4705563Z Autotune Choices Stats: 2025-09-07T09:55:42.4706575Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_350", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009727999567985535, "best_triton_pos": 0} 2025-09-07T09:55:42.4777237Z AUTOTUNE addmm(676x1000, 676x512, 512x1000) 2025-09-07T09:55:42.4777546Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T09:55:42.4777870Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:42.4778618Z triton_mm_350 0.0097 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:42.4779667Z triton_mm_349 0.0104 ms 93.5% 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 2025-09-07T09:55:42.4781034Z triton_mm_345 0.0104 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 2025-09-07T09:55:42.4782466Z triton_mm_348 0.0112 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 2025-09-07T09:55:42.4783543Z triton_mm_356 0.0112 ms 87.1% 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 2025-09-07T09:55:42.4784515Z triton_mm_352 0.0114 ms 85.4% 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 2025-09-07T09:55:42.4785480Z triton_mm_355 0.0115 ms 84.4% 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 2025-09-07T09:55:42.4786682Z triton_mm_346 0.0116 ms 83.5% 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 2025-09-07T09:55:42.4787709Z triton_mm_339 0.0124 ms 78.4% 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 2025-09-07T09:55:42.4788433Z addmm 0.0125 ms 77.9% 2025-09-07T09:55:42.4788885Z SingleProcess AUTOTUNE benchmarking takes 0.2703 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T09:55:42.9435410Z Autotune Choices Stats: 2025-09-07T09:55:42.9436512Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_146", "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=5, num_warps=4", "best_time": 0.006752000190317631, "best_triton_pos": 0} 2025-09-07T09:55:42.9589562Z AUTOTUNE addmm(2916x128, 2916x32, 32x128) 2025-09-07T09:55:42.9589841Z strides: [0, 1], [32, 1], [1, 32] 2025-09-07T09:55:42.9590144Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:42.9591006Z triton_mm_146 0.0068 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=5, num_warps=4 2025-09-07T09:55:42.9591969Z triton_mm_142 0.0069 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=4 2025-09-07T09:55:42.9592932Z triton_mm_145 0.0069 ms 98.1% 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=8 2025-09-07T09:55:42.9593866Z triton_mm_139 0.0069 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:42.9594819Z triton_mm_144 0.0069 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=2, num_warps=4 2025-09-07T09:55:42.9595767Z triton_mm_140 0.0070 ms 96.3% 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 2025-09-07T09:55:42.9596705Z triton_mm_141 0.0070 ms 95.9% 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 2025-09-07T09:55:42.9597657Z triton_mm_149 0.0071 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:42.9598609Z triton_mm_138 0.0071 ms 94.6% 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 2025-09-07T09:55:42.9599519Z triton_mm_151 0.0072 ms 93.8% 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 2025-09-07T09:55:42.9600865Z SingleProcess AUTOTUNE benchmarking takes 0.2626 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:55:43.4257772Z Autotune Choices Stats: 2025-09-07T09:55:43.4258857Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_7", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2", "best_time": 0.007135999854654074, "best_triton_pos": 0} 2025-09-07T09:55:43.4554497Z AUTOTUNE addmm(12100x16, 12100x64, 64x16) 2025-09-07T09:55:43.4554811Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T09:55:43.4555107Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:43.4556240Z triton_mm_7 0.0071 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:55:43.4557222Z triton_mm_8 0.0072 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:55:43.4558180Z triton_mm_10 0.0072 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:43.4559122Z triton_mm_12 0.0074 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:43.4560063Z triton_mm_14 0.0074 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.4561188Z triton_mm_13 0.0074 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.4562171Z triton_mm_15 0.0074 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:43.4563140Z triton_mm_16 0.0074 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:43.4564140Z triton_mm_18 0.0074 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:43.4565119Z triton_mm_17 0.0075 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.4565971Z SingleProcess AUTOTUNE benchmarking takes 0.2640 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:55:43.9411858Z Autotune Choices Stats: 2025-09-07T09:55:43.9412910Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_57", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.008224000222980976, "best_triton_pos": 0} 2025-09-07T09:55:43.9711183Z AUTOTUNE addmm(12100x16, 12100x128, 128x16) 2025-09-07T09:55:43.9711472Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T09:55:43.9711790Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:43.9712471Z triton_mm_57 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.9713471Z triton_mm_50 0.0083 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.9714731Z triton_mm_58 0.0085 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:43.9715697Z triton_mm_51 0.0085 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.9716642Z triton_mm_52 0.0085 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:43.9717583Z triton_mm_46 0.0086 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:43.9718720Z triton_mm_45 0.0087 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:55:43.9719647Z triton_mm_55 0.0088 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:43.9721000Z triton_mm_53 0.0089 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:43.9721900Z triton_mm_54 0.0089 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:43.9722679Z SingleProcess AUTOTUNE benchmarking takes 0.2509 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:55:44.2760735Z Autotune Choices Stats: 2025-09-07T09:55:44.2761838Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_313", "best_kernel_desc": "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", "best_time": 0.006560000125318766, "best_triton_pos": 0} 2025-09-07T09:55:44.3402867Z AUTOTUNE addmm(676x256, 676x64, 64x256) 2025-09-07T09:55:44.3403347Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T09:55:44.3403847Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:44.3404916Z triton_mm_313 0.0066 ms 100.0% 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 2025-09-07T09:55:44.3406383Z triton_mm_320 0.0066 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 2025-09-07T09:55:44.3407899Z triton_mm_314 0.0067 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 2025-09-07T09:55:44.3409320Z triton_mm_315 0.0067 ms 97.6% 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 2025-09-07T09:55:44.3410204Z triton_mm_316 0.0067 ms 97.6% 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 2025-09-07T09:55:44.3411275Z triton_mm_319 0.0067 ms 97.6% 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 2025-09-07T09:55:44.3412163Z triton_mm_323 0.0069 ms 95.3% 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 2025-09-07T09:55:44.3413057Z triton_mm_324 0.0069 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=4, num_warps=4 2025-09-07T09:55:44.3414342Z triton_mm_318 0.0072 ms 91.1% 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 2025-09-07T09:55:44.3415232Z triton_mm_325 0.0072 ms 91.1% 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 2025-09-07T09:55:44.3416020Z SingleProcess AUTOTUNE benchmarking takes 0.3509 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T09:55:44.8330430Z Autotune Choices Stats: 2025-09-07T09:55:44.8331941Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_225", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.006463999859988689, "best_triton_pos": 0} 2025-09-07T09:55:45.1057910Z AUTOTUNE addmm(676x192, 676x48, 48x192) 2025-09-07T09:55:45.1058261Z strides: [0, 1], [48, 1], [1, 48] 2025-09-07T09:55:45.1058588Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:45.1059758Z triton_mm_225 0.0065 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:45.1061894Z triton_mm_232 0.0065 ms 99.0% 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=5, num_warps=4 2025-09-07T09:55:45.1063618Z triton_mm_231 0.0066 ms 98.5% 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 2025-09-07T09:55:45.1065163Z triton_mm_227 0.0066 ms 97.6% 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 2025-09-07T09:55:45.1066734Z triton_mm_226 0.0068 ms 95.7% 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 2025-09-07T09:55:45.1068273Z triton_mm_228 0.0068 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:45.1069995Z triton_mm_230 0.0069 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:45.1071297Z triton_mm_236 0.0070 ms 92.7% 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=4, num_warps=4 2025-09-07T09:55:45.1072455Z triton_mm_224 0.0070 ms 91.8% 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 2025-09-07T09:55:45.1073622Z triton_mm_235 0.0071 ms 91.0% 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 2025-09-07T09:55:45.1074635Z SingleProcess AUTOTUNE benchmarking takes 0.5371 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T09:55:45.7963442Z Autotune Choices Stats: 2025-09-07T09:55:45.7965266Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_87", "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=3, num_warps=8", "best_time": 0.007104000076651573, "best_triton_pos": 0} 2025-09-07T09:55:45.8054538Z AUTOTUNE addmm(2916x32, 2916x128, 128x32) 2025-09-07T09:55:45.8054971Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T09:55:45.8055429Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:45.8056446Z triton_mm_87 0.0071 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=3, num_warps=8 2025-09-07T09:55:45.8058280Z triton_mm_90 0.0072 ms 99.1% 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=3, num_warps=4 2025-09-07T09:55:45.8059825Z triton_mm_82 0.0072 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:45.8061630Z triton_mm_88 0.0073 ms 96.9% 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=3, num_warps=4 2025-09-07T09:55:45.8063409Z triton_mm_81 0.0074 ms 96.5% 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 2025-09-07T09:55:45.8064876Z triton_mm_83 0.0074 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:45.8066310Z triton_mm_89 0.0074 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:45.8067747Z triton_mm_95 0.0075 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:45.8069189Z triton_mm_96 0.0075 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:45.8070468Z triton_mm_92 0.0076 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:45.8071480Z SingleProcess AUTOTUNE benchmarking takes 0.2619 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:55:46.3443639Z Autotune Choices Stats: 2025-09-07T09:55:46.3445269Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_132", "best_kernel_desc": "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=4, num_warps=4", "best_time": 0.0077760000713169575, "best_triton_pos": 0} 2025-09-07T09:55:46.5478593Z AUTOTUNE addmm(2916x32, 2916x256, 256x32) 2025-09-07T09:55:46.5479019Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T09:55:46.5479520Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:46.5480986Z triton_mm_132 0.0078 ms 100.0% 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=4, num_warps=4 2025-09-07T09:55:46.5482387Z triton_mm_125 0.0078 ms 99.6% 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 2025-09-07T09:55:46.5483712Z triton_mm_128 0.0080 ms 96.8% 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=3, num_warps=8 2025-09-07T09:55:46.5485005Z triton_mm_131 0.0080 ms 96.8% 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=3, num_warps=4 2025-09-07T09:55:46.5486286Z triton_mm_123 0.0081 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:46.5487580Z triton_mm_122 0.0082 ms 95.3% 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 2025-09-07T09:55:46.5488923Z triton_mm_124 0.0082 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:46.5490767Z triton_mm_136 0.0082 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:46.5492062Z triton_mm_137 0.0082 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:46.5493336Z triton_mm_130 0.0084 ms 92.4% 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=4, num_warps=8 2025-09-07T09:55:46.5494450Z SingleProcess AUTOTUNE benchmarking takes 0.4382 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:55:46.8130499Z Autotune Choices Stats: 2025-09-07T09:55:46.8131756Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_254", "best_kernel_desc": "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", "best_time": 0.007424000184983015, "best_triton_pos": 0} 2025-09-07T09:55:47.0188042Z AUTOTUNE addmm(676x64, 676x384, 384x64) 2025-09-07T09:55:47.0188522Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T09:55:47.0189107Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:47.0190564Z triton_mm_254 0.0074 ms 100.0% 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 2025-09-07T09:55:47.0191763Z triton_mm_262 0.0076 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 2025-09-07T09:55:47.0192928Z triton_mm_258 0.0080 ms 92.4% 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 2025-09-07T09:55:47.0193672Z bias_addmm 0.0082 ms 90.6% 2025-09-07T09:55:47.0194384Z triton_mm_251 0.0084 ms 87.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:47.0195527Z triton_mm_253 0.0084 ms 87.9% 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 2025-09-07T09:55:47.0196664Z triton_mm_252 0.0085 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 2025-09-07T09:55:47.0197803Z triton_mm_261 0.0085 ms 87.5% 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 2025-09-07T09:55:47.0198951Z triton_mm_257 0.0087 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 2025-09-07T09:55:47.0200037Z triton_mm_267 0.0087 ms 85.3% 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 2025-09-07T09:55:47.0201065Z SingleProcess AUTOTUNE benchmarking takes 0.4523 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:47.5273030Z Autotune Choices Stats: 2025-09-07T09:55:47.7194165Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_298", "best_kernel_desc": "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", "best_time": 0.007840000092983246, "best_triton_pos": 0} 2025-09-07T09:55:47.7195546Z AUTOTUNE addmm(676x64, 676x512, 512x64) 2025-09-07T09:55:47.7196264Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T09:55:47.7196677Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:47.7197602Z triton_mm_298 0.0078 ms 100.0% 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 2025-09-07T09:55:47.7198914Z triton_mm_306 0.0080 ms 98.0% 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 2025-09-07T09:55:47.7200142Z triton_mm_302 0.0081 ms 97.2% 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 2025-09-07T09:55:47.7201213Z bias_addmm 0.0082 ms 96.1% 2025-09-07T09:55:47.7202150Z triton_mm_297 0.0091 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:47.7203318Z triton_mm_311 0.0091 ms 86.0% 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 2025-09-07T09:55:47.7204455Z triton_mm_305 0.0092 ms 85.7% 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 2025-09-07T09:55:47.7205622Z triton_mm_296 0.0092 ms 85.4% 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 2025-09-07T09:55:47.7206767Z triton_mm_301 0.0092 ms 85.4% 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 2025-09-07T09:55:47.7207910Z triton_mm_295 0.0092 ms 84.8% 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 2025-09-07T09:55:47.7208923Z SingleProcess AUTOTUNE benchmarking takes 0.4357 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:47.9792982Z Autotune Choices Stats: 2025-09-07T09:55:47.9794179Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_166", "best_kernel_desc": "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", "best_time": 0.007199999876320362, "best_triton_pos": 0} 2025-09-07T09:55:47.9861645Z AUTOTUNE addmm(676x48, 676x256, 256x48) 2025-09-07T09:55:47.9861964Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T09:55:47.9862292Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:47.9863161Z triton_mm_166 0.0072 ms 100.0% 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 2025-09-07T09:55:47.9864280Z triton_mm_174 0.0074 ms 97.0% 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 2025-09-07T09:55:47.9865362Z triton_mm_170 0.0075 ms 95.7% 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 2025-09-07T09:55:47.9866401Z triton_mm_169 0.0076 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 2025-09-07T09:55:47.9867426Z triton_mm_173 0.0076 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=4 2025-09-07T09:55:47.9868456Z triton_mm_165 0.0077 ms 93.8% 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 2025-09-07T09:55:47.9870542Z triton_mm_163 0.0077 ms 93.4% 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 2025-09-07T09:55:47.9871310Z bias_addmm 0.0078 ms 92.6% 2025-09-07T09:55:47.9872019Z triton_mm_164 0.0078 ms 91.8% 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 2025-09-07T09:55:47.9873160Z triton_mm_172 0.0080 ms 90.4% 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 2025-09-07T09:55:47.9874168Z SingleProcess AUTOTUNE benchmarking takes 0.2476 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:48.4914257Z Autotune Choices Stats: 2025-09-07T09:55:48.4915743Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_210", "best_kernel_desc": "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", "best_time": 0.007584000006318092, "best_triton_pos": 0} 2025-09-07T09:55:48.5786905Z AUTOTUNE addmm(676x48, 676x384, 384x48) 2025-09-07T09:55:48.5787248Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T09:55:48.5787572Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:48.5788313Z triton_mm_210 0.0076 ms 100.0% 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 2025-09-07T09:55:48.5789347Z triton_mm_214 0.0077 ms 97.9% 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 2025-09-07T09:55:48.5790800Z triton_mm_218 0.0077 ms 97.9% 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=4, num_warps=4 2025-09-07T09:55:48.5791782Z triton_mm_209 0.0083 ms 91.2% 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 2025-09-07T09:55:48.5792392Z bias_addmm 0.0084 ms 90.8% 2025-09-07T09:55:48.5792982Z triton_mm_217 0.0084 ms 89.8% 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 2025-09-07T09:55:48.5793943Z triton_mm_207 0.0085 ms 89.4% 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 2025-09-07T09:55:48.5794900Z triton_mm_208 0.0085 ms 89.1% 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 2025-09-07T09:55:48.5795854Z triton_mm_213 0.0085 ms 88.8% 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 2025-09-07T09:55:48.5796814Z triton_mm_223 0.0087 ms 87.1% 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 2025-09-07T09:55:48.5797658Z SingleProcess AUTOTUNE benchmarking takes 0.3315 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:49.1320125Z Autotune Choices Stats: 2025-09-07T09:55:49.1322732Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.016063999384641647, "best_triton_pos": 1, "best_triton_time": 0.016256000846624374, "best_triton_kernel": "triton_convolution2d_4", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:55:49.1743972Z AUTOTUNE convolution(4x3x224x224, 64x3x3x3) 2025-09-07T09:55:49.1745075Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T09:55:49.1745544Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.1746002Z convolution 0.0161 ms 100.0% 2025-09-07T09:55:49.1747225Z triton_convolution2d_4 0.0163 ms 98.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.1749216Z triton_convolution2d_3 0.0183 ms 87.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.1751383Z triton_convolution2d_0 0.0183 ms 87.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.1752831Z triton_convolution2d_5 0.0220 ms 73.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.1754060Z triton_convolution2d_2 0.0261 ms 61.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.1755280Z triton_convolution2d_1 0.0460 ms 34.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.1756285Z SingleProcess AUTOTUNE benchmarking takes 0.1737 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:55:49.2618422Z Autotune Choices Stats: 2025-09-07T09:55:49.2620480Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_37", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:55:49.3103361Z AUTOTUNE convolution(4x16x55x55, 64x16x3x3) 2025-09-07T09:55:49.3103740Z strides: [48400, 1, 880, 16], [144, 1, 48, 16] 2025-09-07T09:55:49.3104045Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.3104821Z triton_convolution2d_37 0.0102 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.3106060Z triton_convolution2d_41 0.0108 ms 95.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.3107276Z triton_convolution2d_40 0.0112 ms 91.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.3108034Z convolution 0.0114 ms 90.1% 2025-09-07T09:55:49.3108755Z triton_convolution2d_42 0.0117 ms 87.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.3109969Z triton_convolution2d_38 0.0124 ms 82.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.3111203Z triton_convolution2d_39 0.0157 ms 65.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.3112014Z SingleProcess AUTOTUNE benchmarking takes 0.1344 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:55:49.4086746Z Autotune Choices Stats: 2025-09-07T09:55:49.4088993Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009119999594986439, "best_triton_pos": 1, "best_triton_time": 0.011008000001311302, "best_triton_kernel": "triton_convolution2d_118", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:49.4376661Z AUTOTUNE convolution(4x32x27x27, 128x32x3x3) 2025-09-07T09:55:49.4377004Z strides: [23328, 1, 864, 32], [288, 1, 96, 32] 2025-09-07T09:55:49.4377319Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.4377626Z convolution 0.0091 ms 100.0% 2025-09-07T09:55:49.4378643Z triton_convolution2d_118 0.0110 ms 82.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.4379985Z triton_convolution2d_119 0.0119 ms 76.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.4382563Z triton_convolution2d_117 0.0124 ms 73.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.4384689Z triton_convolution2d_120 0.0138 ms 66.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.4386678Z triton_convolution2d_114 0.0144 ms 63.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.4388650Z triton_convolution2d_115 0.0171 ms 53.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.4390861Z triton_convolution2d_116 0.0249 ms 36.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.4391843Z SingleProcess AUTOTUNE benchmarking takes 0.1262 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:49.5383503Z Autotune Choices Stats: 2025-09-07T09:55:49.5385674Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009983999654650688, "best_triton_pos": 1, "best_triton_time": 0.01740800030529499, "best_triton_kernel": "triton_convolution2d_203", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:49.5469953Z AUTOTUNE convolution(4x48x13x13, 192x48x3x3) 2025-09-07T09:55:49.5470925Z strides: [8112, 1, 624, 48], [432, 1, 144, 48] 2025-09-07T09:55:49.5471243Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.5471538Z convolution 0.0100 ms 100.0% 2025-09-07T09:55:49.5472331Z triton_convolution2d_203 0.0174 ms 57.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.5473667Z triton_convolution2d_204 0.0178 ms 56.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.5475014Z triton_convolution2d_202 0.0223 ms 44.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.5476555Z triton_convolution2d_199 0.0226 ms 44.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.5477889Z triton_convolution2d_205 0.0233 ms 42.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.5479227Z triton_convolution2d_200 0.0263 ms 38.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.5480834Z triton_convolution2d_201 0.0365 ms 27.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.5481835Z SingleProcess AUTOTUNE benchmarking takes 0.1070 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:49.6544037Z Autotune Choices Stats: 2025-09-07T09:55:49.6546327Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010975999757647514, "best_triton_pos": 1, "best_triton_time": 0.016416000202298164, "best_triton_kernel": "triton_convolution2d_291", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:49.7087050Z AUTOTUNE convolution(4x64x13x13, 256x64x3x3) 2025-09-07T09:55:49.7087617Z strides: [10816, 1, 832, 64], [576, 1, 192, 64] 2025-09-07T09:55:49.7088134Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.7088610Z convolution 0.0110 ms 100.0% 2025-09-07T09:55:49.7089831Z triton_convolution2d_291 0.0164 ms 66.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.7091697Z triton_convolution2d_290 0.0186 ms 59.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.7092941Z triton_convolution2d_292 0.0193 ms 57.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.7094189Z triton_convolution2d_293 0.0231 ms 47.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.7095439Z triton_convolution2d_288 0.0284 ms 38.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.7096692Z triton_convolution2d_287 0.0289 ms 37.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.7097932Z triton_convolution2d_289 0.0482 ms 22.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.7098912Z SingleProcess AUTOTUNE benchmarking takes 0.1596 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:56:03.3047018Z pass 2025-09-07T09:56:06.1368576Z accuracy pass_rate=71.43% 2025-09-07T09:56:06.1379879Z calls_captured gmean=0.00x mean=345.857x 2025-09-07T09:56:06.1383310Z unique_graphs gmean=0.00x mean=2.000x 2025-09-07T09:56:06.1386914Z graph_breaks gmean=0.00x mean=4.571x 2025-09-07T09:56:06.1390112Z unique_graph_breaks gmean=0.00x mean=3.571x 2025-09-07T09:56:06.1393709Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:56:06.1396889Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:56:06.1400124Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:56:06.1401577Z compilation_latency mean=31.281 seconds 2025-09-07T09:56:06.9766346Z + [[ 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* ]] 2025-09-07T09:56:06.9767734Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:56:06.9768651Z + for target in "${targets[@]}" 2025-09-07T09:56:06.9768966Z + target_flag=('--performance') 2025-09-07T09:56:06.9769245Z + local target_flag 2025-09-07T09:56:06.9769501Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:56:06.9769819Z + target_flag+=(--cold-start-latency) 2025-09-07T09:56:06.9771658Z + [[ 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* ]] 2025-09-07T09:56:06.9773789Z + [[ 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* ]] 2025-09-07T09:56:06.9776036Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv 2025-09-07T09:56:07.4733480Z /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. 2025-09-07T09:56:07.4734566Z import pynvml # type: ignore[import] 2025-09-07T09:56:11.2084753Z /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. 2025-09-07T09:56:11.2085984Z import pynvml # type: ignore[import] 2025-09-07T09:56:13.6761756Z 2025-09-07T09:56:15.6391746Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:56:15.6392124Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:56:15.6392395Z cuda train resnet50 2025-09-07T09:56:49.2600854Z W0907 09:56:49.259000 48969 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:57:09.4641249Z 2025-09-07T09:57:09.5812095Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T09:57:20.3547237Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:57:20.3547973Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:57:20.3548575Z return self._call_impl(*args, **kwargs) 2025-09-07T09:57:20.3549137Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:57:20.3549715Z return forward_call(*args, **kwargs) 2025-09-07T09:57:20.3550445Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:57:20.3551096Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:57:20.3551484Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:57:20.3551746Z 2025-09-07T09:57:20.3551947Z The above exception was the direct cause of the following exception: 2025-09-07T09:57:20.3552251Z 2025-09-07T09:57:20.3552360Z Traceback (most recent call last): 2025-09-07T09:57:20.3552807Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:57:20.3553256Z ) = runner.load_model( 2025-09-07T09:57:20.3553714Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:57:20.3554245Z self.validate_model(model, example_inputs) 2025-09-07T09:57:20.3554769Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:57:20.3555570Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:57:20.3555900Z RuntimeError: Eager run failed 2025-09-07T09:57:20.3556081Z 2025-09-07T09:57:20.3556169Z eager_fail_to_run 2025-09-07T09:57:21.9457088Z /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. 2025-09-07T09:57:21.9458185Z import pynvml # type: ignore[import] 2025-09-07T09:57:24.4214435Z 2025-09-07T09:57:26.4748070Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:57:26.4748407Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:57:26.4748691Z cuda train resnext50_32x4d 2025-09-07T09:57:56.3561738Z W0907 09:57:56.355000 51832 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:58:16.3386642Z 2025-09-07T09:58:16.4574882Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:59:32.9445513Z 2025-09-07T09:59:33.0457011Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:02:13.7211560Z 2025-09-07T10:02:13.8455439Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:02:24.7680458Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:02:24.7681492Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:02:24.7682353Z return self._call_impl(*args, **kwargs) 2025-09-07T10:02:24.7683539Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:02:24.7684238Z return forward_call(*args, **kwargs) 2025-09-07T10:02:24.7684898Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:02:24.7685591Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:02:24.7686016Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:02:24.7686302Z 2025-09-07T10:02:24.7686524Z The above exception was the direct cause of the following exception: 2025-09-07T10:02:24.7686862Z 2025-09-07T10:02:24.7686977Z Traceback (most recent call last): 2025-09-07T10:02:24.7687476Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:02:24.7687978Z ) = runner.load_model( 2025-09-07T10:02:24.7688761Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:02:24.7689352Z self.validate_model(model, example_inputs) 2025-09-07T10:02:24.7689921Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:02:24.7690635Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:02:24.7690989Z RuntimeError: Eager run failed 2025-09-07T10:02:24.7691181Z 2025-09-07T10:02:24.7691273Z eager_fail_to_run 2025-09-07T10:02:26.4454049Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:02:26.4455530Z import pynvml # type: ignore[import] 2025-09-07T10:02:28.9799721Z 2025-09-07T10:02:31.2658987Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:02:31.2659341Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:02:31.2659605Z cuda train resnext50_32x4d 2025-09-07T10:03:02.2116547Z W0907 10:03:02.210000 66776 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:03:23.4163448Z 2025-09-07T10:03:23.5236540Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:04:39.6763566Z 2025-09-07T10:04:39.7777587Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:07:16.8395757Z 2025-09-07T10:07:17.2529578Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:07:27.8419912Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:07:27.8420731Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:07:27.8421193Z return self._call_impl(*args, **kwargs) 2025-09-07T10:07:27.8421628Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:07:27.8422065Z return forward_call(*args, **kwargs) 2025-09-07T10:07:27.8422522Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:07:27.8423084Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:07:27.8423377Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:07:27.8423582Z 2025-09-07T10:07:27.8423739Z The above exception was the direct cause of the following exception: 2025-09-07T10:07:27.8423974Z 2025-09-07T10:07:27.8424058Z Traceback (most recent call last): 2025-09-07T10:07:27.8424404Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:07:27.8424749Z ) = runner.load_model( 2025-09-07T10:07:27.8425105Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:07:27.8425508Z self.validate_model(model, example_inputs) 2025-09-07T10:07:27.8425913Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:07:27.8426322Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:07:27.8426838Z RuntimeError: Eager run failed 2025-09-07T10:07:27.8426983Z 2025-09-07T10:07:27.8427051Z eager_fail_to_run 2025-09-07T10:07:29.4517114Z /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. 2025-09-07T10:07:29.4518546Z import pynvml # type: ignore[import] 2025-09-07T10:07:31.9387345Z 2025-09-07T10:07:34.2389929Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:07:34.2390659Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:07:34.2390996Z cuda train resnext50_32x4d 2025-09-07T10:08:11.1082993Z W0907 10:08:11.107000 82404 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:08:31.9769913Z 2025-09-07T10:08:32.0807641Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:10:02.1234303Z 2025-09-07T10:10:02.2244998Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:10:09.4636034Z torchbench_main() 2025-09-07T10:10:09.4636475Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T10:10:09.4637015Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T10:10:09.4637461Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T10:10:09.4640968Z process_entry(0, runner, original_dir, args) 2025-09-07T10:10:09.4641516Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T10:10:09.4643655Z result = run(runner, args, original_dir) 2025-09-07T10:10:09.4644100Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4251, in run 2025-09-07T10:10:09.4647367Z assert marked, f"nothing in example_inputs had a dim with {batch_size}" 2025-09-07T10:10:09.4648327Z AssertionError: nothing in example_inputs had a dim with 32 2025-09-07T10:10:10.3868755Z Run failed with return code: 1 2025-09-07T10:10:10.3869051Z Output: None 2025-09-07T10:10:10.3869249Z Error: None 2025-09-07T10:10:10.8831377Z /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. 2025-09-07T10:10:10.8832757Z import pynvml # type: ignore[import] 2025-09-07T10:10:13.4388227Z 2025-09-07T10:10:14.8493557Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:10:14.8493965Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:10:14.8494328Z cuda train squeezenet1_1 2025-09-07T10:10:35.5020519Z 2025-09-07T10:10:35.7085966Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:12:30.1878853Z 2025-09-07T10:12:30.2888980Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:12:41.4147726Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:12:41.4148450Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:12:41.4149056Z return self._call_impl(*args, **kwargs) 2025-09-07T10:12:41.4149606Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:12:41.4150178Z return forward_call(*args, **kwargs) 2025-09-07T10:12:41.4150894Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:12:41.4151857Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:12:41.4152145Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:12:41.4152352Z 2025-09-07T10:12:41.4152506Z The above exception was the direct cause of the following exception: 2025-09-07T10:12:41.4152742Z 2025-09-07T10:12:41.4152823Z Traceback (most recent call last): 2025-09-07T10:12:41.4153162Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:12:41.4153507Z ) = runner.load_model( 2025-09-07T10:12:41.4153845Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:12:41.4154245Z self.validate_model(model, example_inputs) 2025-09-07T10:12:41.4154636Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:12:41.4155263Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:12:41.4155510Z RuntimeError: Eager run failed 2025-09-07T10:12:41.4155655Z 2025-09-07T10:12:41.4155721Z eager_fail_to_run 2025-09-07T10:12:43.0728318Z /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. 2025-09-07T10:12:43.0729780Z import pynvml # type: ignore[import] 2025-09-07T10:12:45.5767760Z 2025-09-07T10:12:47.8590861Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:12:47.8591245Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:12:47.8591549Z cuda train resnext50_32x4d 2025-09-07T10:13:40.3829950Z W0907 10:13:40.382000 96437 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:14:10.6899056Z 2025-09-07T10:14:10.8214240Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:16:08.4261608Z 2025-09-07T10:16:08.5298357Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:19:55.2168355Z 2025-09-07T10:19:55.3407714Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:20:06.3096939Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:20:06.3097573Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:20:06.3098100Z return self._call_impl(*args, **kwargs) 2025-09-07T10:20:06.3098584Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:20:06.3099075Z return forward_call(*args, **kwargs) 2025-09-07T10:20:06.3099573Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:20:06.3100044Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:20:06.3100491Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:20:06.3100700Z 2025-09-07T10:20:06.3100865Z The above exception was the direct cause of the following exception: 2025-09-07T10:20:06.3101100Z 2025-09-07T10:20:06.3101182Z Traceback (most recent call last): 2025-09-07T10:20:06.3101528Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:20:06.3101879Z ) = runner.load_model( 2025-09-07T10:20:06.3102225Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:20:06.3102628Z self.validate_model(model, example_inputs) 2025-09-07T10:20:06.3103137Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:20:06.3103541Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:20:06.3103804Z RuntimeError: Eager run failed 2025-09-07T10:20:06.3103936Z 2025-09-07T10:20:06.3104017Z eager_fail_to_run 2025-09-07T10:20:07.9969438Z /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. 2025-09-07T10:20:07.9971780Z import pynvml # type: ignore[import] 2025-09-07T10:20:10.4626611Z 2025-09-07T10:20:12.7423591Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:20:12.7423956Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:20:12.7424257Z cuda train resnext50_32x4d 2025-09-07T10:20:29.5156455Z Autotune Choices Stats: 2025-09-07T10:20:29.5157840Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.05686400085687637, "best_triton_pos": 0} 2025-09-07T10:20:29.5168121Z AUTOTUNE convolution(8x3x224x224, 64x3x7x7) 2025-09-07T10:20:29.5168469Z strides: [150528, 50176, 224, 1], [147, 49, 7, 1] 2025-09-07T10:20:29.5168789Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:29.5169624Z triton_convolution2d_5 0.0569 ms 100.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:20:29.5171072Z triton_convolution2d_1 0.0614 ms 92.6% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:20:29.5172671Z triton_convolution2d_3 0.0635 ms 89.5% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:20:29.5173507Z convolution 0.0657 ms 86.5% 2025-09-07T10:20:29.5174266Z triton_convolution2d_0 0.0728 ms 78.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:20:29.5175561Z triton_convolution2d_4 0.0870 ms 65.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:20:29.5176844Z triton_convolution2d_2 0.1824 ms 31.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:20:29.5177886Z SingleProcess AUTOTUNE benchmarking takes 0.1293 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T10:20:29.6475499Z Autotune Choices Stats: 2025-09-07T10:20:29.6476868Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_10", "best_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.009568000212311745, "best_triton_pos": 0} 2025-09-07T10:20:29.6487910Z AUTOTUNE convolution(8x64x56x56, 128x64x1x1) 2025-09-07T10:20:29.6488248Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T10:20:29.6488553Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:29.6489367Z triton_convolution2d_10 0.0096 ms 100.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.6490175Z convolution 0.0100 ms 95.8% 2025-09-07T10:20:29.6491274Z triton_convolution2d_11 0.0100 ms 95.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.6492620Z triton_convolution2d_9 0.0105 ms 91.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.6493931Z triton_convolution2d_6 0.0106 ms 90.3% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.6495246Z triton_convolution2d_12 0.0113 ms 84.9% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.6496555Z triton_convolution2d_7 0.0120 ms 79.7% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.6498057Z triton_convolution2d_8 0.0132 ms 72.6% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:29.6498866Z conv1x1_via_mm 0.0562 ms 17.0% 2025-09-07T10:20:29.6499373Z SingleProcess AUTOTUNE benchmarking takes 0.1316 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:29.7772929Z Autotune Choices Stats: 2025-09-07T10:20:29.7775496Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014879999682307243, "best_triton_pos": 1, "best_triton_time": 0.01724799908697605, "best_triton_kernel": "triton_convolution2d_17", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:29.7785437Z AUTOTUNE convolution(8x128x56x56, 256x128x1x1) 2025-09-07T10:20:29.7785769Z strides: [401408, 3136, 56, 1], [128, 1, 1, 1] 2025-09-07T10:20:29.7786082Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:29.7786376Z convolution 0.0149 ms 100.0% 2025-09-07T10:20:29.7787159Z triton_convolution2d_17 0.0172 ms 86.3% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.7788487Z triton_convolution2d_16 0.0181 ms 82.3% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.7789806Z triton_convolution2d_14 0.0183 ms 81.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.7791423Z triton_convolution2d_19 0.0200 ms 74.3% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.7792741Z triton_convolution2d_13 0.0222 ms 67.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.7794049Z triton_convolution2d_18 0.0224 ms 66.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.7795361Z triton_convolution2d_15 0.0301 ms 49.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:29.7796195Z conv1x1_via_mm 0.0889 ms 16.7% 2025-09-07T10:20:29.7796707Z SingleProcess AUTOTUNE benchmarking takes 0.1294 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:29.9062137Z Autotune Choices Stats: 2025-09-07T10:20:29.9064007Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_20", "best_kernel_desc": "ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.013279999606311321, "best_triton_pos": 0} 2025-09-07T10:20:29.9074639Z AUTOTUNE convolution(8x64x56x56, 256x64x1x1) 2025-09-07T10:20:29.9074981Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T10:20:29.9075306Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:29.9076131Z triton_convolution2d_20 0.0133 ms 100.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.9077136Z convolution 0.0135 ms 98.6% 2025-09-07T10:20:29.9077919Z triton_convolution2d_24 0.0137 ms 97.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.9079239Z triton_convolution2d_21 0.0144 ms 92.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:29.9080846Z triton_convolution2d_23 0.0145 ms 91.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.9082307Z triton_convolution2d_26 0.0157 ms 84.7% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.9083622Z triton_convolution2d_25 0.0163 ms 81.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:29.9084953Z triton_convolution2d_22 0.0201 ms 66.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:29.9085758Z conv1x1_via_mm 0.0812 ms 16.4% 2025-09-07T10:20:29.9086191Z SingleProcess AUTOTUNE benchmarking takes 0.1279 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.0344762Z Autotune Choices Stats: 2025-09-07T10:20:30.0347025Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013887999579310417, "best_triton_pos": 1, "best_triton_time": 0.01568000018596649, "best_triton_kernel": "triton_convolution2d_32", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T10:20:30.0356703Z AUTOTUNE convolution(8x256x56x56, 128x256x1x1) 2025-09-07T10:20:30.0357048Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T10:20:30.0357339Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.0357608Z convolution 0.0139 ms 100.0% 2025-09-07T10:20:30.0358329Z triton_convolution2d_32 0.0157 ms 88.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.0359544Z triton_convolution2d_31 0.0162 ms 85.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.0360899Z triton_convolution2d_30 0.0180 ms 77.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.0362120Z triton_convolution2d_33 0.0189 ms 73.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.0363321Z triton_convolution2d_27 0.0196 ms 71.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.0364529Z triton_convolution2d_28 0.0236 ms 59.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.0365951Z triton_convolution2d_29 0.0277 ms 50.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.0366695Z conv1x1_via_mm 0.0883 ms 15.7% 2025-09-07T10:20:30.0367165Z SingleProcess AUTOTUNE benchmarking takes 0.1279 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.1684405Z Autotune Choices Stats: 2025-09-07T10:20:30.1686653Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018271999433636665, "best_triton_pos": 1, "best_triton_time": 0.024768000468611717, "best_triton_kernel": "triton_convolution2d_59", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:30.1697237Z AUTOTUNE convolution(8x256x56x56, 256x256x1x1) 2025-09-07T10:20:30.1697529Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T10:20:30.1697823Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.1698076Z convolution 0.0183 ms 100.0% 2025-09-07T10:20:30.1698752Z triton_convolution2d_59 0.0248 ms 73.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.1699880Z triton_convolution2d_58 0.0252 ms 72.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.1701315Z triton_convolution2d_56 0.0261 ms 70.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.1702441Z triton_convolution2d_61 0.0286 ms 63.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.1703626Z triton_convolution2d_60 0.0321 ms 57.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.1704736Z triton_convolution2d_55 0.0345 ms 53.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.1705871Z triton_convolution2d_57 0.0491 ms 37.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.1706561Z conv1x1_via_mm 0.1152 ms 15.9% 2025-09-07T10:20:30.1707006Z SingleProcess AUTOTUNE benchmarking takes 0.1303 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.2994489Z Autotune Choices Stats: 2025-09-07T10:20:30.2996551Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012543999589979649, "best_triton_pos": 1, "best_triton_time": 0.01484800036996603, "best_triton_kernel": "triton_convolution2d_66", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:30.3007445Z AUTOTUNE convolution(8x256x28x28, 512x256x1x1) 2025-09-07T10:20:30.3007767Z strides: [200704, 784, 28, 1], [256, 1, 1, 1] 2025-09-07T10:20:30.3008072Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.3008347Z convolution 0.0125 ms 100.0% 2025-09-07T10:20:30.3009070Z triton_convolution2d_66 0.0148 ms 84.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.3010773Z triton_convolution2d_65 0.0164 ms 76.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.3011997Z triton_convolution2d_67 0.0169 ms 74.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.3013197Z triton_convolution2d_68 0.0172 ms 73.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.3014530Z triton_convolution2d_62 0.0206 ms 60.9% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.3015742Z triton_convolution2d_63 0.0215 ms 58.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.3016852Z triton_convolution2d_64 0.0270 ms 46.5% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.3017544Z conv1x1_via_mm 0.0569 ms 22.0% 2025-09-07T10:20:30.3017980Z SingleProcess AUTOTUNE benchmarking takes 0.1301 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.4056585Z Autotune Choices Stats: 2025-09-07T10:20:30.4058346Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_74", "best_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8", "best_time": 0.01926399953663349, "best_triton_pos": 0} 2025-09-07T10:20:30.4069514Z AUTOTUNE convolution(8x256x56x56, 512x256x1x1) 2025-09-07T10:20:30.4069813Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T10:20:30.4070080Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.4070939Z triton_convolution2d_74 0.0193 ms 100.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.4072081Z triton_convolution2d_69 0.0245 ms 78.7% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.4073201Z triton_convolution2d_75 0.0252 ms 76.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.4074325Z triton_convolution2d_73 0.0256 ms 75.3% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.4075478Z triton_convolution2d_70 0.0265 ms 72.7% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.4076223Z convolution 0.0372 ms 51.8% 2025-09-07T10:20:30.4076946Z triton_convolution2d_72 0.0559 ms 34.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.4078170Z triton_convolution2d_71 0.0877 ms 22.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.4079396Z SingleProcess AUTOTUNE benchmarking takes 0.1053 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:20:30.5362071Z Autotune Choices Stats: 2025-09-07T10:20:30.5363431Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012415999546647072, "best_triton_pos": 1, "best_triton_time": 0.019551999866962433, "best_triton_kernel": "triton_convolution2d_80", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:30.5375147Z AUTOTUNE convolution(8x512x28x28, 256x512x1x1) 2025-09-07T10:20:30.5375704Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T10:20:30.5375994Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.5376277Z convolution 0.0124 ms 100.0% 2025-09-07T10:20:30.5376956Z triton_convolution2d_80 0.0196 ms 63.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.5378084Z triton_convolution2d_79 0.0235 ms 52.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.5379214Z triton_convolution2d_82 0.0236 ms 52.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.5380649Z triton_convolution2d_81 0.0248 ms 50.1% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.5381783Z triton_convolution2d_76 0.0317 ms 39.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.5382999Z triton_convolution2d_77 0.0341 ms 36.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.5384120Z triton_convolution2d_78 0.0401 ms 31.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.5384806Z conv1x1_via_mm 0.0535 ms 23.2% 2025-09-07T10:20:30.5385254Z SingleProcess AUTOTUNE benchmarking takes 0.1302 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.6732276Z Autotune Choices Stats: 2025-09-07T10:20:30.6734449Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013535999692976475, "best_triton_pos": 1, "best_triton_time": 0.02115200087428093, "best_triton_kernel": "triton_convolution2d_122", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:30.6745279Z AUTOTUNE convolution(8x512x28x28, 512x512x1x1) 2025-09-07T10:20:30.6745577Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T10:20:30.6745884Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.6746137Z convolution 0.0135 ms 100.0% 2025-09-07T10:20:30.6746815Z triton_convolution2d_122 0.0212 ms 64.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.6748151Z triton_convolution2d_121 0.0238 ms 56.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.6749277Z triton_convolution2d_123 0.0251 ms 54.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.6750669Z triton_convolution2d_124 0.0254 ms 53.3% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.6751945Z triton_convolution2d_118 0.0322 ms 42.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.6753074Z triton_convolution2d_119 0.0349 ms 38.7% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.6754202Z triton_convolution2d_120 0.0461 ms 29.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.6754898Z conv1x1_via_mm 0.0704 ms 19.2% 2025-09-07T10:20:30.6755343Z SingleProcess AUTOTUNE benchmarking takes 0.1311 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.8055497Z Autotune Choices Stats: 2025-09-07T10:20:30.8057722Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018912000581622124, "best_triton_pos": 1, "best_triton_time": 0.020128000527620316, "best_triton_kernel": "triton_convolution2d_129", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:30.8069106Z AUTOTUNE convolution(8x512x14x14, 1024x512x1x1) 2025-09-07T10:20:30.8069409Z strides: [100352, 196, 14, 1], [512, 1, 1, 1] 2025-09-07T10:20:30.8069695Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.8069946Z convolution 0.0189 ms 100.0% 2025-09-07T10:20:30.8070762Z triton_convolution2d_129 0.0201 ms 94.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.8071933Z triton_convolution2d_128 0.0232 ms 81.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.8073112Z triton_convolution2d_131 0.0238 ms 79.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.8074245Z triton_convolution2d_130 0.0243 ms 77.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.8075410Z triton_convolution2d_126 0.0291 ms 64.9% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.8076729Z triton_convolution2d_125 0.0316 ms 59.9% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.8077535Z conv1x1_via_mm 0.0381 ms 49.6% 2025-09-07T10:20:30.8078333Z triton_convolution2d_127 0.0427 ms 44.3% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.8079605Z SingleProcess AUTOTUNE benchmarking takes 0.1314 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:30.9098626Z Autotune Choices Stats: 2025-09-07T10:20:30.9100997Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_136", "best_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.022752000018954277, "best_triton_pos": 0} 2025-09-07T10:20:30.9112637Z AUTOTUNE convolution(8x512x28x28, 1024x512x1x1) 2025-09-07T10:20:30.9112938Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T10:20:30.9113398Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:30.9114129Z triton_convolution2d_136 0.0228 ms 100.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.9115279Z triton_convolution2d_137 0.0252 ms 90.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.9116512Z triton_convolution2d_135 0.0257 ms 88.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.9117260Z convolution 0.0294 ms 77.3% 2025-09-07T10:20:30.9117989Z triton_convolution2d_138 0.0356 ms 63.9% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:30.9119200Z triton_convolution2d_132 0.0364 ms 62.6% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.9120579Z triton_convolution2d_133 0.0390 ms 58.4% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:30.9121795Z triton_convolution2d_134 0.0731 ms 31.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:30.9122769Z SingleProcess AUTOTUNE benchmarking takes 0.1034 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:20:31.0553225Z Autotune Choices Stats: 2025-09-07T10:20:31.0555533Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.024960000067949295, "best_triton_pos": 1, "best_triton_time": 0.0306560005992651, "best_triton_kernel": "triton_convolution2d_143", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:31.0567166Z AUTOTUNE convolution(8x1024x14x14, 512x1024x1x1) 2025-09-07T10:20:31.0567482Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T10:20:31.0567780Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:31.0568069Z convolution 0.0250 ms 100.0% 2025-09-07T10:20:31.0568794Z triton_convolution2d_143 0.0307 ms 81.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.0569538Z conv1x1_via_mm 0.0372 ms 67.1% 2025-09-07T10:20:31.0570559Z triton_convolution2d_142 0.0372 ms 67.1% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.0572010Z triton_convolution2d_144 0.0387 ms 64.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.0573235Z triton_convolution2d_145 0.0392 ms 63.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.0574450Z triton_convolution2d_140 0.0498 ms 50.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.0575806Z triton_convolution2d_139 0.0552 ms 45.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.0576958Z triton_convolution2d_141 0.0784 ms 31.8% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:31.0577858Z SingleProcess AUTOTUNE benchmarking takes 0.1451 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:31.2101825Z Autotune Choices Stats: 2025-09-07T10:20:31.2103295Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.029120000079274178, "best_triton_pos": 1, "best_triton_time": 0.03232000023126602, "best_triton_kernel": "triton_convolution2d_213", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:20:31.2116117Z AUTOTUNE convolution(8x1024x14x14, 1024x1024x1x1) 2025-09-07T10:20:31.2116460Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T10:20:31.2116767Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:31.2117068Z convolution 0.0291 ms 100.0% 2025-09-07T10:20:31.2117852Z triton_convolution2d_213 0.0323 ms 90.1% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.2119187Z triton_convolution2d_212 0.0380 ms 76.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.2120782Z triton_convolution2d_214 0.0396 ms 73.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.2122117Z triton_convolution2d_215 0.0398 ms 73.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.2123437Z triton_convolution2d_210 0.0509 ms 57.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.2124243Z conv1x1_via_mm 0.0526 ms 55.4% 2025-09-07T10:20:31.2125029Z triton_convolution2d_209 0.0574 ms 50.7% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.2126375Z triton_convolution2d_211 0.0798 ms 36.5% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:31.2127488Z SingleProcess AUTOTUNE benchmarking takes 0.1443 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:31.3608561Z Autotune Choices Stats: 2025-09-07T10:20:31.3609973Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.024383999407291412, "best_triton_pos": 2, "best_triton_time": 0.03855999931693077, "best_triton_kernel": "triton_convolution2d_219", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T10:20:31.3623365Z AUTOTUNE convolution(8x1024x7x7, 2048x1024x1x1) 2025-09-07T10:20:31.3623651Z strides: [50176, 49, 7, 1], [1024, 1, 1, 1] 2025-09-07T10:20:31.3623912Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:31.3624356Z convolution 0.0244 ms 100.0% 2025-09-07T10:20:31.3624606Z conv1x1_via_mm 0.0375 ms 65.1% 2025-09-07T10:20:31.3625297Z triton_convolution2d_219 0.0386 ms 63.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.3626429Z triton_convolution2d_220 0.0410 ms 59.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.3627495Z triton_convolution2d_221 0.0489 ms 49.9% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.3628543Z triton_convolution2d_222 0.0556 ms 43.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.3629597Z triton_convolution2d_216 0.0580 ms 42.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.3630806Z triton_convolution2d_217 0.0677 ms 36.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.3631851Z triton_convolution2d_218 0.0732 ms 33.3% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=512, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:31.3632681Z SingleProcess AUTOTUNE benchmarking takes 0.1497 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:31.4834483Z Autotune Choices Stats: 2025-09-07T10:20:31.4836783Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027168000116944313, "best_triton_pos": 1, "best_triton_time": 0.0424639992415905, "best_triton_kernel": "triton_convolution2d_226", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T10:20:31.4848452Z AUTOTUNE convolution(8x1024x14x14, 2048x1024x1x1) 2025-09-07T10:20:31.4848777Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T10:20:31.4849060Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:31.4849339Z convolution 0.0272 ms 100.0% 2025-09-07T10:20:31.4850073Z triton_convolution2d_226 0.0425 ms 64.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.4851554Z triton_convolution2d_227 0.0516 ms 52.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.4852956Z triton_convolution2d_228 0.0528 ms 51.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.4854156Z triton_convolution2d_223 0.0635 ms 42.8% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.4855356Z triton_convolution2d_229 0.0689 ms 39.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.4856666Z triton_convolution2d_224 0.0725 ms 37.5% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.4857796Z triton_convolution2d_225 0.0935 ms 29.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:31.4858692Z SingleProcess AUTOTUNE benchmarking takes 0.1215 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:20:31.6699719Z Autotune Choices Stats: 2025-09-07T10:20:31.6702362Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02489599958062172, "best_triton_pos": 2, "best_triton_time": 0.06876800209283829, "best_triton_kernel": "triton_convolution2d_233", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T10:20:31.6714883Z AUTOTUNE convolution(8x2048x7x7, 1024x2048x1x1) 2025-09-07T10:20:31.6715177Z strides: [100352, 49, 7, 1], [2048, 1, 1, 1] 2025-09-07T10:20:31.6715450Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:31.6715711Z convolution 0.0249 ms 100.0% 2025-09-07T10:20:31.6715974Z conv1x1_via_mm 0.0356 ms 70.0% 2025-09-07T10:20:31.6716715Z triton_convolution2d_233 0.0688 ms 36.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.6717933Z triton_convolution2d_234 0.0725 ms 34.3% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.6719147Z triton_convolution2d_235 0.0895 ms 27.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.6720510Z triton_convolution2d_236 0.1018 ms 24.5% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:20:31.6721725Z triton_convolution2d_230 0.1076 ms 23.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.6722930Z triton_convolution2d_231 0.1246 ms 20.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:20:31.6724139Z triton_convolution2d_232 0.1408 ms 17.7% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=512, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:20:31.6725105Z SingleProcess AUTOTUNE benchmarking takes 0.1856 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:20:31.9114996Z Autotune Choices Stats: 2025-09-07T10:20:31.9116760Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_262", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.01056000031530857, "best_triton_pos": 0} 2025-09-07T10:20:31.9131487Z AUTOTUNE addmm(8x1000, 8x2048, 2048x1000) 2025-09-07T10:20:31.9131783Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T10:20:31.9132085Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:20:31.9132775Z triton_mm_262 0.0106 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:20:31.9133613Z bias_addmm 0.0108 ms 97.9% 2025-09-07T10:20:31.9134220Z triton_mm_266 0.0113 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:20:31.9135186Z triton_mm_270 0.0139 ms 76.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:20:31.9135793Z addmm 0.0142 ms 74.2% 2025-09-07T10:20:31.9136359Z triton_mm_274 0.0152 ms 69.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:20:31.9137297Z triton_mm_261 0.0169 ms 62.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:20:31.9138229Z triton_mm_260 0.0179 ms 59.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:20:31.9139169Z triton_mm_265 0.0179 ms 59.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:20:31.9140104Z triton_mm_259 0.0185 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:20:31.9141383Z SingleProcess AUTOTUNE benchmarking takes 0.2371 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:20:43.5817095Z Autotune Choices Stats: 2025-09-07T10:20:43.5818215Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_297", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.00687999976798892, "best_triton_pos": 0} 2025-09-07T10:20:43.5833470Z AUTOTUNE mm(1000x8, 8x2048) 2025-09-07T10:20:43.5833749Z strides: [1, 1000], [2048, 1] 2025-09-07T10:20:43.5834025Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:43.5834672Z triton_mm_297 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:20:43.5835671Z triton_mm_298 0.0070 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:20:43.5836654Z triton_mm_303 0.0070 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:20:43.5837628Z triton_mm_304 0.0070 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:20:43.5838588Z triton_mm_302 0.0071 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:20:43.5840060Z triton_mm_299 0.0071 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:20:43.5841529Z triton_mm_301 0.0071 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:20:43.5842490Z triton_mm_307 0.0071 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:20:43.5843750Z triton_mm_300 0.0072 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:20:43.5844728Z triton_mm_306 0.0072 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:20:43.5845581Z SingleProcess AUTOTUNE benchmarking takes 0.1520 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T10:20:44.0583740Z Autotune Choices Stats: 2025-09-07T10:20:44.0585047Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009247999638319016, "best_triton_pos": 1, "best_triton_time": 0.010208000428974628, "best_triton_kernel": "triton_mm_283", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T10:20:44.0598646Z AUTOTUNE mm(8x1000, 1000x2048) 2025-09-07T10:20:44.0598912Z strides: [1000, 1], [2048, 1] 2025-09-07T10:20:44.0599188Z dtypes: torch.float16, torch.float16 2025-09-07T10:20:44.0599453Z mm 0.0092 ms 100.0% 2025-09-07T10:20:44.0600064Z triton_mm_283 0.0102 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:20:44.0601343Z triton_mm_279 0.0105 ms 88.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:20:44.0602267Z triton_mm_287 0.0106 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:20:44.0603161Z triton_mm_277 0.0117 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:20:44.0604052Z triton_mm_278 0.0120 ms 77.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:20:44.0604945Z triton_mm_291 0.0120 ms 77.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:20:44.0605829Z triton_mm_282 0.0121 ms 76.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:20:44.0606708Z triton_mm_289 0.0132 ms 70.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:20:44.0607589Z triton_mm_286 0.0132 ms 70.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:20:44.0608375Z SingleProcess AUTOTUNE benchmarking takes 0.1767 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:20:51.2000185Z W0907 10:20:51.199000 120348 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:21:12.2076384Z 2025-09-07T10:21:12.3129084Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:22:46.5682282Z 2025-09-07T10:22:46.6719279Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:38:41.6053499Z torchbench_main() 2025-09-07T10:38:41.6053986Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T10:38:41.6054527Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T10:38:41.6054986Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T10:38:41.6057933Z process_entry(0, runner, original_dir, args) 2025-09-07T10:38:41.6058484Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T10:38:41.6061076Z result = run(runner, args, original_dir) 2025-09-07T10:38:41.6061497Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4251, in run 2025-09-07T10:38:41.6064998Z assert marked, f"nothing in example_inputs had a dim with {batch_size}" 2025-09-07T10:38:41.6065416Z AssertionError: nothing in example_inputs had a dim with 4 2025-09-07T10:38:43.8046657Z Run failed with return code: 1 2025-09-07T10:38:43.8047013Z Output: None 2025-09-07T10:38:43.8047225Z Error: None 2025-09-07T10:38:44.3232557Z /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. 2025-09-07T10:38:44.3235056Z import pynvml # type: ignore[import] 2025-09-07T10:38:46.8348403Z 2025-09-07T10:38:47.9726607Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:38:47.9727008Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:38:47.9797587Z cuda eval shufflenet_v2_x1_0 2025-09-07T10:38:53.2217760Z pass 2025-09-07T10:38:56.7615791Z /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. 2025-09-07T10:38:56.7617584Z import pynvml # type: ignore[import] 2025-09-07T10:39:00.5465221Z 2025-09-07T10:39:01.5335196Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:39:01.5335605Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:39:01.5338669Z cuda eval soft_actor_critic 2025-09-07T10:39:03.6334385Z pass 2025-09-07T10:39:07.3140743Z /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. 2025-09-07T10:39:07.3142201Z import pynvml # type: ignore[import] 2025-09-07T10:39:09.8242484Z 2025-09-07T10:39:11.4874845Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:39:11.4875229Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:39:11.4939811Z cuda eval speech_transformer 2025-09-07T10:39:18.8711327Z pass 2025-09-07T10:39:21.8606101Z /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. 2025-09-07T10:39:21.8607316Z import pynvml # type: ignore[import] 2025-09-07T10:39:24.4173202Z 2025-09-07T10:39:25.4086011Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:39:25.4086368Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:39:25.4103715Z cuda eval squeezenet1_1 2025-09-07T10:39:28.0691151Z pass 2025-09-07T10:39:30.9085450Z accuracy pass_rate=87.50% 2025-09-07T10:39:30.9096597Z calls_captured gmean=0.00x mean=469.125x 2025-09-07T10:39:30.9099924Z unique_graphs gmean=0.00x mean=1.625x 2025-09-07T10:39:30.9103596Z graph_breaks gmean=0.00x mean=1.250x 2025-09-07T10:39:30.9107085Z unique_graph_breaks gmean=0.00x mean=0.250x 2025-09-07T10:39:30.9110068Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:39:30.9113681Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:39:30.9116769Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:39:30.9117696Z compilation_latency mean=3.651 seconds 2025-09-07T10:39:31.7222762Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cppwrapper-true* ]] 2025-09-07T10:39:31.7224766Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T10:39:31.7226764Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T10:39:32.2732169Z /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. 2025-09-07T10:39:32.2733958Z import pynvml # type: ignore[import] 2025-09-07T10:39:36.1953422Z /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. 2025-09-07T10:39:36.1955047Z import pynvml # type: ignore[import] 2025-09-07T10:39:38.6698911Z 2025-09-07T10:39:40.1190750Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:39:40.1191303Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:39:40.1252451Z cuda eval resnet50 2025-09-07T10:39:54.7943648Z pass 2025-09-07T10:39:57.8965477Z /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. 2025-09-07T10:39:57.8966950Z import pynvml # type: ignore[import] 2025-09-07T10:40:00.4245690Z 2025-09-07T10:40:00.5844748Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:40:00.5845228Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:40:00.5845644Z cuda eval resnet50_quantized_qat 2025-09-07T10:40:00.5851035Z Traceback (most recent call last): 2025-09-07T10:40:00.5851749Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:40:00.5852416Z ) = runner.load_model( 2025-09-07T10:40:00.5853058Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T10:40:00.5853759Z benchmark = benchmark_cls( 2025-09-07T10:40:00.5854297Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T10:40:00.5854898Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T10:40:00.5855642Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T10:40:00.5856490Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T10:40:00.5857088Z NotImplementedError: The eval test only supports CPU. 2025-09-07T10:40:00.5857442Z 2025-09-07T10:40:00.5857554Z model_fail_to_load 2025-09-07T10:40:01.9468233Z /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. 2025-09-07T10:40:01.9469390Z import pynvml # type: ignore[import] 2025-09-07T10:40:04.5326526Z 2025-09-07T10:40:06.0980470Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:40:06.0980797Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:40:06.1046132Z cuda eval resnext50_32x4d 2025-09-07T10:40:20.9056125Z pass 2025-09-07T10:40:23.9895667Z /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. 2025-09-07T10:40:23.9897541Z import pynvml # type: ignore[import] 2025-09-07T10:40:26.5600596Z 2025-09-07T10:40:34.9217019Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:40:34.9217539Z loading model: 0it [00:08, ?it/s] 2025-09-07T10:40:34.9338346Z cuda eval sam 2025-09-07T10:41:50.5561297Z pass 2025-09-07T10:41:54.9595994Z /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. 2025-09-07T10:41:54.9597243Z import pynvml # type: ignore[import] 2025-09-07T10:41:57.4600609Z 2025-09-07T10:42:10.2697160Z loading model: 0it [00:00, ?it/s]skipping cudagraphs due to cpp wrapper enabled 2025-09-07T10:42:38.2822367Z Autotune Choices Stats: 2025-09-07T10:42:38.2823832Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.08195199817419052, "best_triton_pos": 1, "best_triton_time": 0.09296000003814697, "best_triton_kernel": "triton_mm_94", "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"} 2025-09-07T10:42:38.2868654Z AUTOTUNE mm(4096x1280, 1280x5120) 2025-09-07T10:42:38.2868929Z strides: [1280, 1], [1, 1280] 2025-09-07T10:42:38.2869169Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:38.2869406Z mm 0.0820 ms 100.0% 2025-09-07T10:42:38.2869933Z triton_mm_94 0.0930 ms 88.2% 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 2025-09-07T10:42:38.2871055Z triton_mm_95 0.1038 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=5, num_warps=8 2025-09-07T10:42:38.2872272Z triton_mm_93 0.1139 ms 72.0% 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 2025-09-07T10:42:38.2873123Z triton_mm_88 0.1294 ms 63.3% 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 2025-09-07T10:42:38.2873987Z triton_mm_89 0.1356 ms 60.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:38.2874815Z triton_mm_87 0.1532 ms 53.5% 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 2025-09-07T10:42:38.2875640Z triton_mm_86 0.1561 ms 52.5% 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 2025-09-07T10:42:38.2876484Z triton_mm_91 0.1585 ms 51.7% 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 2025-09-07T10:42:38.2877314Z triton_mm_92 0.1612 ms 50.9% 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 2025-09-07T10:42:38.2878050Z SingleProcess AUTOTUNE benchmarking takes 0.7871 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:42:39.4794674Z Autotune Choices Stats: 2025-09-07T10:42:39.4795950Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.07420799881219864, "best_triton_pos": 1, "best_triton_time": 0.10278400033712387, "best_triton_kernel": "triton_mm_3477", "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"} 2025-09-07T10:42:39.4841449Z AUTOTUNE mm(4096x5120, 5120x1280) 2025-09-07T10:42:39.4841971Z strides: [5120, 1], [1, 5120] 2025-09-07T10:42:39.4842485Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:39.4842931Z mm 0.0742 ms 100.0% 2025-09-07T10:42:39.4843970Z triton_mm_3477 0.1028 ms 72.2% 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 2025-09-07T10:42:39.4845622Z triton_mm_3478 0.1030 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 2025-09-07T10:42:39.4847431Z triton_mm_3472 0.1115 ms 66.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:39.4848423Z triton_mm_3471 0.1135 ms 65.4% 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 2025-09-07T10:42:39.4849400Z triton_mm_3476 0.1137 ms 65.3% 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 2025-09-07T10:42:39.4851079Z triton_mm_3470 0.1616 ms 45.9% 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 2025-09-07T10:42:39.4852058Z triton_mm_3473 0.1653 ms 44.9% 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 2025-09-07T10:42:39.4853036Z triton_mm_3469 0.1670 ms 44.4% 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 2025-09-07T10:42:39.4854045Z triton_mm_3474 0.1676 ms 44.3% 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 2025-09-07T10:42:39.4855138Z SingleProcess AUTOTUNE benchmarking takes 0.5718 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:42:39.8227440Z Autotune Choices Stats: 2025-09-07T10:42:39.8228652Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.02611199952661991, "best_triton_pos": 1, "best_triton_time": 0.031136000528931618, "best_triton_kernel": "triton_mm_834", "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"} 2025-09-07T10:42:39.8272729Z AUTOTUNE mm(4096x1280, 1280x1280) 2025-09-07T10:42:39.8273092Z strides: [1280, 1], [1, 1280] 2025-09-07T10:42:39.8273362Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:39.8273635Z mm 0.0261 ms 100.0% 2025-09-07T10:42:39.8274237Z triton_mm_834 0.0311 ms 83.9% 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 2025-09-07T10:42:39.8275274Z triton_mm_835 0.0315 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=3, num_warps=4 2025-09-07T10:42:39.8276281Z triton_mm_836 0.0334 ms 78.2% 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 2025-09-07T10:42:39.8277256Z triton_mm_829 0.0343 ms 76.2% 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 2025-09-07T10:42:39.8278193Z triton_mm_830 0.0404 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:39.8279083Z triton_mm_828 0.0434 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 2025-09-07T10:42:39.8279976Z triton_mm_832 0.0445 ms 58.7% 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 2025-09-07T10:42:39.8281055Z triton_mm_831 0.0460 ms 56.7% 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 2025-09-07T10:42:39.8281967Z triton_mm_825 0.0466 ms 56.1% 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 2025-09-07T10:42:39.8282748Z SingleProcess AUTOTUNE benchmarking takes 0.3266 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:42:41.0669314Z Autotune Choices Stats: 2025-09-07T10:42:41.0670997Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_6", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.3240000009536743, "best_triton_pos": 0} 2025-09-07T10:42:41.0719587Z AUTOTUNE convolution(1x3x1024x1024, 1280x3x16x16) 2025-09-07T10:42:41.0720430Z strides: [3145728, 1048576, 1024, 1], [768, 256, 16, 1] 2025-09-07T10:42:41.0720966Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:41.0722240Z triton_convolution2d_6 0.3240 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:42:41.0724260Z triton_convolution2d_1 0.3354 ms 96.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:42:41.0726728Z triton_convolution2d_3 0.3475 ms 93.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:42:41.0728067Z convolution 0.3628 ms 89.3% 2025-09-07T10:42:41.0728752Z triton_convolution2d_5 0.5525 ms 58.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:42:41.0729896Z triton_convolution2d_4 0.5782 ms 56.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:42:41.0731186Z triton_convolution2d_0 0.6776 ms 47.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:42:41.0732337Z triton_convolution2d_2 1.6856 ms 19.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:42:41.0733241Z SingleProcess AUTOTUNE benchmarking takes 0.3734 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:42:41.6007930Z Autotune Choices Stats: 2025-09-07T10:42:41.6009213Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.07171200215816498, "best_triton_pos": 1, "best_triton_time": 0.0907519981265068, "best_triton_kernel": "triton_mm_24", "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"} 2025-09-07T10:42:41.6054110Z AUTOTUNE mm(4900x1280, 1280x3840) 2025-09-07T10:42:41.6054389Z strides: [1280, 1], [1, 1280] 2025-09-07T10:42:41.6054670Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:41.6054951Z mm 0.0717 ms 100.0% 2025-09-07T10:42:41.6055585Z triton_mm_24 0.0908 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 2025-09-07T10:42:41.6056585Z triton_mm_25 0.0956 ms 75.1% 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 2025-09-07T10:42:41.6057643Z triton_mm_23 0.0998 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 2025-09-07T10:42:41.6058607Z triton_mm_18 0.1166 ms 61.5% 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 2025-09-07T10:42:41.6059576Z triton_mm_19 0.1223 ms 58.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:41.6060685Z triton_mm_22 0.1325 ms 54.1% 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 2025-09-07T10:42:41.6061894Z triton_mm_17 0.1390 ms 51.6% 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 2025-09-07T10:42:41.6062963Z triton_mm_16 0.1439 ms 49.8% 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 2025-09-07T10:42:41.6063921Z triton_mm_21 0.1439 ms 49.8% 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 2025-09-07T10:42:41.6064763Z SingleProcess AUTOTUNE benchmarking takes 0.5329 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:42:41.8118368Z Autotune Choices Stats: 2025-09-07T10:42:41.8119927Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_33", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.012671999633312225, "best_triton_pos": 0} 2025-09-07T10:42:41.8166626Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T10:42:41.8167070Z strides: [448000, 80, 1], [1152, 1, 80] 2025-09-07T10:42:41.8167473Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:41.8168402Z triton_bmm_33 0.0127 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:41.8169908Z triton_bmm_30 0.0130 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:42:41.8171593Z triton_bmm_36 0.0131 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:41.8173086Z triton_bmm_29 0.0132 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:42:41.8174564Z triton_bmm_38 0.0135 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:42:41.8176037Z triton_bmm_37 0.0135 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:41.8177481Z triton_bmm_32 0.0136 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:42:41.8178889Z triton_bmm_28 0.0137 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:42:41.8180474Z triton_bmm_39 0.0137 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:42:41.8181953Z triton_bmm_34 0.0138 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:41.8183314Z SingleProcess AUTOTUNE benchmarking takes 0.2097 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T10:42:42.0201482Z Autotune Choices Stats: 2025-09-07T10:42:42.0203048Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_56", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013407999649643898, "best_triton_pos": 0} 2025-09-07T10:42:42.0249448Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T10:42:42.0249855Z strides: [80, 1120, 1], [1152, 1, 80] 2025-09-07T10:42:42.0250436Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:42.0251403Z triton_bmm_56 0.0134 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:42.0252877Z triton_bmm_49 0.0135 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:42.0254344Z triton_bmm_46 0.0139 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:42:42.0256165Z triton_bmm_48 0.0140 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:42:42.0257646Z triton_bmm_52 0.0140 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:42.0259110Z triton_bmm_44 0.0140 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:42:42.0260749Z triton_bmm_45 0.0140 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:42:42.0262212Z triton_bmm_54 0.0140 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:42:42.0263818Z triton_bmm_51 0.0141 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:42.0265287Z triton_bmm_50 0.0142 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:42.0266546Z SingleProcess AUTOTUNE benchmarking takes 0.2078 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T10:42:42.3827410Z Autotune Choices Stats: 2025-09-07T10:42:42.3829302Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.029503999277949333, "best_triton_pos": 1, "best_triton_time": 0.034912001341581345, "best_triton_kernel": "triton_mm_76", "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"} 2025-09-07T10:42:42.3875882Z AUTOTUNE mm(4900x1280, 1280x1280) 2025-09-07T10:42:42.3876309Z strides: [1280, 1], [1, 1280] 2025-09-07T10:42:42.3876689Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:42.3877070Z mm 0.0295 ms 100.0% 2025-09-07T10:42:42.3877908Z triton_mm_76 0.0349 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:42:42.3879294Z triton_mm_75 0.0371 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 2025-09-07T10:42:42.3880787Z triton_mm_74 0.0374 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 2025-09-07T10:42:42.3882205Z triton_mm_69 0.0384 ms 76.9% 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 2025-09-07T10:42:42.3883594Z triton_mm_70 0.0470 ms 62.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:42.3885442Z triton_mm_68 0.0514 ms 57.4% 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 2025-09-07T10:42:42.3886432Z triton_mm_72 0.0526 ms 56.0% 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 2025-09-07T10:42:42.3887237Z triton_mm_65 0.0535 ms 55.1% 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 2025-09-07T10:42:42.3888292Z triton_mm_67 0.0573 ms 51.5% 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 2025-09-07T10:42:42.3889039Z SingleProcess AUTOTUNE benchmarking takes 0.3620 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:42:42.9681877Z Autotune Choices Stats: 2025-09-07T10:42:42.9683502Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_780", "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": 0.07772800326347351, "best_triton_pos": 0} 2025-09-07T10:42:42.9731065Z AUTOTUNE addmm(4096x3840, 4096x1280, 1280x3840) 2025-09-07T10:42:42.9731579Z strides: [0, 1], [1280, 1], [1, 1280] 2025-09-07T10:42:42.9732040Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:42:42.9733098Z triton_mm_780 0.0777 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 2025-09-07T10:42:42.9734628Z triton_mm_781 0.0864 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=5, num_warps=8 2025-09-07T10:42:42.9736122Z triton_mm_779 0.0921 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 2025-09-07T10:42:42.9737091Z addmm 0.0997 ms 78.0% 2025-09-07T10:42:42.9737995Z triton_mm_774 0.1009 ms 77.0% 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 2025-09-07T10:42:42.9739496Z triton_mm_775 0.1107 ms 70.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:42:42.9741212Z triton_mm_773 0.1172 ms 66.3% 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 2025-09-07T10:42:42.9742812Z triton_mm_778 0.1192 ms 65.2% 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 2025-09-07T10:42:42.9744304Z triton_mm_777 0.1205 ms 64.5% 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 2025-09-07T10:42:42.9745792Z triton_mm_772 0.1215 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=3, num_warps=4 2025-09-07T10:42:42.9747118Z SingleProcess AUTOTUNE benchmarking takes 0.5265 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:42:43.2010833Z Autotune Choices Stats: 2025-09-07T10:42:43.2012017Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_798", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013663999736309052, "best_triton_pos": 0} 2025-09-07T10:42:43.2062312Z AUTOTUNE bmm(64x1024x80, 64x80x64) 2025-09-07T10:42:43.2062728Z strides: [81920, 80, 1], [5120, 1, 80] 2025-09-07T10:42:43.2063036Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:43.2063884Z triton_bmm_798 0.0137 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:43.2064990Z triton_bmm_796 0.0137 ms 99.5% 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 2025-09-07T10:42:43.2066457Z triton_bmm_795 0.0141 ms 97.0% 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 2025-09-07T10:42:43.2067531Z triton_bmm_791 0.0141 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:42:43.2068592Z triton_bmm_793 0.0141 ms 96.6% 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=4 2025-09-07T10:42:43.2069630Z triton_bmm_788 0.0143 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:42:43.2070908Z triton_bmm_792 0.0143 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:42:43.2071977Z triton_bmm_797 0.0144 ms 94.9% 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=2, num_warps=8 2025-09-07T10:42:43.2073019Z triton_bmm_787 0.0147 ms 92.8% 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 2025-09-07T10:42:43.2074046Z triton_bmm_789 0.0148 ms 92.0% 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 2025-09-07T10:42:43.2074959Z SingleProcess AUTOTUNE benchmarking takes 0.2324 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:42:43.6151367Z Autotune Choices Stats: 2025-09-07T10:42:43.6152617Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012736000120639801, "best_triton_pos": 2, "best_triton_time": 0.03593600168824196, "best_triton_kernel": "triton_convolution2d_3483", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:42:43.6206340Z AUTOTUNE convolution(1x1280x64x64, 256x1280x1x1) 2025-09-07T10:42:43.6206901Z strides: [5242880, 4096, 64, 1], [1280, 1, 1, 1] 2025-09-07T10:42:43.6207339Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:43.6207725Z convolution 0.0127 ms 100.0% 2025-09-07T10:42:43.6208089Z conv1x1_via_mm 0.0273 ms 46.6% 2025-09-07T10:42:43.6209163Z triton_convolution2d_3483 0.0359 ms 35.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:42:43.6211237Z triton_convolution2d_3485 0.0443 ms 28.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:42:43.6213034Z triton_convolution2d_3482 0.0447 ms 28.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:42:43.6215323Z triton_convolution2d_3484 0.0476 ms 26.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:42:43.6217191Z triton_convolution2d_3479 0.0669 ms 19.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:42:43.6219005Z triton_convolution2d_3480 0.0684 ms 18.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:42:43.6221311Z triton_convolution2d_3481 0.0831 ms 15.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:42:43.6222946Z SingleProcess AUTOTUNE benchmarking takes 0.1721 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:42:43.8171265Z Autotune Choices Stats: 2025-09-07T10:42:43.8172835Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03161599859595299, "best_triton_pos": 1, "best_triton_time": 0.08928000181913376, "best_triton_kernel": "triton_convolution2d_3489", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:42:43.8223077Z AUTOTUNE convolution(1x256x64x64, 256x256x3x3) 2025-09-07T10:42:43.8223406Z strides: [1048576, 4096, 64, 1], [2304, 9, 3, 1] 2025-09-07T10:42:43.8223730Z dtypes: torch.float16, torch.float16 2025-09-07T10:42:43.8224002Z convolution 0.0316 ms 100.0% 2025-09-07T10:42:43.8224778Z triton_convolution2d_3489 0.0893 ms 35.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:42:43.8226035Z triton_convolution2d_3490 0.0897 ms 35.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:42:43.8227285Z triton_convolution2d_3492 0.0931 ms 34.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:42:43.8228632Z triton_convolution2d_3491 0.1143 ms 27.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:42:43.8229977Z triton_convolution2d_3487 0.1154 ms 27.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:42:43.8231494Z triton_convolution2d_3486 0.1747 ms 18.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:42:43.8232858Z triton_convolution2d_3488 0.2838 ms 11.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:42:43.8233921Z SingleProcess AUTOTUNE benchmarking takes 0.1998 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T10:43:44.5801602Z Warning: Custom flash attention kernels were written specifically for A100. 2025-09-07T10:43:44.5802505Z We will try to read previously created kernel configurations from /var/lib/jenkins/workspace/flash_4_configs.p. 2025-09-07T10:43:44.5803883Z You can disable this kernel by setting SEGMENT_ANYTHING_FAST_USE_FLASH_4=0 2025-09-07T10:43:44.5804562Z Loading best configs from file /var/lib/jenkins/workspace/flash_4_configs.p 2025-09-07T10:43:44.7868513Z 2025-09-07T10:43:44.7868805Z loading model: 0it [01:47, ?it/s] 2025-09-07T10:43:44.7916122Z cuda eval sam_fast 2025-09-07T10:43:48.2926720Z skipping cudagraphs due to cpp wrapper enabled 2025-09-07T10:46:21.7868698Z E0907 10:46:21.786000 175888 site-packages/torch/_dynamo/utils.py:3013] Accuracy failed: uint8 tensor did not match 2025-09-07T10:46:21.7870158Z E0907 10:46:21.786000 175888 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name masks 2025-09-07T10:46:21.8103185Z pass 2025-09-07T10:46:30.2516881Z /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. 2025-09-07T10:46:30.2518707Z import pynvml # type: ignore[import] 2025-09-07T10:46:32.7393575Z 2025-09-07T10:46:33.8750745Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:46:33.8751128Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:46:33.8814071Z cuda eval shufflenet_v2_x1_0 2025-09-07T10:46:54.1959961Z pass 2025-09-07T10:46:57.4859492Z /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. 2025-09-07T10:46:57.4861053Z import pynvml # type: ignore[import] 2025-09-07T10:46:59.9835042Z 2025-09-07T10:47:01.1064906Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:47:01.1065278Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:47:01.1067088Z cuda eval soft_actor_critic 2025-09-07T10:47:06.5558157Z pass 2025-09-07T10:47:09.1697699Z /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. 2025-09-07T10:47:09.1698952Z import pynvml # type: ignore[import] 2025-09-07T10:47:11.6642367Z 2025-09-07T10:47:13.4398025Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:47:13.4398395Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:47:13.4464906Z cuda eval speech_transformer 2025-09-07T10:47:42.7767911Z pass 2025-09-07T10:47:46.6059364Z /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. 2025-09-07T10:47:46.6061081Z import pynvml # type: ignore[import] 2025-09-07T10:47:49.1237955Z 2025-09-07T10:47:50.3022705Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:47:50.3023056Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:47:50.3038170Z cuda eval squeezenet1_1 2025-09-07T10:47:58.9149037Z pass 2025-09-07T10:48:01.1994065Z accuracy pass_rate=88.89% 2025-09-07T10:48:01.1997839Z calls_captured gmean=0.00x mean=522.111x 2025-09-07T10:48:01.2001225Z unique_graphs gmean=0.00x mean=1.444x 2025-09-07T10:48:01.2004355Z graph_breaks gmean=0.00x mean=1.111x 2025-09-07T10:48:01.2014186Z unique_graph_breaks gmean=0.00x mean=0.222x 2025-09-07T10:48:01.2017366Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:48:01.2020922Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:48:01.2024291Z cudagraph_skips gmean=nanx mean=-0.111x 2025-09-07T10:48:01.2025335Z compilation_latency mean=25.989 seconds 2025-09-07T10:48:02.0582478Z + [[ 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* ]] 2025-09-07T10:48:02.0583980Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:48:02.0585395Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 7 --freezing --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T10:48:02.6061358Z /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. 2025-09-07T10:48:02.6062953Z import pynvml # type: ignore[import] 2025-09-07T10:48:06.5098885Z /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. 2025-09-07T10:48:06.5101415Z import pynvml # type: ignore[import] 2025-09-07T10:48:08.9731827Z 2025-09-07T10:48:10.3916243Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:10.3916592Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:48:10.3974521Z cuda eval resnet50 2025-09-07T10:48:21.0409850Z pass 2025-09-07T10:48:23.8203399Z /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. 2025-09-07T10:48:23.8204734Z import pynvml # type: ignore[import] 2025-09-07T10:48:26.4682162Z 2025-09-07T10:48:26.6222938Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:26.6223282Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:26.6223597Z cuda eval resnet50_quantized_qat 2025-09-07T10:48:26.6229034Z Traceback (most recent call last): 2025-09-07T10:48:26.6229458Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:48:26.6229871Z ) = runner.load_model( 2025-09-07T10:48:26.6230643Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T10:48:26.6231085Z benchmark = benchmark_cls( 2025-09-07T10:48:26.6231414Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T10:48:26.6231777Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T10:48:26.6232254Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T10:48:26.6232807Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T10:48:26.6233186Z NotImplementedError: The eval test only supports CPU. 2025-09-07T10:48:26.6233405Z 2025-09-07T10:48:26.6233488Z model_fail_to_load 2025-09-07T10:48:28.0289276Z /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. 2025-09-07T10:48:28.0291054Z import pynvml # type: ignore[import] 2025-09-07T10:48:30.5192408Z 2025-09-07T10:48:32.0585655Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:32.0586014Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:48:32.0648100Z cuda eval resnext50_32x4d 2025-09-07T10:48:42.6655975Z pass 2025-09-07T10:48:46.3791930Z /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. 2025-09-07T10:48:46.3794515Z import pynvml # type: ignore[import] 2025-09-07T10:48:49.0717042Z 2025-09-07T10:48:56.5143967Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:48:56.5144362Z loading model: 0it [00:07, ?it/s] 2025-09-07T10:48:56.5276919Z cuda eval sam 2025-09-07T10:49:48.3639273Z pass 2025-09-07T10:49:52.5216823Z /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. 2025-09-07T10:49:52.5219020Z import pynvml # type: ignore[import] 2025-09-07T10:49:55.0061932Z 2025-09-07T10:51:12.3559462Z loading model: 0it [00:00, ?it/s]Warning: Custom flash attention kernels were written specifically for A100. 2025-09-07T10:51:12.3560590Z We will try to read previously created kernel configurations from /var/lib/jenkins/workspace/flash_4_configs.p. 2025-09-07T10:51:12.3561256Z You can disable this kernel by setting SEGMENT_ANYTHING_FAST_USE_FLASH_4=0 2025-09-07T10:51:12.3561773Z Loading best configs from file /var/lib/jenkins/workspace/flash_4_configs.p 2025-09-07T10:51:19.4712208Z 2025-09-07T10:51:19.4712623Z loading model: 0it [01:24, ?it/s] 2025-09-07T10:51:19.4755855Z cuda eval sam_fast 2025-09-07T10:53:52.3836320Z pass 2025-09-07T10:53:57.5476370Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:53:57.5485745Z import pynvml # type: ignore[import] 2025-09-07T10:54:00.1408861Z 2025-09-07T10:54:01.3711216Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:54:01.3711780Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:54:01.3713577Z cuda eval soft_actor_critic 2025-09-07T10:54:04.4192311Z pass 2025-09-07T10:54:07.3725684Z /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. 2025-09-07T10:54:07.3727200Z import pynvml # type: ignore[import] 2025-09-07T10:54:09.8651966Z 2025-09-07T10:54:11.2993024Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:54:11.2993394Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:54:11.3055837Z cuda eval speech_transformer 2025-09-07T10:54:18.7307370Z W0907 10:54:18.730000 187984 site-packages/torch/_inductor/utils.py:2298] [7/0_1] DeviceCopy in input program 2025-09-07T10:54:19.7903960Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7904361Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7904667Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7904976Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7905257Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7905538Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7905831Z cudagraph partition due to non gpu ops 2025-09-07T10:54:19.7906124Z cudagraph partition due to DeviceCopy ops 2025-09-07T10:54:19.8142663Z cudagraph partition into 2 partitions 2025-09-07T10:54:33.3584905Z W0907 10:54:33.357000 187984 site-packages/torch/_inductor/utils.py:2298] [13/0_1] DeviceCopy in input program 2025-09-07T10:54:34.7187563Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7187967Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7188340Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7188645Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7189458Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7189746Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7190029Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7190718Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7191030Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7191312Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7191651Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7192006Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7192314Z cudagraph partition due to non gpu ops 2025-09-07T10:54:34.7192608Z cudagraph partition due to DeviceCopy ops 2025-09-07T10:54:35.1311547Z cudagraph partition into 2 partitions 2025-09-07T10:54:36.6887719Z pass 2025-09-07T10:54:39.7517123Z /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. 2025-09-07T10:54:39.7518271Z import pynvml # type: ignore[import] 2025-09-07T10:54:42.3377398Z 2025-09-07T10:54:43.3976865Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:54:43.3977234Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:54:43.3991330Z cuda eval squeezenet1_1 2025-09-07T10:54:48.6460689Z pass 2025-09-07T10:54:50.9977127Z accuracy pass_rate=87.50% 2025-09-07T10:54:50.9988880Z calls_captured gmean=0.00x mean=553.500x 2025-09-07T10:54:50.9992541Z unique_graphs gmean=0.00x mean=1.500x 2025-09-07T10:54:50.9995668Z graph_breaks gmean=0.00x mean=1.250x 2025-09-07T10:54:50.9998997Z unique_graph_breaks gmean=0.00x mean=0.250x 2025-09-07T10:54:51.0002557Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:54:51.0005806Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:54:51.0009060Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:54:51.0010048Z compilation_latency mean=18.002 seconds 2025-09-07T10:54:51.8266715Z + [[ 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* ]] 2025-09-07T10:54:51.8268111Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:54:51.8268397Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T10:54:51.8269766Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 7 --freezing --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T10:54:52.3788645Z /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. 2025-09-07T10:54:52.3789818Z import pynvml # type: ignore[import] 2025-09-07T10:54:56.3775276Z /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. 2025-09-07T10:54:56.3777135Z import pynvml # type: ignore[import] 2025-09-07T10:54:58.9095957Z 2025-09-07T10:55:00.8314011Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:55:00.8314340Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:55:00.8378183Z cuda eval resnet50 2025-09-07T10:55:16.3591151Z Autotune Choices Stats: 2025-09-07T10:55:16.3593752Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_58", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009824000298976898, "best_triton_pos": 0} 2025-09-07T10:55:16.3642982Z AUTOTUNE addmm(12544x256, 12544x64, 64x256) 2025-09-07T10:55:16.3643746Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T10:55:16.3644781Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:16.3645567Z triton_mm_58 0.0098 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 2025-09-07T10:55:16.3646539Z triton_mm_61 0.0099 ms 99.7% 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 2025-09-07T10:55:16.3647944Z triton_mm_62 0.0099 ms 99.4% 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 2025-09-07T10:55:16.3648933Z triton_mm_63 0.0099 ms 99.0% 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 2025-09-07T10:55:16.3649885Z triton_mm_56 0.0100 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=2, num_warps=4 2025-09-07T10:55:16.3651128Z triton_mm_59 0.0100 ms 97.8% 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 2025-09-07T10:55:16.3652082Z triton_mm_60 0.0101 ms 97.2% 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 2025-09-07T10:55:16.3653049Z triton_mm_64 0.0101 ms 96.8% 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 2025-09-07T10:55:16.3654086Z triton_mm_67 0.0102 ms 96.2% 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 2025-09-07T10:55:16.3655134Z triton_mm_66 0.0108 ms 91.4% 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 2025-09-07T10:55:16.3656054Z SingleProcess AUTOTUNE benchmarking takes 0.3383 seconds and 0.0004 seconds precompiling for 21 choices 2025-09-07T10:55:17.3130813Z Autotune Choices Stats: 2025-09-07T10:55:17.3132938Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.011296000331640244, "best_triton_pos": 1, "best_triton_time": 0.011296000331640244, "best_triton_kernel": "triton_mm_164", "best_triton_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"} 2025-09-07T10:55:17.3177578Z AUTOTUNE addmm(12544x128, 12544x256, 256x128) 2025-09-07T10:55:17.3177967Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:55:17.3178375Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:17.3178771Z bias_addmm 0.0113 ms 100.0% 2025-09-07T10:55:17.3179532Z triton_mm_164 0.0113 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 2025-09-07T10:55:17.3180942Z triton_mm_168 0.0114 ms 99.2% 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 2025-09-07T10:55:17.3182159Z triton_mm_175 0.0119 ms 94.9% 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 2025-09-07T10:55:17.3183467Z triton_mm_174 0.0119 ms 94.6% 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 2025-09-07T10:55:17.3185304Z triton_mm_167 0.0121 ms 93.4% 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 2025-09-07T10:55:17.3186576Z triton_mm_170 0.0122 ms 92.9% 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 2025-09-07T10:55:17.3187839Z triton_mm_166 0.0122 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=3, num_warps=4 2025-09-07T10:55:17.3189329Z triton_mm_171 0.0123 ms 92.2% 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 2025-09-07T10:55:17.3190739Z triton_mm_173 0.0130 ms 86.7% 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 2025-09-07T10:55:17.3191867Z SingleProcess AUTOTUNE benchmarking takes 0.2835 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:17.8633480Z Autotune Choices Stats: 2025-09-07T10:55:17.8634930Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_242", "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": 0.009088000282645226, "best_triton_pos": 0} 2025-09-07T10:55:17.8681786Z AUTOTUNE addmm(3136x512, 3136x128, 128x512) 2025-09-07T10:55:17.8682156Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T10:55:17.8682568Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:17.8683477Z triton_mm_242 0.0091 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 2025-09-07T10:55:17.8684993Z triton_mm_243 0.0092 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:55:17.8686605Z triton_mm_247 0.0092 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:17.8687630Z bias_addmm 0.0093 ms 97.6% 2025-09-07T10:55:17.8688599Z triton_mm_244 0.0093 ms 97.6% 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 2025-09-07T10:55:17.8690515Z triton_mm_246 0.0093 ms 97.3% 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 2025-09-07T10:55:17.8692135Z triton_mm_248 0.0094 ms 96.9% 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 2025-09-07T10:55:17.8693727Z triton_mm_245 0.0094 ms 96.6% 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 2025-09-07T10:55:17.8695115Z triton_mm_249 0.0095 ms 95.9% 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 2025-09-07T10:55:17.8696381Z triton_mm_241 0.0096 ms 94.7% 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 2025-09-07T10:55:17.8697494Z SingleProcess AUTOTUNE benchmarking takes 0.2814 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:18.7142357Z Autotune Choices Stats: 2025-09-07T10:55:18.7144125Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_18", "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=4, num_warps=4", "best_time": 0.007712000049650669, "best_triton_pos": 0} 2025-09-07T10:55:18.7188540Z AUTOTUNE addmm(12544x64, 12544x64, 64x64) 2025-09-07T10:55:18.7188850Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T10:55:18.7189188Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:18.7189948Z triton_mm_18 0.0077 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 2025-09-07T10:55:18.7191779Z triton_mm_17 0.0080 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:55:18.7192879Z triton_mm_23 0.0080 ms 96.0% 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 2025-09-07T10:55:18.7193932Z triton_mm_10 0.0082 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 2025-09-07T10:55:18.7195189Z triton_mm_9 0.0083 ms 93.4% 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 2025-09-07T10:55:18.7196324Z triton_mm_13 0.0083 ms 92.7% 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 2025-09-07T10:55:18.7197453Z triton_mm_14 0.0083 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:55:18.7198604Z triton_mm_15 0.0083 ms 92.7% 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 2025-09-07T10:55:18.7199746Z triton_mm_7 0.0085 ms 90.9% 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 2025-09-07T10:55:18.7201018Z triton_mm_8 0.0085 ms 90.9% 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 2025-09-07T10:55:18.7202028Z SingleProcess AUTOTUNE benchmarking takes 0.2619 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:55:19.2318606Z Autotune Choices Stats: 2025-09-07T10:55:19.2319814Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_80", "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": 0.01065600011497736, "best_triton_pos": 0} 2025-09-07T10:55:19.2670124Z AUTOTUNE addmm(12544x64, 12544x256, 256x64) 2025-09-07T10:55:19.2670610Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:55:19.2670993Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:19.2671797Z triton_mm_80 0.0107 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 2025-09-07T10:55:19.2672911Z triton_mm_86 0.0108 ms 98.5% 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 2025-09-07T10:55:19.2674021Z triton_mm_76 0.0108 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:55:19.2675322Z triton_mm_70 0.0109 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:55:19.2676794Z triton_mm_79 0.0112 ms 95.4% 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 2025-09-07T10:55:19.2677512Z bias_addmm 0.0113 ms 94.6% 2025-09-07T10:55:19.2678217Z triton_mm_85 0.0113 ms 94.3% 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 2025-09-07T10:55:19.2679408Z triton_mm_72 0.0115 ms 92.5% 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 2025-09-07T10:55:19.2680919Z triton_mm_78 0.0115 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=3, num_warps=4 2025-09-07T10:55:19.2682067Z triton_mm_83 0.0115 ms 92.5% 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 2025-09-07T10:55:19.2683086Z SingleProcess AUTOTUNE benchmarking takes 0.2878 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:55:19.5700083Z Autotune Choices Stats: 2025-09-07T10:55:19.5701775Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.010751999914646149, "best_triton_pos": 1, "best_triton_time": 0.010975999757647514, "best_triton_kernel": "triton_mm_356", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:55:19.5898982Z AUTOTUNE addmm(3136x256, 3136x512, 512x256) 2025-09-07T10:55:19.5899348Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:55:19.5899732Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:19.5900109Z bias_addmm 0.0108 ms 100.0% 2025-09-07T10:55:19.5900986Z triton_mm_356 0.0110 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:19.5902133Z triton_mm_351 0.0113 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:55:19.5903324Z triton_mm_358 0.0119 ms 90.3% 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 2025-09-07T10:55:19.5904488Z triton_mm_355 0.0119 ms 90.1% 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 2025-09-07T10:55:19.5905752Z triton_mm_362 0.0120 ms 89.6% 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 2025-09-07T10:55:19.5906915Z triton_mm_361 0.0124 ms 87.0% 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 2025-09-07T10:55:19.5908071Z triton_mm_352 0.0124 ms 86.4% 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 2025-09-07T10:55:19.5909224Z triton_mm_345 0.0125 ms 86.2% 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 2025-09-07T10:55:19.5910486Z triton_mm_354 0.0126 ms 85.1% 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 2025-09-07T10:55:19.5911495Z SingleProcess AUTOTUNE benchmarking takes 0.2897 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:19.9643842Z Autotune Choices Stats: 2025-09-07T10:55:19.9645144Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_432", "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=4, num_warps=8", "best_time": 0.008736000396311283, "best_triton_pos": 0} 2025-09-07T10:55:20.0023021Z AUTOTUNE addmm(784x1024, 784x256, 256x1024) 2025-09-07T10:55:20.0023350Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:55:20.0023705Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:20.0024457Z triton_mm_432 0.0087 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 2025-09-07T10:55:20.0026112Z triton_mm_429 0.0091 ms 96.5% 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 2025-09-07T10:55:20.0027262Z triton_mm_434 0.0091 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:20.0028395Z triton_mm_433 0.0093 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 2025-09-07T10:55:20.0029121Z bias_addmm 0.0095 ms 92.2% 2025-09-07T10:55:20.0029840Z triton_mm_436 0.0095 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 2025-09-07T10:55:20.0031398Z triton_mm_431 0.0101 ms 86.7% 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 2025-09-07T10:55:20.0032521Z triton_mm_439 0.0101 ms 86.7% 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 2025-09-07T10:55:20.0033642Z triton_mm_435 0.0101 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 2025-09-07T10:55:20.0034799Z triton_mm_440 0.0102 ms 85.6% 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 2025-09-07T10:55:20.0035734Z SingleProcess AUTOTUNE benchmarking takes 0.3052 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:21.1139710Z Autotune Choices Stats: 2025-09-07T10:55:21.1141074Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_217", "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": 0.009440000168979168, "best_triton_pos": 0} 2025-09-07T10:55:21.1434558Z AUTOTUNE addmm(3136x128, 3136x512, 512x128) 2025-09-07T10:55:21.1434958Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:55:21.1435430Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:21.1436257Z triton_mm_217 0.0094 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 2025-09-07T10:55:21.1437422Z triton_mm_221 0.0101 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:21.1438150Z bias_addmm 0.0102 ms 92.8% 2025-09-07T10:55:21.1438857Z triton_mm_216 0.0105 ms 90.2% 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 2025-09-07T10:55:21.1440002Z triton_mm_210 0.0109 ms 86.3% 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 2025-09-07T10:55:21.1441804Z triton_mm_220 0.0110 ms 85.5% 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 2025-09-07T10:55:21.1442935Z triton_mm_212 0.0111 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:55:21.1444072Z triton_mm_213 0.0113 ms 83.3% 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 2025-09-07T10:55:21.1445438Z triton_mm_211 0.0116 ms 81.0% 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 2025-09-07T10:55:21.1446427Z triton_mm_223 0.0117 ms 80.8% 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 2025-09-07T10:55:21.1447260Z SingleProcess AUTOTUNE benchmarking takes 0.2960 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:21.6973330Z Autotune Choices Stats: 2025-09-07T10:55:21.6974559Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_629", "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": 0.009983999654650688, "best_triton_pos": 0} 2025-09-07T10:55:21.7096050Z AUTOTUNE addmm(784x512, 784x1024, 1024x512) 2025-09-07T10:55:21.7096377Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:55:21.7096749Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:21.7097479Z triton_mm_629 0.0100 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 2025-09-07T10:55:21.7098143Z bias_addmm 0.0102 ms 97.5% 2025-09-07T10:55:21.7098756Z triton_mm_633 0.0111 ms 89.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:21.7099743Z triton_mm_628 0.0126 ms 79.2% 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 2025-09-07T10:55:21.7101091Z triton_mm_625 0.0129 ms 77.6% 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 2025-09-07T10:55:21.7102069Z triton_mm_632 0.0132 ms 75.4% 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 2025-09-07T10:55:21.7103162Z triton_mm_639 0.0133 ms 75.2% 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 2025-09-07T10:55:21.7104129Z triton_mm_622 0.0145 ms 68.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:55:21.7105138Z triton_mm_624 0.0145 ms 68.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:55:21.7105812Z addmm 0.0149 ms 67.1% 2025-09-07T10:55:21.7106280Z SingleProcess AUTOTUNE benchmarking takes 0.2806 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:22.0969918Z Autotune Choices Stats: 2025-09-07T10:55:22.0971734Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_707", "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": 0.009279999881982803, "best_triton_pos": 0} 2025-09-07T10:55:22.1429278Z AUTOTUNE addmm(196x2048, 196x512, 512x2048) 2025-09-07T10:55:22.1429609Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:55:22.1429951Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:22.1430879Z triton_mm_707 0.0093 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 2025-09-07T10:55:22.1431941Z triton_mm_711 0.0097 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:22.1432610Z bias_addmm 0.0099 ms 93.5% 2025-09-07T10:55:22.1433567Z triton_mm_706 0.0104 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 2025-09-07T10:55:22.1434615Z triton_mm_710 0.0106 ms 87.6% 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 2025-09-07T10:55:22.1435704Z triton_mm_702 0.0108 ms 86.1% 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 2025-09-07T10:55:22.1436829Z triton_mm_700 0.0109 ms 85.0% 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 2025-09-07T10:55:22.1437964Z triton_mm_703 0.0111 ms 83.8% 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 2025-09-07T10:55:22.1439102Z triton_mm_701 0.0115 ms 81.0% 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 2025-09-07T10:55:22.1440412Z triton_mm_717 0.0116 ms 80.1% 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 2025-09-07T10:55:22.1441428Z SingleProcess AUTOTUNE benchmarking takes 0.3246 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:22.9696138Z Autotune Choices Stats: 2025-09-07T10:55:22.9697112Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_400", "best_kernel_desc": "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", "best_time": 0.009344000369310379, "best_triton_pos": 0} 2025-09-07T10:55:22.9795721Z AUTOTUNE addmm(784x256, 784x1024, 1024x256) 2025-09-07T10:55:22.9796064Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:55:22.9796396Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:22.9797113Z triton_mm_400 0.0093 ms 100.0% 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 2025-09-07T10:55:22.9798111Z triton_mm_404 0.0098 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=5, num_warps=4 2025-09-07T10:55:22.9798731Z bias_addmm 0.0105 ms 89.3% 2025-09-07T10:55:22.9799323Z triton_mm_408 0.0114 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:22.9800622Z triton_mm_399 0.0124 ms 75.6% 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 2025-09-07T10:55:22.9801592Z triton_mm_398 0.0124 ms 75.3% 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 2025-09-07T10:55:22.9802933Z triton_mm_403 0.0127 ms 73.7% 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 2025-09-07T10:55:22.9803895Z triton_mm_407 0.0129 ms 72.5% 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 2025-09-07T10:55:22.9804856Z triton_mm_397 0.0131 ms 71.6% 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 2025-09-07T10:55:22.9806058Z triton_mm_414 0.0133 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 2025-09-07T10:55:22.9806912Z SingleProcess AUTOTUNE benchmarking takes 0.2775 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:23.6339663Z Autotune Choices Stats: 2025-09-07T10:55:23.6341405Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.011008000001311302, "best_triton_pos": 1, "best_triton_time": 0.011776000261306763, "best_triton_kernel": "triton_mm_677", "best_triton_kernel_desc": "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"} 2025-09-07T10:55:23.6399506Z AUTOTUNE addmm(196x512, 196x2048, 2048x512) 2025-09-07T10:55:23.6399796Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T10:55:23.6400112Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:23.6400575Z bias_addmm 0.0110 ms 100.0% 2025-09-07T10:55:23.6401215Z triton_mm_677 0.0118 ms 93.5% 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 2025-09-07T10:55:23.6402221Z triton_mm_681 0.0125 ms 88.2% 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 2025-09-07T10:55:23.6403195Z triton_mm_685 0.0142 ms 77.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:23.6403810Z addmm 0.0151 ms 73.0% 2025-09-07T10:55:23.6404373Z triton_mm_676 0.0180 ms 61.1% 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 2025-09-07T10:55:23.6405337Z triton_mm_691 0.0183 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=5, num_warps=8 2025-09-07T10:55:23.6406305Z triton_mm_675 0.0185 ms 59.4% 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 2025-09-07T10:55:23.6407266Z triton_mm_674 0.0192 ms 57.2% 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 2025-09-07T10:55:23.6408219Z triton_mm_680 0.0192 ms 57.2% 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 2025-09-07T10:55:23.6409064Z SingleProcess AUTOTUNE benchmarking takes 0.2844 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:24.4746881Z Autotune Choices Stats: 2025-09-07T10:55:24.4748395Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.05929600074887276, "best_triton_pos": 1, "best_triton_time": 0.07388799637556076, "best_triton_kernel": "triton_convolution2d_0", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:24.5400549Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T10:55:24.5400883Z strides: [150528, 1, 672, 3], [147, 1, 21, 3] 2025-09-07T10:55:24.5401187Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:24.5401468Z convolution 0.0593 ms 100.0% 2025-09-07T10:55:24.5402205Z triton_convolution2d_0 0.0739 ms 80.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.5403851Z triton_convolution2d_3 0.0760 ms 78.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.5405069Z triton_convolution2d_4 0.0831 ms 71.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.5406319Z triton_convolution2d_2 0.1203 ms 49.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:24.5407488Z triton_convolution2d_5 0.1252 ms 47.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.5408648Z triton_convolution2d_1 0.2674 ms 22.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.5409568Z SingleProcess AUTOTUNE benchmarking takes 0.2609 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T10:55:24.6410594Z Autotune Choices Stats: 2025-09-07T10:55:24.6412051Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013663999736309052, "best_triton_pos": 1, "best_triton_time": 0.017216000705957413, "best_triton_kernel": "triton_convolution2d_29", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:55:24.6534114Z AUTOTUNE convolution(4x64x56x56, 64x64x3x3) 2025-09-07T10:55:24.6534462Z strides: [200704, 1, 3584, 64], [576, 1, 192, 64] 2025-09-07T10:55:24.6534786Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:24.6535090Z convolution 0.0137 ms 100.0% 2025-09-07T10:55:24.6535853Z triton_convolution2d_29 0.0172 ms 79.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.6537126Z triton_convolution2d_28 0.0176 ms 77.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.6538354Z triton_convolution2d_27 0.0183 ms 74.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.6539572Z triton_convolution2d_24 0.0214 ms 63.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.6541025Z triton_convolution2d_30 0.0239 ms 57.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.6542548Z triton_convolution2d_25 0.0300 ms 45.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.6543897Z triton_convolution2d_26 0.0503 ms 27.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:24.6544888Z SingleProcess AUTOTUNE benchmarking takes 0.1125 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:24.7721493Z Autotune Choices Stats: 2025-09-07T10:55:24.7723081Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013088000006973743, "best_triton_pos": 1, "best_triton_time": 0.030271999537944794, "best_triton_kernel": "triton_convolution2d_180", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:24.7772155Z AUTOTUNE convolution(4x128x56x56, 128x128x3x3) 2025-09-07T10:55:24.7772497Z strides: [401408, 1, 7168, 128], [1152, 1, 384, 128] 2025-09-07T10:55:24.7772818Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:24.7773120Z convolution 0.0131 ms 100.0% 2025-09-07T10:55:24.7773863Z triton_convolution2d_180 0.0303 ms 43.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.7775108Z triton_convolution2d_181 0.0337 ms 38.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.7776460Z triton_convolution2d_179 0.0370 ms 35.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.7777620Z triton_convolution2d_182 0.0375 ms 34.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:24.7778761Z triton_convolution2d_176 0.0456 ms 28.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.7779899Z triton_convolution2d_177 0.0515 ms 25.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:24.7781327Z triton_convolution2d_178 0.1036 ms 12.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:24.7782243Z SingleProcess AUTOTUNE benchmarking takes 0.1181 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:24.8747263Z Autotune Choices Stats: 2025-09-07T10:55:24.8748382Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_206", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.012319999746978283, "best_triton_pos": 0} 2025-09-07T10:55:24.8944275Z AUTOTUNE convolution(4x256x56x56, 512x256x1x1) 2025-09-07T10:55:24.8944790Z strides: [802816, 1, 14336, 256], [256, 1, 1, 1] 2025-09-07T10:55:24.8945267Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:24.8946518Z triton_convolution2d_206 0.0123 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:24.8947582Z convolution 0.0126 ms 97.5% 2025-09-07T10:55:24.8948272Z triton_convolution2d_205 0.0136 ms 90.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:24.8949414Z triton_convolution2d_207 0.0137 ms 89.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:24.8951047Z triton_convolution2d_208 0.0140 ms 87.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:24.8952210Z triton_convolution2d_202 0.0168 ms 73.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:24.8953352Z triton_convolution2d_203 0.0169 ms 72.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:24.8954490Z triton_convolution2d_204 0.0290 ms 42.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:55:24.8955394Z SingleProcess AUTOTUNE benchmarking takes 0.1164 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.0076269Z Autotune Choices Stats: 2025-09-07T10:55:25.0077727Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011872000060975552, "best_triton_pos": 1, "best_triton_time": 0.029279999434947968, "best_triton_kernel": "triton_convolution2d_232", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.0126357Z AUTOTUNE convolution(4x128x28x28, 128x128x3x3) 2025-09-07T10:55:25.0126716Z strides: [100352, 1, 3584, 128], [1152, 1, 384, 128] 2025-09-07T10:55:25.0127044Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.0127345Z convolution 0.0119 ms 100.0% 2025-09-07T10:55:25.0128097Z triton_convolution2d_232 0.0293 ms 40.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.0129341Z triton_convolution2d_233 0.0325 ms 36.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.0130961Z triton_convolution2d_231 0.0380 ms 31.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.0132214Z triton_convolution2d_234 0.0393 ms 30.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.0133463Z triton_convolution2d_228 0.0448 ms 26.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.0134716Z triton_convolution2d_229 0.0470 ms 25.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.0136350Z triton_convolution2d_230 0.0990 ms 12.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:25.0137331Z SingleProcess AUTOTUNE benchmarking takes 0.1177 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.1645767Z Autotune Choices Stats: 2025-09-07T10:55:25.1647416Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014208000153303146, "best_triton_pos": 1, "best_triton_time": 0.054368000477552414, "best_triton_kernel": "triton_convolution2d_367", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.1697036Z AUTOTUNE convolution(4x256x28x28, 256x256x3x3) 2025-09-07T10:55:25.1697401Z strides: [200704, 1, 7168, 256], [2304, 1, 768, 256] 2025-09-07T10:55:25.1697728Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.1698035Z convolution 0.0142 ms 100.0% 2025-09-07T10:55:25.1698809Z triton_convolution2d_367 0.0544 ms 26.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.1700074Z triton_convolution2d_369 0.0684 ms 20.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.1701658Z triton_convolution2d_366 0.0692 ms 20.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.1702978Z triton_convolution2d_368 0.0746 ms 19.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.1704218Z triton_convolution2d_364 0.0958 ms 14.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.1705445Z triton_convolution2d_363 0.0984 ms 14.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.1706820Z triton_convolution2d_365 0.1905 ms 7.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:25.1707800Z SingleProcess AUTOTUNE benchmarking takes 0.1528 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.2747080Z Autotune Choices Stats: 2025-09-07T10:55:25.2748318Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013088000006973743, "best_triton_pos": 1, "best_triton_time": 0.01679999940097332, "best_triton_kernel": "triton_convolution2d_393", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.2799679Z AUTOTUNE convolution(4x512x28x28, 1024x512x1x1) 2025-09-07T10:55:25.2800017Z strides: [401408, 1, 14336, 512], [512, 1, 1, 1] 2025-09-07T10:55:25.2800497Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.2800789Z convolution 0.0131 ms 100.0% 2025-09-07T10:55:25.2801550Z triton_convolution2d_393 0.0168 ms 77.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:25.2803111Z triton_convolution2d_392 0.0196 ms 66.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:25.2804370Z triton_convolution2d_394 0.0198 ms 66.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:25.2805639Z triton_convolution2d_395 0.0200 ms 65.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:25.2807034Z triton_convolution2d_389 0.0258 ms 50.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:25.2808170Z triton_convolution2d_390 0.0263 ms 49.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:25.2809309Z triton_convolution2d_391 0.0461 ms 28.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:55:25.2810349Z SingleProcess AUTOTUNE benchmarking takes 0.1095 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.4276946Z Autotune Choices Stats: 2025-09-07T10:55:25.4278351Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013887999579310417, "best_triton_pos": 1, "best_triton_time": 0.05385600030422211, "best_triton_kernel": "triton_convolution2d_419", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.4327448Z AUTOTUNE convolution(4x256x14x14, 256x256x3x3) 2025-09-07T10:55:25.4327786Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T10:55:25.4328101Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.4328382Z convolution 0.0139 ms 100.0% 2025-09-07T10:55:25.4329137Z triton_convolution2d_419 0.0539 ms 25.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.4330557Z triton_convolution2d_418 0.0694 ms 20.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.4331812Z triton_convolution2d_421 0.0725 ms 19.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.4333047Z triton_convolution2d_420 0.0739 ms 18.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.4334276Z triton_convolution2d_416 0.0905 ms 15.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.4335501Z triton_convolution2d_415 0.1015 ms 13.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.4336806Z triton_convolution2d_417 0.1864 ms 7.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:25.4337911Z SingleProcess AUTOTUNE benchmarking takes 0.1520 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.6463039Z Autotune Choices Stats: 2025-09-07T10:55:25.6464469Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.017343999817967415, "best_triton_pos": 1, "best_triton_time": 0.10838399827480316, "best_triton_kernel": "triton_convolution2d_644", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.6514030Z AUTOTUNE convolution(4x512x14x14, 512x512x3x3) 2025-09-07T10:55:25.6514666Z strides: [100352, 1, 7168, 512], [4608, 1, 1536, 512] 2025-09-07T10:55:25.6515006Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.6515292Z convolution 0.0173 ms 100.0% 2025-09-07T10:55:25.6516036Z triton_convolution2d_644 0.1084 ms 16.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.6517481Z triton_convolution2d_646 0.1316 ms 13.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.6518768Z triton_convolution2d_643 0.1319 ms 13.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.6520038Z triton_convolution2d_645 0.1423 ms 12.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.6521694Z triton_convolution2d_641 0.1962 ms 8.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.6522971Z triton_convolution2d_640 0.2173 ms 8.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.6524232Z triton_convolution2d_642 0.2506 ms 6.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:25.6525228Z SingleProcess AUTOTUNE benchmarking takes 0.2108 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.7576795Z Autotune Choices Stats: 2025-09-07T10:55:25.7578180Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013120000250637531, "best_triton_pos": 1, "best_triton_time": 0.02723200060427189, "best_triton_kernel": "triton_convolution2d_670", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.7627502Z AUTOTUNE convolution(4x1024x14x14, 2048x1024x1x1) 2025-09-07T10:55:25.7627861Z strides: [200704, 1, 14336, 1024], [1024, 1, 1, 1] 2025-09-07T10:55:25.7628164Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.7628447Z convolution 0.0131 ms 100.0% 2025-09-07T10:55:25.7629186Z triton_convolution2d_670 0.0272 ms 48.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:25.7630563Z triton_convolution2d_672 0.0323 ms 40.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:25.7632080Z triton_convolution2d_669 0.0324 ms 40.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:25.7633313Z triton_convolution2d_671 0.0334 ms 39.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:55:25.7634550Z triton_convolution2d_667 0.0447 ms 29.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:25.7635923Z triton_convolution2d_666 0.0461 ms 28.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:55:25.7637174Z triton_convolution2d_668 0.0585 ms 22.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:55:25.7638093Z SingleProcess AUTOTUNE benchmarking takes 0.1106 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:25.9614437Z Autotune Choices Stats: 2025-09-07T10:55:25.9615814Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016543999314308167, "best_triton_pos": 1, "best_triton_time": 0.10780800133943558, "best_triton_kernel": "triton_convolution2d_696", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:55:25.9665562Z AUTOTUNE convolution(4x512x7x7, 512x512x3x3) 2025-09-07T10:55:25.9665910Z strides: [25088, 1, 3584, 512], [4608, 1, 1536, 512] 2025-09-07T10:55:25.9666258Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:55:25.9666603Z convolution 0.0165 ms 100.0% 2025-09-07T10:55:25.9667364Z triton_convolution2d_696 0.1078 ms 15.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.9668623Z triton_convolution2d_695 0.1331 ms 12.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.9669879Z triton_convolution2d_698 0.1375 ms 12.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.9672357Z triton_convolution2d_697 0.1410 ms 11.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:55:25.9673589Z triton_convolution2d_694 0.1731 ms 9.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:55:25.9674818Z triton_convolution2d_693 0.1941 ms 8.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.9676045Z triton_convolution2d_692 0.2040 ms 8.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:55:25.9677245Z SingleProcess AUTOTUNE benchmarking takes 0.2031 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:55:26.5286536Z Autotune Choices Stats: 2025-09-07T10:55:26.5287601Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_767", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.01071999967098236, "best_triton_pos": 0} 2025-09-07T10:55:26.5344859Z AUTOTUNE addmm(4x1000, 4x2048, 2048x1000) 2025-09-07T10:55:26.5345165Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T10:55:26.5345498Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:26.5346695Z triton_mm_767 0.0107 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:55:26.5347455Z bias_addmm 0.0112 ms 95.4% 2025-09-07T10:55:26.5348074Z triton_mm_771 0.0114 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:55:26.5349052Z triton_mm_775 0.0140 ms 76.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:26.5350019Z triton_mm_779 0.0153 ms 70.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:55:26.5350967Z addmm 0.0154 ms 69.8% 2025-09-07T10:55:26.5351558Z triton_mm_766 0.0167 ms 64.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:55:26.5352511Z triton_mm_765 0.0181 ms 59.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:55:26.5353481Z triton_mm_770 0.0184 ms 58.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:55:26.5354434Z triton_mm_764 0.0185 ms 58.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:55:26.5355283Z SingleProcess AUTOTUNE benchmarking takes 0.5636 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:55:28.8865327Z pass 2025-09-07T10:55:32.0033334Z /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. 2025-09-07T10:55:32.0034580Z import pynvml # type: ignore[import] 2025-09-07T10:55:34.4877666Z 2025-09-07T10:55:34.6398771Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:55:34.6399282Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:55:34.6399732Z cuda eval resnet50_quantized_qat 2025-09-07T10:55:34.6405392Z Traceback (most recent call last): 2025-09-07T10:55:34.6406085Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:55:34.6406758Z ) = runner.load_model( 2025-09-07T10:55:34.6407435Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T10:55:34.6408164Z benchmark = benchmark_cls( 2025-09-07T10:55:34.6408711Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T10:55:34.6409341Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T10:55:34.6410161Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T10:55:34.6412123Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T10:55:34.6412760Z NotImplementedError: The eval test only supports CPU. 2025-09-07T10:55:34.6413137Z 2025-09-07T10:55:34.6413259Z model_fail_to_load 2025-09-07T10:55:36.1210557Z /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. 2025-09-07T10:55:36.1212376Z import pynvml # type: ignore[import] 2025-09-07T10:55:38.7501620Z 2025-09-07T10:55:40.3588351Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:55:40.3588873Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:55:40.3645989Z cuda eval resnext50_32x4d 2025-09-07T10:55:55.9696393Z Autotune Choices Stats: 2025-09-07T10:55:55.9698783Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_91", "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": 0.01104000024497509, "best_triton_pos": 0} 2025-09-07T10:55:55.9953865Z AUTOTUNE addmm(12544x256, 12544x128, 128x256) 2025-09-07T10:55:55.9954194Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T10:55:55.9954522Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:55.9955358Z triton_mm_91 0.0110 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 2025-09-07T10:55:55.9956366Z triton_mm_95 0.0111 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 2025-09-07T10:55:55.9957368Z triton_mm_93 0.0112 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 2025-09-07T10:55:55.9958356Z triton_mm_96 0.0113 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:55:55.9959310Z triton_mm_88 0.0113 ms 97.5% 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 2025-09-07T10:55:55.9960422Z triton_mm_92 0.0113 ms 97.5% 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 2025-09-07T10:55:55.9961412Z triton_mm_94 0.0114 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:55.9962032Z bias_addmm 0.0116 ms 95.6% 2025-09-07T10:55:55.9962623Z triton_mm_98 0.0116 ms 95.6% 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 2025-09-07T10:55:55.9963583Z triton_mm_99 0.0117 ms 94.0% 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 2025-09-07T10:55:55.9964419Z SingleProcess AUTOTUNE benchmarking takes 0.3091 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:56.3030903Z Autotune Choices Stats: 2025-09-07T10:55:56.3032411Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_150", "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": 0.012608000077307224, "best_triton_pos": 0} 2025-09-07T10:55:56.3241941Z AUTOTUNE addmm(12544x256, 12544x256, 256x256) 2025-09-07T10:55:56.3242454Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:55:56.3243504Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:56.3244527Z triton_mm_150 0.0126 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 2025-09-07T10:55:56.3245467Z bias_addmm 0.0127 ms 99.2% 2025-09-07T10:55:56.3246370Z triton_mm_156 0.0132 ms 95.2% 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 2025-09-07T10:55:56.3247836Z triton_mm_152 0.0134 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 2025-09-07T10:55:56.3249650Z triton_mm_149 0.0136 ms 92.9% 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 2025-09-07T10:55:56.3251394Z triton_mm_148 0.0137 ms 92.1% 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 2025-09-07T10:55:56.3252852Z triton_mm_153 0.0140 ms 90.4% 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 2025-09-07T10:55:56.3254282Z triton_mm_145 0.0145 ms 87.0% 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 2025-09-07T10:55:56.3255722Z triton_mm_155 0.0153 ms 82.6% 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 2025-09-07T10:55:56.3257181Z triton_mm_154 0.0158 ms 79.8% 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 2025-09-07T10:55:56.3258454Z SingleProcess AUTOTUNE benchmarking takes 0.2901 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:56.9982464Z Autotune Choices Stats: 2025-09-07T10:55:56.9984072Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_14", "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": 0.008224000222980976, "best_triton_pos": 0} 2025-09-07T10:55:57.0287474Z AUTOTUNE addmm(12544x128, 12544x64, 64x128) 2025-09-07T10:55:57.0287949Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T10:55:57.0288409Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:57.0289408Z triton_mm_14 0.0082 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 2025-09-07T10:55:57.0291379Z triton_mm_18 0.0085 ms 96.3% 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=4, num_warps=4 2025-09-07T10:55:57.0292855Z triton_mm_23 0.0086 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 2025-09-07T10:55:57.0294313Z triton_mm_24 0.0086 ms 95.2% 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 2025-09-07T10:55:57.0295776Z triton_mm_13 0.0087 ms 94.8% 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 2025-09-07T10:55:57.0297236Z triton_mm_17 0.0087 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 2025-09-07T10:55:57.0298675Z triton_mm_19 0.0088 ms 93.8% 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 2025-09-07T10:55:57.0300903Z triton_mm_20 0.0088 ms 93.8% 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 2025-09-07T10:55:57.0302346Z triton_mm_10 0.0088 ms 93.1% 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 2025-09-07T10:55:57.0303844Z triton_mm_12 0.0090 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:55:57.0305081Z SingleProcess AUTOTUNE benchmarking takes 0.4160 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:57.3547174Z Autotune Choices Stats: 2025-09-07T10:55:57.3549057Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.009952000342309475, "best_triton_pos": 1, "best_triton_time": 0.010111999697983265, "best_triton_kernel": "triton_mm_210", "best_triton_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"} 2025-09-07T10:55:57.3691951Z AUTOTUNE addmm(3136x512, 3136x256, 256x512) 2025-09-07T10:55:57.3692376Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:55:57.3692830Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:57.3693293Z bias_addmm 0.0100 ms 100.0% 2025-09-07T10:55:57.3694177Z triton_mm_210 0.0101 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 2025-09-07T10:55:57.3695644Z triton_mm_214 0.0102 ms 97.8% 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 2025-09-07T10:55:57.3697109Z triton_mm_220 0.0102 ms 97.2% 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 2025-09-07T10:55:57.3698554Z triton_mm_213 0.0106 ms 94.2% 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 2025-09-07T10:55:57.3699973Z triton_mm_217 0.0107 ms 93.1% 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 2025-09-07T10:55:57.3701661Z triton_mm_216 0.0108 ms 91.7% 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 2025-09-07T10:55:57.3703213Z triton_mm_212 0.0110 ms 90.7% 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 2025-09-07T10:55:57.3704666Z triton_mm_221 0.0110 ms 90.4% 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 2025-09-07T10:55:57.3706122Z triton_mm_219 0.0114 ms 87.1% 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 2025-09-07T10:55:57.3707378Z SingleProcess AUTOTUNE benchmarking takes 0.2830 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:57.6841849Z Autotune Choices Stats: 2025-09-07T10:55:57.6843702Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.011711999773979187, "best_triton_pos": 1, "best_triton_time": 0.01235199999064207, "best_triton_kernel": "triton_mm_305", "best_triton_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"} 2025-09-07T10:55:57.6989639Z AUTOTUNE addmm(3136x512, 3136x512, 512x512) 2025-09-07T10:55:57.6990108Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:55:57.6990739Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:57.6991188Z bias_addmm 0.0117 ms 100.0% 2025-09-07T10:55:57.6992104Z triton_mm_305 0.0124 ms 94.8% 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 2025-09-07T10:55:57.6993584Z triton_mm_316 0.0124 ms 94.8% 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 2025-09-07T10:55:57.6995471Z triton_mm_309 0.0124 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 2025-09-07T10:55:57.6997044Z triton_mm_315 0.0125 ms 93.6% 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 2025-09-07T10:55:57.6998561Z triton_mm_308 0.0135 ms 86.9% 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 2025-09-07T10:55:57.7000042Z triton_mm_312 0.0137 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=4, num_warps=8 2025-09-07T10:55:57.7001745Z triton_mm_310 0.0140 ms 83.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:57.7003249Z triton_mm_307 0.0144 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=3, num_warps=4 2025-09-07T10:55:57.7004715Z triton_mm_311 0.0145 ms 80.8% 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 2025-09-07T10:55:57.7005997Z SingleProcess AUTOTUNE benchmarking takes 0.2782 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:58.1559045Z Autotune Choices Stats: 2025-09-07T10:55:58.1560708Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_374", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009375999681651592, "best_triton_pos": 0} 2025-09-07T10:55:58.1765999Z AUTOTUNE addmm(784x1024, 784x512, 512x1024) 2025-09-07T10:55:58.1766488Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:55:58.1766999Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:58.1768055Z triton_mm_374 0.0094 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:58.1769067Z bias_addmm 0.0097 ms 96.4% 2025-09-07T10:55:58.1769986Z triton_mm_373 0.0102 ms 92.1% 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 2025-09-07T10:55:58.1771630Z triton_mm_369 0.0105 ms 89.3% 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 2025-09-07T10:55:58.1773104Z triton_mm_380 0.0111 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 2025-09-07T10:55:58.1774610Z triton_mm_372 0.0112 ms 83.7% 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 2025-09-07T10:55:58.1776551Z triton_mm_376 0.0113 ms 83.2% 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 2025-09-07T10:55:58.1778049Z triton_mm_379 0.0115 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=3, num_warps=4 2025-09-07T10:55:58.1779554Z triton_mm_370 0.0115 ms 81.4% 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 2025-09-07T10:55:58.1781273Z triton_mm_371 0.0124 ms 75.9% 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 2025-09-07T10:55:58.1783056Z SingleProcess AUTOTUNE benchmarking takes 0.2891 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:58.5227755Z Autotune Choices Stats: 2025-09-07T10:55:58.5229227Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_545", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.011296000331640244, "best_triton_pos": 0} 2025-09-07T10:55:58.5296043Z AUTOTUNE addmm(784x1024, 784x1024, 1024x1024) 2025-09-07T10:55:58.5296540Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:55:58.5297031Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:58.5298089Z triton_mm_545 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:58.5299061Z bias_addmm 0.0113 ms 99.7% 2025-09-07T10:55:58.5299953Z triton_mm_540 0.0135 ms 83.8% 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 2025-09-07T10:55:58.5301697Z triton_mm_551 0.0135 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 2025-09-07T10:55:58.5303294Z triton_mm_544 0.0137 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 2025-09-07T10:55:58.5304792Z triton_mm_541 0.0139 ms 81.5% 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 2025-09-07T10:55:58.5306306Z triton_mm_550 0.0149 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=3, num_warps=4 2025-09-07T10:55:58.5307846Z triton_mm_543 0.0152 ms 74.2% 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 2025-09-07T10:55:58.5309343Z triton_mm_547 0.0153 ms 73.7% 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 2025-09-07T10:55:58.5310510Z addmm 0.0159 ms 71.0% 2025-09-07T10:55:58.5311207Z SingleProcess AUTOTUNE benchmarking takes 0.2725 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:59.0192164Z Autotune Choices Stats: 2025-09-07T10:55:59.0193698Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_605", "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": 0.010432000271975994, "best_triton_pos": 0} 2025-09-07T10:55:59.0533266Z AUTOTUNE addmm(196x2048, 196x1024, 1024x2048) 2025-09-07T10:55:59.0533738Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:55:59.0534822Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:59.0535903Z triton_mm_605 0.0104 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 2025-09-07T10:55:59.0536911Z bias_addmm 0.0116 ms 89.6% 2025-09-07T10:55:59.0537842Z triton_mm_601 0.0132 ms 78.7% 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 2025-09-07T10:55:59.0539387Z triton_mm_604 0.0133 ms 78.6% 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 2025-09-07T10:55:59.0541774Z triton_mm_615 0.0133 ms 78.6% 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 2025-09-07T10:55:59.0543378Z triton_mm_608 0.0142 ms 73.4% 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 2025-09-07T10:55:59.0544895Z triton_mm_600 0.0146 ms 71.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:55:59.0545854Z addmm 0.0151 ms 68.9% 2025-09-07T10:55:59.0546743Z triton_mm_598 0.0152 ms 68.6% 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 2025-09-07T10:55:59.0548270Z triton_mm_609 0.0153 ms 68.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:59.0549609Z SingleProcess AUTOTUNE benchmarking takes 0.3114 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:55:59.3999149Z Autotune Choices Stats: 2025-09-07T10:55:59.4001590Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.011935999616980553, "best_triton_pos": 1, "best_triton_time": 0.012160000391304493, "best_triton_kernel": "triton_mm_582", "best_triton_kernel_desc": "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"} 2025-09-07T10:55:59.4377440Z AUTOTUNE addmm(196x1024, 196x2048, 2048x1024) 2025-09-07T10:55:59.4377901Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T10:55:59.4378395Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:55:59.4378904Z bias_addmm 0.0119 ms 100.0% 2025-09-07T10:55:59.4379867Z triton_mm_582 0.0122 ms 98.2% 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 2025-09-07T10:55:59.4381615Z triton_mm_586 0.0129 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:55:59.4383241Z triton_mm_590 0.0146 ms 82.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:55:59.4384211Z addmm 0.0155 ms 77.1% 2025-09-07T10:55:59.4385104Z triton_mm_596 0.0184 ms 65.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:55:59.4386592Z triton_mm_581 0.0187 ms 63.9% 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 2025-09-07T10:55:59.4388086Z triton_mm_580 0.0195 ms 61.3% 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 2025-09-07T10:55:59.4390091Z triton_mm_585 0.0200 ms 59.8% 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 2025-09-07T10:55:59.4391732Z triton_mm_579 0.0202 ms 59.0% 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 2025-09-07T10:55:59.4393039Z SingleProcess AUTOTUNE benchmarking takes 0.3227 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T10:56:03.0620581Z pass 2025-09-07T10:56:06.1291827Z /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. 2025-09-07T10:56:06.1294495Z import pynvml # type: ignore[import] 2025-09-07T10:56:08.6200920Z 2025-09-07T10:56:15.8288899Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:56:15.8289275Z loading model: 0it [00:07, ?it/s] 2025-09-07T10:56:15.8407579Z cuda eval sam 2025-09-07T10:57:08.1320831Z Autotune Choices Stats: 2025-09-07T10:57:08.1322769Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.08057600259780884, "best_triton_pos": 1, "best_triton_time": 0.09366399794816971, "best_triton_kernel": "triton_mm_132", "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"} 2025-09-07T10:57:08.1382406Z AUTOTUNE mm(4096x1280, 1280x5120) 2025-09-07T10:57:08.1382964Z strides: [1280, 1], [1, 1280] 2025-09-07T10:57:08.1383375Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:08.1383782Z mm 0.0806 ms 100.0% 2025-09-07T10:57:08.1384712Z triton_mm_132 0.0937 ms 86.0% 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 2025-09-07T10:57:08.1386248Z triton_mm_133 0.1029 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=5, num_warps=8 2025-09-07T10:57:08.1387784Z triton_mm_131 0.1140 ms 70.7% 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 2025-09-07T10:57:08.1389303Z triton_mm_126 0.1285 ms 62.7% 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 2025-09-07T10:57:08.1391280Z triton_mm_127 0.1345 ms 59.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:08.1392803Z triton_mm_125 0.1538 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 2025-09-07T10:57:08.1394255Z triton_mm_124 0.1574 ms 51.2% 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 2025-09-07T10:57:08.1395690Z triton_mm_129 0.1582 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=4, num_warps=8 2025-09-07T10:57:08.1397201Z triton_mm_130 0.1605 ms 50.2% 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 2025-09-07T10:57:08.1398466Z SingleProcess AUTOTUNE benchmarking takes 0.6589 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T10:57:09.6548828Z Autotune Choices Stats: 2025-09-07T10:57:09.6550039Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.0719359964132309, "best_triton_pos": 1, "best_triton_time": 0.10185600072145462, "best_triton_kernel": "triton_mm_4710", "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"} 2025-09-07T10:57:09.6605745Z AUTOTUNE mm(4096x5120, 5120x1280) 2025-09-07T10:57:09.6606092Z strides: [5120, 1], [1, 5120] 2025-09-07T10:57:09.6606394Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:09.6606683Z mm 0.0719 ms 100.0% 2025-09-07T10:57:09.6607337Z triton_mm_4710 0.1019 ms 70.6% 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 2025-09-07T10:57:09.6608837Z triton_mm_4711 0.1019 ms 70.6% 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 2025-09-07T10:57:09.6609913Z triton_mm_4709 0.1072 ms 67.1% 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 2025-09-07T10:57:09.6611473Z triton_mm_4705 0.1158 ms 62.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:09.6612465Z triton_mm_4704 0.1194 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 2025-09-07T10:57:09.6613443Z triton_mm_4703 0.1612 ms 44.6% 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 2025-09-07T10:57:09.6614435Z triton_mm_4707 0.1672 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 2025-09-07T10:57:09.6615420Z triton_mm_4706 0.1684 ms 42.7% 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 2025-09-07T10:57:09.6616461Z triton_mm_4702 0.1700 ms 42.3% 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 2025-09-07T10:57:09.6617324Z SingleProcess AUTOTUNE benchmarking takes 0.5609 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:10.9993927Z Autotune Choices Stats: 2025-09-07T10:57:10.9995021Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_4786", "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": 0.008031999692320824, "best_triton_pos": 0} 2025-09-07T10:57:11.0064551Z AUTOTUNE mm(4096x256, 256x128) 2025-09-07T10:57:11.0064846Z strides: [1, 4096], [1, 256] 2025-09-07T10:57:11.0065134Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:11.0065833Z triton_mm_4786 0.0080 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 2025-09-07T10:57:11.0066989Z triton_mm_4789 0.0082 ms 97.7% 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 2025-09-07T10:57:11.0068003Z triton_mm_4785 0.0083 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=3, num_warps=8 2025-09-07T10:57:11.0068973Z triton_mm_4781 0.0086 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:11.0069961Z triton_mm_4790 0.0086 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:11.0071370Z mm 0.0087 ms 91.9% 2025-09-07T10:57:11.0071950Z triton_mm_4792 0.0088 ms 91.6% 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 2025-09-07T10:57:11.0072928Z triton_mm_4788 0.0089 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=4, num_warps=8 2025-09-07T10:57:11.0073896Z triton_mm_4780 0.0089 ms 90.0% 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 2025-09-07T10:57:11.0075117Z triton_mm_4779 0.0091 ms 88.7% 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 2025-09-07T10:57:11.0075990Z SingleProcess AUTOTUNE benchmarking takes 0.5729 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:57:11.4798263Z Autotune Choices Stats: 2025-09-07T10:57:11.4799367Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4822", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00723200011998415, "best_triton_pos": 0} 2025-09-07T10:57:11.5271546Z AUTOTUNE mm(5x256, 256x2048) 2025-09-07T10:57:11.5271986Z strides: [256, 1], [1, 256] 2025-09-07T10:57:11.5272287Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:11.5272986Z triton_mm_4822 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:11.5274051Z triton_mm_4818 0.0073 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:11.5274685Z mm 0.0074 ms 97.4% 2025-09-07T10:57:11.5275250Z triton_mm_4816 0.0075 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:11.5276216Z triton_mm_4821 0.0075 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:11.5277183Z triton_mm_4815 0.0076 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:11.5278168Z triton_mm_4830 0.0076 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:11.5279067Z triton_mm_4817 0.0076 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:11.5279963Z triton_mm_4825 0.0078 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:11.5281038Z triton_mm_4826 0.0078 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:11.5281833Z SingleProcess AUTOTUNE benchmarking takes 0.2568 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:12.0234136Z Autotune Choices Stats: 2025-09-07T10:57:12.0235146Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5223", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.0066559999249875546, "best_triton_pos": 0} 2025-09-07T10:57:12.0527426Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T10:57:12.0527707Z strides: [256, 1], [1, 256] 2025-09-07T10:57:12.0527973Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:12.0528672Z triton_mm_5223 0.0067 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.0529681Z triton_mm_5227 0.0068 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.0531291Z triton_mm_5222 0.0068 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.0532290Z triton_mm_5226 0.0069 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.0533276Z triton_mm_5221 0.0069 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.0534242Z triton_mm_5220 0.0070 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:12.0535217Z triton_mm_5231 0.0070 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:12.0536189Z triton_mm_5235 0.0071 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:12.0537237Z triton_mm_5230 0.0072 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.0537812Z mm 0.0073 ms 91.6% 2025-09-07T10:57:12.0538226Z SingleProcess AUTOTUNE benchmarking takes 0.2372 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:12.5198966Z Autotune Choices Stats: 2025-09-07T10:57:12.5200012Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5244", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006432000081986189, "best_triton_pos": 0} 2025-09-07T10:57:12.5257889Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T10:57:12.5258164Z strides: [256, 1], [1, 256] 2025-09-07T10:57:12.5258448Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:12.5259134Z triton_mm_5244 0.0064 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.5260182Z triton_mm_5240 0.0066 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.5261331Z triton_mm_5243 0.0068 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.5262288Z triton_mm_5238 0.0068 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.5263345Z triton_mm_5252 0.0069 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:12.5264306Z triton_mm_5239 0.0070 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.5265639Z triton_mm_5248 0.0070 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:12.5266606Z triton_mm_5237 0.0071 ms 91.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:12.5267695Z triton_mm_5250 0.0071 ms 91.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:12.5268838Z triton_mm_5247 0.0074 ms 87.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.5269700Z SingleProcess AUTOTUNE benchmarking takes 0.2106 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:12.7469204Z Autotune Choices Stats: 2025-09-07T10:57:12.7470060Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5268", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006591999903321266, "best_triton_pos": 0} 2025-09-07T10:57:12.7529482Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T10:57:12.7529685Z strides: [256, 1], [1, 256] 2025-09-07T10:57:12.7529901Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:12.7530590Z triton_mm_5268 0.0066 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.7531425Z triton_mm_5272 0.0067 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.7532222Z triton_mm_5266 0.0067 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.7533006Z triton_mm_5276 0.0068 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:12.7533790Z triton_mm_5271 0.0069 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.7534564Z triton_mm_5267 0.0069 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.7535363Z triton_mm_5265 0.0070 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:12.7536147Z triton_mm_5280 0.0071 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:12.7536926Z triton_mm_5275 0.0072 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.7537699Z triton_mm_5278 0.0073 ms 90.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:12.7538383Z SingleProcess AUTOTUNE benchmarking takes 0.2072 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:12.9905833Z Autotune Choices Stats: 2025-09-07T10:57:12.9906807Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5313", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006527999881654978, "best_triton_pos": 0} 2025-09-07T10:57:12.9965920Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T10:57:12.9966144Z strides: [256, 1], [1, 256] 2025-09-07T10:57:12.9966375Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:12.9966994Z triton_mm_5313 0.0065 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.9967916Z triton_mm_5317 0.0067 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.9969087Z triton_mm_5312 0.0068 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:12.9969673Z mm 0.0068 ms 95.8% 2025-09-07T10:57:12.9970584Z triton_mm_5316 0.0069 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.9971491Z triton_mm_5311 0.0069 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:12.9972388Z triton_mm_5310 0.0070 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:12.9973302Z triton_mm_5321 0.0070 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:12.9974210Z triton_mm_5325 0.0070 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:12.9975112Z triton_mm_5320 0.0072 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:12.9975921Z SingleProcess AUTOTUNE benchmarking takes 0.2087 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:13.2474750Z Autotune Choices Stats: 2025-09-07T10:57:13.2475880Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5358", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006591999903321266, "best_triton_pos": 0} 2025-09-07T10:57:13.2535366Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T10:57:13.2535681Z strides: [256, 1], [1, 256] 2025-09-07T10:57:13.2535965Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:13.2536693Z triton_mm_5358 0.0066 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:13.2537905Z triton_mm_5361 0.0067 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:13.2539367Z triton_mm_5362 0.0067 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:13.2541121Z triton_mm_5357 0.0068 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:13.2542599Z triton_mm_5355 0.0070 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:13.2544782Z triton_mm_5356 0.0070 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:13.2546285Z triton_mm_5366 0.0070 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:13.2548001Z triton_mm_5368 0.0070 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:13.2549078Z triton_mm_5370 0.0071 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:13.2550491Z triton_mm_5365 0.0072 ms 91.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:13.2551448Z SingleProcess AUTOTUNE benchmarking takes 0.2236 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:13.8395989Z Autotune Choices Stats: 2025-09-07T10:57:13.8397222Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.07203199714422226, "best_triton_pos": 1, "best_triton_time": 0.09087999910116196, "best_triton_kernel": "triton_mm_24", "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"} 2025-09-07T10:57:13.8458543Z AUTOTUNE mm(4900x1280, 1280x3840) 2025-09-07T10:57:13.8458988Z strides: [1280, 1], [1, 1280] 2025-09-07T10:57:13.8459424Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:13.8459854Z mm 0.0720 ms 100.0% 2025-09-07T10:57:13.8461120Z triton_mm_24 0.0909 ms 79.3% 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 2025-09-07T10:57:13.8462906Z triton_mm_25 0.0953 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 2025-09-07T10:57:13.8464531Z triton_mm_23 0.1013 ms 71.1% 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 2025-09-07T10:57:13.8466153Z triton_mm_18 0.1107 ms 65.1% 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 2025-09-07T10:57:13.8467915Z triton_mm_19 0.1214 ms 59.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:13.8469128Z triton_mm_22 0.1342 ms 53.7% 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 2025-09-07T10:57:13.8470132Z triton_mm_17 0.1389 ms 51.9% 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 2025-09-07T10:57:13.8471230Z triton_mm_21 0.1440 ms 50.0% 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 2025-09-07T10:57:13.8472213Z triton_mm_16 0.1446 ms 49.8% 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 2025-09-07T10:57:13.8473051Z SingleProcess AUTOTUNE benchmarking takes 0.5252 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:14.4006048Z Autotune Choices Stats: 2025-09-07T10:57:14.4007473Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.029120000079274178, "best_triton_pos": 1, "best_triton_time": 0.03542400151491165, "best_triton_kernel": "triton_mm_114", "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"} 2025-09-07T10:57:14.4065669Z AUTOTUNE mm(4900x1280, 1280x1280) 2025-09-07T10:57:14.4065997Z strides: [1280, 1], [1, 1280] 2025-09-07T10:57:14.4066280Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:14.4066562Z mm 0.0291 ms 100.0% 2025-09-07T10:57:14.4070096Z triton_mm_114 0.0354 ms 82.2% 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 2025-09-07T10:57:14.4071766Z triton_mm_113 0.0367 ms 79.3% 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 2025-09-07T10:57:14.4072784Z triton_mm_112 0.0376 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 2025-09-07T10:57:14.4073760Z triton_mm_107 0.0391 ms 74.4% 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 2025-09-07T10:57:14.4074722Z triton_mm_108 0.0468 ms 62.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:14.4075719Z triton_mm_106 0.0512 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 2025-09-07T10:57:14.4076692Z triton_mm_110 0.0530 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 2025-09-07T10:57:14.4077664Z triton_mm_103 0.0545 ms 53.4% 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 2025-09-07T10:57:14.4078622Z triton_mm_105 0.0570 ms 51.1% 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 2025-09-07T10:57:14.4079364Z SingleProcess AUTOTUNE benchmarking takes 0.3412 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:15.5593364Z Autotune Choices Stats: 2025-09-07T10:57:15.5594404Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1138", "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": 0.030688000842928886, "best_triton_pos": 0} 2025-09-07T10:57:15.5655174Z AUTOTUNE mm(4096x1280, 1280x1280) 2025-09-07T10:57:15.5655480Z strides: [1280, 1], [1, 1280] 2025-09-07T10:57:15.5655797Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:15.5656487Z triton_mm_1138 0.0307 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 2025-09-07T10:57:15.5657502Z triton_mm_1139 0.0314 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 2025-09-07T10:57:15.5658500Z triton_mm_1140 0.0333 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=5, num_warps=8 2025-09-07T10:57:15.5659486Z triton_mm_1133 0.0343 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 2025-09-07T10:57:15.5661026Z triton_mm_1134 0.0393 ms 78.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:15.5662005Z triton_mm_1132 0.0432 ms 71.0% 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 2025-09-07T10:57:15.5663078Z triton_mm_1136 0.0446 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 2025-09-07T10:57:15.5664310Z triton_mm_1135 0.0456 ms 67.3% 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 2025-09-07T10:57:15.5665549Z triton_mm_1129 0.0463 ms 66.3% 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 2025-09-07T10:57:15.5666541Z triton_mm_1131 0.0521 ms 58.9% 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 2025-09-07T10:57:15.5667395Z SingleProcess AUTOTUNE benchmarking takes 0.3169 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:17.6384337Z Autotune Choices Stats: 2025-09-07T10:57:17.6386238Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_6", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.32422399520874023, "best_triton_pos": 0} 2025-09-07T10:57:17.6444942Z AUTOTUNE convolution(1x3x1024x1024, 1280x3x16x16) 2025-09-07T10:57:17.6445517Z strides: [3145728, 1048576, 1024, 1], [768, 256, 16, 1] 2025-09-07T10:57:17.6446093Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:17.6447410Z triton_convolution2d_6 0.3242 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:57:17.6449548Z triton_convolution2d_1 0.3354 ms 96.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:57:17.6451094Z triton_convolution2d_3 0.3501 ms 92.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:57:17.6451880Z convolution 0.4524 ms 71.7% 2025-09-07T10:57:17.6452616Z triton_convolution2d_5 0.5567 ms 58.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:57:17.6453849Z triton_convolution2d_4 0.5815 ms 55.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:57:17.6455078Z triton_convolution2d_0 0.6847 ms 47.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:57:17.6456315Z triton_convolution2d_2 1.6908 ms 19.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:57:17.6457301Z SingleProcess AUTOTUNE benchmarking takes 0.2887 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:57:17.9102932Z Autotune Choices Stats: 2025-09-07T10:57:17.9104557Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_42", "best_kernel_desc": "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", "best_time": 0.036288000643253326, "best_triton_pos": 0} 2025-09-07T10:57:17.9161899Z AUTOTUNE bmm(400x196x80, 400x80x196) 2025-09-07T10:57:17.9162380Z strides: [80, 32000, 1], [15680, 1, 80] 2025-09-07T10:57:17.9162845Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:17.9163934Z triton_bmm_42 0.0363 ms 100.0% 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 2025-09-07T10:57:17.9165822Z triton_bmm_36 0.0365 ms 99.4% 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 2025-09-07T10:57:17.9167818Z triton_bmm_39 0.0369 ms 98.3% 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 2025-09-07T10:57:17.9169413Z triton_bmm_40 0.0370 ms 98.2% 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 2025-09-07T10:57:17.9170637Z triton_bmm_43 0.0375 ms 96.8% 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 2025-09-07T10:57:17.9171551Z triton_bmm_35 0.0379 ms 95.8% 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=3, num_warps=4 2025-09-07T10:57:17.9172468Z triton_bmm_37 0.0398 ms 91.1% 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 2025-09-07T10:57:17.9173362Z triton_bmm_38 0.0414 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:17.9174267Z triton_bmm_32 0.0438 ms 82.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:17.9175162Z triton_bmm_41 0.0443 ms 82.0% 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 2025-09-07T10:57:17.9175950Z SingleProcess AUTOTUNE benchmarking takes 0.2704 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:18.1125780Z Autotune Choices Stats: 2025-09-07T10:57:18.1126843Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_52", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.012799999676644802, "best_triton_pos": 0} 2025-09-07T10:57:18.1184686Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T10:57:18.1184957Z strides: [448000, 80, 1], [1120, 1, 80] 2025-09-07T10:57:18.1185245Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:18.1185943Z triton_bmm_52 0.0128 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.1186940Z triton_bmm_59 0.0130 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.1187943Z triton_bmm_49 0.0132 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:18.1189079Z triton_bmm_48 0.0132 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:18.1190505Z triton_bmm_55 0.0132 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:18.1191481Z triton_bmm_54 0.0135 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:18.1192450Z triton_bmm_60 0.0135 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:18.1193664Z triton_bmm_56 0.0135 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.1194639Z triton_bmm_58 0.0137 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:57:18.1195609Z triton_bmm_51 0.0138 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:18.1196455Z SingleProcess AUTOTUNE benchmarking takes 0.2019 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T10:57:18.3576958Z Autotune Choices Stats: 2025-09-07T10:57:18.3578560Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_68", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013344000093638897, "best_triton_pos": 0} 2025-09-07T10:57:18.3635474Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T10:57:18.3635770Z strides: [80, 1120, 1], [1120, 1, 80] 2025-09-07T10:57:18.3636064Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:18.3636712Z triton_bmm_68 0.0133 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.3637711Z triton_bmm_64 0.0136 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:18.3638683Z triton_bmm_75 0.0136 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.3639670Z triton_bmm_70 0.0140 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:18.3640783Z triton_bmm_69 0.0140 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.3641751Z triton_bmm_71 0.0140 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:18.3642713Z triton_bmm_63 0.0141 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:18.3643668Z triton_bmm_67 0.0141 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:18.3644641Z triton_bmm_72 0.0141 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:18.3646202Z triton_bmm_73 0.0141 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:18.3647226Z SingleProcess AUTOTUNE benchmarking takes 0.2446 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T10:57:18.6391739Z Autotune Choices Stats: 2025-09-07T10:57:18.6392929Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "bmm", "best_time": 0.0342399999499321, "best_triton_pos": 1, "best_triton_time": 0.037696000188589096, "best_triton_kernel": "triton_bmm_94", "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"} 2025-09-07T10:57:18.6456152Z AUTOTUNE bmm(400x200x200, 400x200x80) 2025-09-07T10:57:18.6456510Z strides: [40000, 200, 1], [16000, 80, 1] 2025-09-07T10:57:18.6456822Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:18.6457519Z bmm 0.0342 ms 100.0% 2025-09-07T10:57:18.6458178Z triton_bmm_94 0.0377 ms 90.8% 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 2025-09-07T10:57:18.6459243Z triton_bmm_87 0.0383 ms 89.4% 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 2025-09-07T10:57:18.6460160Z triton_bmm_93 0.0385 ms 88.9% 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 2025-09-07T10:57:18.6461401Z triton_bmm_88 0.0389 ms 88.1% 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 2025-09-07T10:57:18.6462314Z triton_bmm_86 0.0400 ms 85.7% 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 2025-09-07T10:57:18.6463334Z triton_bmm_95 0.0405 ms 84.6% 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 2025-09-07T10:57:18.6464237Z triton_bmm_91 0.0409 ms 83.7% 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 2025-09-07T10:57:18.6465131Z triton_bmm_90 0.0426 ms 80.5% 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 2025-09-07T10:57:18.6466029Z triton_bmm_84 0.0449 ms 76.2% 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 2025-09-07T10:57:18.6466816Z SingleProcess AUTOTUNE benchmarking takes 0.2815 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:19.2536760Z Autotune Choices Stats: 2025-09-07T10:57:19.2538831Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.06400000303983688, "best_triton_pos": 1, "best_triton_time": 0.07740800082683563, "best_triton_kernel": "triton_mm_1046", "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"} 2025-09-07T10:57:19.2599604Z AUTOTUNE addmm(4096x3840, 4096x1280, 1280x3840) 2025-09-07T10:57:19.2600459Z strides: [0, 1], [1280, 1], [1, 1280] 2025-09-07T10:57:19.2600985Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:57:19.2601533Z bias_addmm 0.0640 ms 100.0% 2025-09-07T10:57:19.2602548Z triton_mm_1046 0.0774 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=3, num_warps=4 2025-09-07T10:57:19.2604147Z triton_mm_1047 0.0863 ms 74.1% 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 2025-09-07T10:57:19.2606169Z triton_mm_1045 0.0934 ms 68.5% 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 2025-09-07T10:57:19.2607159Z addmm 0.0979 ms 65.4% 2025-09-07T10:57:19.2608090Z triton_mm_1040 0.1008 ms 63.5% 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 2025-09-07T10:57:19.2609800Z triton_mm_1041 0.1099 ms 58.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:19.2611096Z triton_mm_1044 0.1167 ms 54.8% 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 2025-09-07T10:57:19.2612006Z triton_mm_1039 0.1172 ms 54.6% 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 2025-09-07T10:57:19.2612904Z triton_mm_1043 0.1204 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 2025-09-07T10:57:19.2613708Z SingleProcess AUTOTUNE benchmarking takes 0.5358 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T10:57:19.9456465Z Autotune Choices Stats: 2025-09-07T10:57:19.9458524Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "bmm", "best_time": 0.22220799326896667, "best_triton_pos": 1, "best_triton_time": 0.24665600061416626, "best_triton_kernel": "triton_bmm_1064", "best_triton_kernel_desc": "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"} 2025-09-07T10:57:19.9516226Z AUTOTUNE bmm(16x4096x80, 16x80x4096) 2025-09-07T10:57:19.9516500Z strides: [80, 1280, 1], [80, 1, 3840] 2025-09-07T10:57:19.9516789Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:19.9517049Z bmm 0.2222 ms 100.0% 2025-09-07T10:57:19.9517651Z triton_bmm_1064 0.2467 ms 90.1% 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 2025-09-07T10:57:19.9518663Z triton_bmm_1061 0.2670 ms 83.2% 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=3, num_warps=4 2025-09-07T10:57:19.9519804Z triton_bmm_1057 0.2697 ms 82.4% 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=3, num_warps=4 2025-09-07T10:57:19.9521084Z triton_bmm_1063 0.2757 ms 80.6% 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 2025-09-07T10:57:19.9522120Z triton_bmm_1060 0.2805 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:19.9523133Z triton_bmm_1058 0.2816 ms 78.9% 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 2025-09-07T10:57:19.9524147Z triton_bmm_1065 0.2863 ms 77.6% 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 2025-09-07T10:57:19.9525180Z triton_bmm_1062 0.2900 ms 76.6% 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 2025-09-07T10:57:19.9526192Z triton_bmm_1059 0.3109 ms 71.5% 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 2025-09-07T10:57:19.9527246Z SingleProcess AUTOTUNE benchmarking takes 0.6903 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:20.1707949Z Autotune Choices Stats: 2025-09-07T10:57:20.1709739Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_1083", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013887999579310417, "best_triton_pos": 0} 2025-09-07T10:57:20.1770986Z AUTOTUNE bmm(64x1024x80, 64x80x64) 2025-09-07T10:57:20.1771420Z strides: [81920, 80, 1], [5120, 1, 80] 2025-09-07T10:57:20.1771873Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:20.1773293Z triton_bmm_1083 0.0139 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:20.1775006Z triton_bmm_1078 0.0140 ms 99.3% 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=4 2025-09-07T10:57:20.1776610Z triton_bmm_1081 0.0140 ms 99.3% 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=4, num_warps=8 2025-09-07T10:57:20.1778185Z triton_bmm_1077 0.0144 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:20.1779913Z triton_bmm_1080 0.0144 ms 96.7% 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=3, num_warps=4 2025-09-07T10:57:20.1781000Z triton_bmm_1073 0.0144 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:20.1781908Z triton_bmm_1074 0.0145 ms 95.8% 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 2025-09-07T10:57:20.1782896Z triton_bmm_1076 0.0146 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:20.1783472Z bmm 0.0147 ms 94.8% 2025-09-07T10:57:20.1784015Z triton_bmm_1082 0.0147 ms 94.8% 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=2, num_warps=8 2025-09-07T10:57:20.1784811Z SingleProcess AUTOTUNE benchmarking takes 0.2242 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:57:20.8523593Z Autotune Choices Stats: 2025-09-07T10:57:20.8525224Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_1120", "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": 0.2134079933166504, "best_triton_pos": 0} 2025-09-07T10:57:20.8583816Z AUTOTUNE bmm(16x4096x4096, 16x4096x80) 2025-09-07T10:57:20.8584319Z strides: [16777216, 4096, 1], [80, 3840, 1] 2025-09-07T10:57:20.8584784Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:20.8585841Z triton_bmm_1120 0.2134 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 2025-09-07T10:57:20.8587485Z triton_bmm_1121 0.2140 ms 99.7% 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 2025-09-07T10:57:20.8588491Z bmm 0.2156 ms 99.0% 2025-09-07T10:57:20.8589500Z triton_bmm_1115 0.2292 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:20.8591367Z triton_bmm_1114 0.2393 ms 89.2% 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 2025-09-07T10:57:20.8592356Z triton_bmm_1111 0.2763 ms 77.2% 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 2025-09-07T10:57:20.8593329Z triton_bmm_1110 0.2774 ms 76.9% 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 2025-09-07T10:57:20.8594533Z triton_bmm_1113 0.2963 ms 72.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:20.8595522Z triton_bmm_1119 0.3039 ms 70.2% 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 2025-09-07T10:57:20.8596505Z triton_bmm_1116 0.3101 ms 68.8% 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 2025-09-07T10:57:20.8597362Z SingleProcess AUTOTUNE benchmarking takes 0.6788 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:57:21.3957772Z Autotune Choices Stats: 2025-09-07T10:57:21.3958760Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4661", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006688000168651342, "best_triton_pos": 0} 2025-09-07T10:57:21.4024637Z AUTOTUNE mm(5x256, 256x256) 2025-09-07T10:57:21.4025105Z strides: [256, 1], [1, 256] 2025-09-07T10:57:21.4025561Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:21.4026672Z triton_mm_4661 0.0067 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:21.4028298Z triton_mm_4665 0.0067 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:21.4030009Z triton_mm_4660 0.0068 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:21.4031347Z triton_mm_4659 0.0069 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:21.4032323Z triton_mm_4664 0.0069 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:21.4033294Z triton_mm_4673 0.0069 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:21.4034268Z triton_mm_4668 0.0071 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:21.4035240Z triton_mm_4658 0.0071 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:21.4036222Z triton_mm_4669 0.0073 ms 91.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:21.4037185Z triton_mm_4671 0.0073 ms 91.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:21.4038321Z SingleProcess AUTOTUNE benchmarking takes 0.2132 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:57:21.5557825Z Autotune Choices Stats: 2025-09-07T10:57:21.5559189Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013088000006973743, "best_triton_pos": 2, "best_triton_time": 0.036159999668598175, "best_triton_kernel": "triton_convolution2d_4716", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:57:21.5622008Z AUTOTUNE convolution(1x1280x64x64, 256x1280x1x1) 2025-09-07T10:57:21.5623098Z strides: [5242880, 4096, 64, 1], [1280, 1, 1, 1] 2025-09-07T10:57:21.5623622Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:21.5624090Z convolution 0.0131 ms 100.0% 2025-09-07T10:57:21.5624517Z conv1x1_via_mm 0.0248 ms 52.8% 2025-09-07T10:57:21.5625727Z triton_convolution2d_4716 0.0362 ms 36.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:21.5627741Z triton_convolution2d_4718 0.0446 ms 29.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:21.5629948Z triton_convolution2d_4715 0.0451 ms 29.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:21.5631600Z triton_convolution2d_4717 0.0477 ms 27.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:21.5632837Z triton_convolution2d_4712 0.0681 ms 19.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:21.5634060Z triton_convolution2d_4713 0.0685 ms 19.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:21.5635306Z triton_convolution2d_4714 0.0830 ms 15.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:57:21.5636286Z SingleProcess AUTOTUNE benchmarking takes 0.1571 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:57:21.7390722Z Autotune Choices Stats: 2025-09-07T10:57:21.7392107Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03110400028526783, "best_triton_pos": 1, "best_triton_time": 0.08899199962615967, "best_triton_kernel": "triton_convolution2d_4723", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:57:21.7453432Z AUTOTUNE convolution(1x256x64x64, 256x256x3x3) 2025-09-07T10:57:21.7453780Z strides: [1048576, 4096, 64, 1], [2304, 9, 3, 1] 2025-09-07T10:57:21.7454115Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:21.7454414Z convolution 0.0311 ms 100.0% 2025-09-07T10:57:21.7455192Z triton_convolution2d_4723 0.0890 ms 35.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:57:21.7456654Z triton_convolution2d_4722 0.0908 ms 34.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:57:21.7457933Z triton_convolution2d_4725 0.0927 ms 33.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:57:21.7459187Z triton_convolution2d_4720 0.1153 ms 27.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:57:21.7460857Z triton_convolution2d_4724 0.1170 ms 26.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:57:21.7462007Z triton_convolution2d_4719 0.1750 ms 17.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:57:21.7463230Z triton_convolution2d_4721 0.2818 ms 11.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:57:21.7464139Z SingleProcess AUTOTUNE benchmarking takes 0.1817 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:57:21.9482926Z Autotune Choices Stats: 2025-09-07T10:57:21.9484504Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_4730", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.005727999843657017, "best_triton_pos": 0} 2025-09-07T10:57:21.9552895Z AUTOTUNE mm(4096x2, 2x128) 2025-09-07T10:57:21.9553309Z strides: [2, 1], [128, 1] 2025-09-07T10:57:21.9553672Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:21.9554657Z triton_mm_4730 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:21.9556145Z triton_mm_4731 0.0059 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:21.9557660Z triton_mm_4737 0.0059 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:21.9559227Z triton_mm_4738 0.0060 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:21.9561238Z triton_mm_4733 0.0060 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:21.9562691Z triton_mm_4734 0.0060 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:21.9564150Z triton_mm_4727 0.0061 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:21.9565664Z triton_mm_4732 0.0061 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:57:21.9567134Z triton_mm_4736 0.0061 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:21.9568996Z triton_mm_4735 0.0061 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:21.9570500Z SingleProcess AUTOTUNE benchmarking takes 0.2082 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T10:57:22.1993819Z Autotune Choices Stats: 2025-09-07T10:57:22.1994836Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_4753", "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": 0.008767999708652496, "best_triton_pos": 0} 2025-09-07T10:57:22.2062180Z AUTOTUNE mm(4096x256, 256x256) 2025-09-07T10:57:22.2062462Z strides: [256, 1], [256, 1] 2025-09-07T10:57:22.2063126Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:22.2063860Z triton_mm_4753 0.0088 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 2025-09-07T10:57:22.2064554Z mm 0.0089 ms 98.2% 2025-09-07T10:57:22.2065205Z triton_mm_4756 0.0092 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:22.2066273Z triton_mm_4752 0.0092 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:22.2067355Z triton_mm_4754 0.0093 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:22.2068434Z triton_mm_4751 0.0094 ms 93.2% 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 2025-09-07T10:57:22.2069492Z triton_mm_4749 0.0095 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 2025-09-07T10:57:22.2070965Z triton_mm_4760 0.0098 ms 89.5% 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 2025-09-07T10:57:22.2072037Z triton_mm_4759 0.0100 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=3, num_warps=4 2025-09-07T10:57:22.2073108Z triton_mm_4755 0.0101 ms 86.4% 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 2025-09-07T10:57:22.2074033Z SingleProcess AUTOTUNE benchmarking takes 0.2502 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:57:22.4522620Z Autotune Choices Stats: 2025-09-07T10:57:22.4523778Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_4769", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00684799998998642, "best_triton_pos": 0} 2025-09-07T10:57:22.4591350Z AUTOTUNE addmm(5x128, 5x256, 256x128) 2025-09-07T10:57:22.4591657Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:57:22.4592034Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:57:22.4592808Z triton_mm_4769 0.0068 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:22.4593916Z triton_mm_4765 0.0070 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:22.4595304Z triton_mm_4764 0.0071 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:22.4596348Z triton_mm_4768 0.0071 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.4597390Z triton_mm_4763 0.0071 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:22.4598189Z bias_addmm 0.0073 ms 93.4% 2025-09-07T10:57:22.4598833Z triton_mm_4762 0.0074 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:22.4600092Z triton_mm_4777 0.0074 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:22.4601497Z triton_mm_4772 0.0075 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.4602477Z triton_mm_4773 0.0076 ms 90.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:22.4603324Z SingleProcess AUTOTUNE benchmarking takes 0.2523 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:57:22.6706579Z Autotune Choices Stats: 2025-09-07T10:57:22.6707773Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4800", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T10:57:22.6778110Z AUTOTUNE mm(5x128, 128x256) 2025-09-07T10:57:22.6778467Z strides: [128, 1], [1, 128] 2025-09-07T10:57:22.6778755Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:22.6779484Z triton_mm_4800 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:22.6781037Z triton_mm_4804 0.0062 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.6782130Z triton_mm_4799 0.0063 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:22.6783385Z triton_mm_4811 0.0063 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:22.6784447Z triton_mm_4813 0.0064 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:22.6785113Z mm 0.0065 ms 95.0% 2025-09-07T10:57:22.6785722Z triton_mm_4808 0.0065 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.6786795Z triton_mm_4810 0.0066 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.6787845Z triton_mm_4807 0.0067 ms 91.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:22.6788898Z triton_mm_4805 0.0068 ms 91.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:22.6790435Z SingleProcess AUTOTUNE benchmarking takes 0.2179 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T10:57:22.9070550Z Autotune Choices Stats: 2025-09-07T10:57:22.9072122Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4835", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.009375999681651592, "best_triton_pos": 0} 2025-09-07T10:57:22.9139404Z AUTOTUNE mm(5x2048, 2048x256) 2025-09-07T10:57:22.9139783Z strides: [2048, 1], [1, 2048] 2025-09-07T10:57:22.9140149Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:22.9141696Z triton_mm_4835 0.0094 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:22.9142665Z mm 0.0099 ms 95.1% 2025-09-07T10:57:22.9143639Z triton_mm_4839 0.0102 ms 91.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:22.9145129Z triton_mm_4843 0.0126 ms 74.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:22.9146593Z triton_mm_4847 0.0147 ms 63.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:22.9148028Z triton_mm_4834 0.0152 ms 61.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:22.9149457Z triton_mm_4833 0.0165 ms 56.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:22.9151074Z triton_mm_4838 0.0168 ms 55.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.9152474Z triton_mm_4832 0.0173 ms 54.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:22.9153923Z triton_mm_4842 0.0190 ms 49.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:22.9155204Z SingleProcess AUTOTUNE benchmarking takes 0.2355 seconds and 0.0004 seconds precompiling for 18 choices 2025-09-07T10:57:23.2014174Z Autotune Choices Stats: 2025-09-07T10:57:23.2015206Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_4892", "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=4, num_warps=8", "best_time": 0.00774399982765317, "best_triton_pos": 0} 2025-09-07T10:57:23.2084953Z AUTOTUNE mm(4096x128, 128x256) 2025-09-07T10:57:23.2085241Z strides: [128, 1], [1, 128] 2025-09-07T10:57:23.2085515Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:23.2086260Z triton_mm_4892 0.0077 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 2025-09-07T10:57:23.2087357Z triton_mm_4893 0.0078 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:23.2088469Z triton_mm_4896 0.0079 ms 97.6% 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 2025-09-07T10:57:23.2089862Z triton_mm_4894 0.0081 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:23.2091347Z triton_mm_4889 0.0081 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 2025-09-07T10:57:23.2092322Z triton_mm_4891 0.0082 ms 94.9% 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 2025-09-07T10:57:23.2093487Z triton_mm_4890 0.0083 ms 93.8% 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 2025-09-07T10:57:23.2094713Z triton_mm_4899 0.0083 ms 93.8% 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 2025-09-07T10:57:23.2095732Z triton_mm_4895 0.0083 ms 93.4% 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 2025-09-07T10:57:23.2096719Z triton_mm_4898 0.0084 ms 92.4% 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 2025-09-07T10:57:23.2097575Z SingleProcess AUTOTUNE benchmarking takes 0.2895 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:57:23.4486321Z Autotune Choices Stats: 2025-09-07T10:57:23.4487278Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_4905", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007040000054985285, "best_triton_pos": 0} 2025-09-07T10:57:23.4561032Z AUTOTUNE addmm(5x256, 5x256, 256x256) 2025-09-07T10:57:23.4561376Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:57:23.4561695Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:57:23.4562410Z triton_mm_4905 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:23.4563451Z triton_mm_4909 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:23.4564475Z triton_mm_4904 0.0072 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:23.4565470Z triton_mm_4903 0.0072 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:57:23.4566444Z triton_mm_4908 0.0072 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:23.4567413Z triton_mm_4902 0.0074 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:23.4568393Z triton_mm_4917 0.0075 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:23.4569016Z bias_addmm 0.0075 ms 94.0% 2025-09-07T10:57:23.4569607Z triton_mm_4912 0.0076 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:23.4571055Z triton_mm_4915 0.0076 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:23.4572150Z SingleProcess AUTOTUNE benchmarking takes 0.2467 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:57:23.7363573Z Autotune Choices Stats: 2025-09-07T10:57:23.7364779Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_4994", "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": 0.008320000022649765, "best_triton_pos": 0} 2025-09-07T10:57:23.7431956Z AUTOTUNE addmm(4096x128, 4096x256, 256x128) 2025-09-07T10:57:23.7432270Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:57:23.7432614Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:57:23.7433656Z triton_mm_4994 0.0083 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 2025-09-07T10:57:23.7434766Z triton_mm_4993 0.0086 ms 96.7% 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 2025-09-07T10:57:23.7435818Z triton_mm_4989 0.0090 ms 92.9% 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 2025-09-07T10:57:23.7436896Z triton_mm_4988 0.0091 ms 91.5% 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 2025-09-07T10:57:23.7437959Z triton_mm_4997 0.0092 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 2025-09-07T10:57:23.7439058Z triton_mm_4998 0.0092 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:23.7439749Z bias_addmm 0.0093 ms 89.0% 2025-09-07T10:57:23.7440833Z triton_mm_4987 0.0094 ms 88.1% 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 2025-09-07T10:57:23.7441900Z triton_mm_4996 0.0095 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:23.7442962Z triton_mm_5000 0.0095 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:23.7443909Z SingleProcess AUTOTUNE benchmarking takes 0.2781 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T10:57:23.9446537Z Autotune Choices Stats: 2025-09-07T10:57:23.9447583Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_5263", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006463999859988689, "best_triton_pos": 0} 2025-09-07T10:57:23.9517695Z AUTOTUNE addmm(1x32, 1x256, 256x32) 2025-09-07T10:57:23.9518012Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:57:23.9518357Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:57:23.9519138Z triton_mm_5263 0.0065 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:23.9520683Z triton_mm_5256 0.0068 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:23.9521740Z triton_mm_5262 0.0068 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=2 2025-09-07T10:57:23.9523025Z triton_mm_5255 0.0068 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:23.9523991Z triton_mm_5259 0.0068 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=2 2025-09-07T10:57:23.9524962Z triton_mm_5254 0.0069 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:23.9526046Z triton_mm_5261 0.0072 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=2 2025-09-07T10:57:23.9526856Z bias_addmm 0.0076 ms 84.9% 2025-09-07T10:57:23.9527451Z triton_mm_5260 0.0077 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=2 2025-09-07T10:57:23.9528061Z addmm 0.0096 ms 67.3% 2025-09-07T10:57:23.9528524Z SingleProcess AUTOTUNE benchmarking takes 0.1857 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T10:57:24.1247930Z Autotune Choices Stats: 2025-09-07T10:57:24.1248930Z {"num_choices": 14, "num_triton_choices": 13, "best_kernel": "triton_mm_5405", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.00800000037997961, "best_triton_pos": 0} 2025-09-07T10:57:24.1318504Z AUTOTUNE mm(4x32, 32x65536) 2025-09-07T10:57:24.1318780Z strides: [32, 1], [1, 32] 2025-09-07T10:57:24.1319056Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T10:57:24.1319783Z triton_mm_5405 0.0080 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:24.1321021Z triton_mm_5407 0.0081 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:57:24.1322071Z triton_mm_5411 0.0081 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:57:24.1323126Z triton_mm_5399 0.0083 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T10:57:24.1324171Z triton_mm_5402 0.0083 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:57:24.1325206Z triton_mm_5404 0.0083 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:57:24.1326246Z triton_mm_5406 0.0083 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:57:24.1327279Z triton_mm_5409 0.0083 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:57:24.1328313Z triton_mm_5410 0.0083 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:57:24.1329347Z triton_mm_5400 0.0084 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:57:24.1330684Z SingleProcess AUTOTUNE benchmarking takes 0.1734 seconds and 0.0002 seconds precompiling for 14 choices 2025-09-07T10:57:24.3121383Z Autotune Choices Stats: 2025-09-07T10:57:24.3122507Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_5456", "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": 0.006335999816656113, "best_triton_pos": 0} 2025-09-07T10:57:24.3194699Z AUTOTUNE addmm(1x4, 1x256, 256x4) 2025-09-07T10:57:24.3195010Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:57:24.3195664Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T10:57:24.3196431Z triton_mm_5456 0.0063 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 2025-09-07T10:57:24.3197798Z triton_mm_5448 0.0066 ms 96.1% 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 2025-09-07T10:57:24.3198876Z triton_mm_5452 0.0067 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T10:57:24.3199935Z triton_mm_5455 0.0067 ms 94.3% 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 2025-09-07T10:57:24.3201225Z triton_mm_5447 0.0068 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T10:57:24.3202289Z triton_mm_5454 0.0068 ms 93.8% 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 2025-09-07T10:57:24.3203349Z triton_mm_5449 0.0068 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T10:57:24.3204396Z triton_mm_5453 0.0080 ms 79.2% 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 2025-09-07T10:57:24.3205071Z addmm 0.0091 ms 70.0% 2025-09-07T10:57:24.3205694Z triton_mm_5451 0.0092 ms 69.0% 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 2025-09-07T10:57:24.3206615Z SingleProcess AUTOTUNE benchmarking takes 0.1868 seconds and 0.0003 seconds precompiling for 13 choices 2025-09-07T10:57:42.0581826Z pass 2025-09-07T10:57:47.2639687Z /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. 2025-09-07T10:57:47.2641813Z import pynvml # type: ignore[import] 2025-09-07T10:57:49.8478236Z 2025-09-07T10:58:17.5813411Z loading model: 0it [00:00, ?it/s]Warning: Custom flash attention kernels were written specifically for A100. 2025-09-07T10:58:17.5814338Z We will try to read previously created kernel configurations from /var/lib/jenkins/workspace/flash_4_configs.p. 2025-09-07T10:58:17.5815068Z You can disable this kernel by setting SEGMENT_ANYTHING_FAST_USE_FLASH_4=0 2025-09-07T10:58:17.5815685Z Loading best configs from file /var/lib/jenkins/workspace/flash_4_configs.p 2025-09-07T10:58:18.2288506Z 2025-09-07T10:58:18.2288973Z loading model: 0it [00:28, ?it/s] 2025-09-07T10:58:18.2330907Z cuda eval sam_fast 2025-09-07T11:00:06.5470740Z Autotune Choices Stats: 2025-09-07T11:00:06.5472561Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.0820159986615181, "best_triton_pos": 1, "best_triton_time": 0.09232000261545181, "best_triton_kernel": "triton_mm_94", "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"} 2025-09-07T11:00:06.5540438Z AUTOTUNE mm(4096x1280, 1280x5120) 2025-09-07T11:00:06.5540814Z strides: [1280, 1], [1, 1280] 2025-09-07T11:00:06.5541189Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:06.5541551Z mm 0.0820 ms 100.0% 2025-09-07T11:00:06.5542358Z triton_mm_94 0.0923 ms 88.8% 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 2025-09-07T11:00:06.5544342Z triton_mm_95 0.1023 ms 80.1% 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 2025-09-07T11:00:06.5545718Z triton_mm_93 0.1141 ms 71.9% 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 2025-09-07T11:00:06.5547088Z triton_mm_88 0.1282 ms 64.0% 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 2025-09-07T11:00:06.5548448Z triton_mm_89 0.1342 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:06.5549760Z triton_mm_87 0.1532 ms 53.5% 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 2025-09-07T11:00:06.5551242Z triton_mm_86 0.1537 ms 53.4% 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 2025-09-07T11:00:06.5552555Z triton_mm_91 0.1571 ms 52.2% 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 2025-09-07T11:00:06.5553875Z triton_mm_92 0.1600 ms 51.3% 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 2025-09-07T11:00:06.5555021Z SingleProcess AUTOTUNE benchmarking takes 0.5481 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:00:07.8578896Z Autotune Choices Stats: 2025-09-07T11:00:07.8580685Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.07363200187683105, "best_triton_pos": 1, "best_triton_time": 0.10246399790048599, "best_triton_kernel": "triton_mm_3523", "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"} 2025-09-07T11:00:07.8648123Z AUTOTUNE mm(4096x5120, 5120x1280) 2025-09-07T11:00:07.8648434Z strides: [5120, 1], [1, 5120] 2025-09-07T11:00:07.8648705Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:07.8648989Z mm 0.0736 ms 100.0% 2025-09-07T11:00:07.8649604Z triton_mm_3523 0.1025 ms 71.9% 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 2025-09-07T11:00:07.8650797Z triton_mm_3524 0.1036 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=5, num_warps=8 2025-09-07T11:00:07.8651824Z triton_mm_3518 0.1124 ms 65.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:07.8652819Z triton_mm_3522 0.1143 ms 64.4% 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 2025-09-07T11:00:07.8654261Z triton_mm_3517 0.1166 ms 63.1% 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 2025-09-07T11:00:07.8655241Z triton_mm_3516 0.1620 ms 45.5% 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 2025-09-07T11:00:07.8656220Z triton_mm_3520 0.1670 ms 44.1% 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 2025-09-07T11:00:07.8657418Z triton_mm_3519 0.1676 ms 43.9% 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 2025-09-07T11:00:07.8658746Z triton_mm_3515 0.1680 ms 43.8% 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 2025-09-07T11:00:07.8659619Z SingleProcess AUTOTUNE benchmarking takes 0.5668 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:00:08.2014551Z Autotune Choices Stats: 2025-09-07T11:00:08.2015608Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_3599", "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": 0.007872000336647034, "best_triton_pos": 0} 2025-09-07T11:00:08.2081520Z AUTOTUNE mm(4096x256, 256x128) 2025-09-07T11:00:08.2081834Z strides: [256, 1], [1, 256] 2025-09-07T11:00:08.2082112Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:08.2082814Z triton_mm_3599 0.0079 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 2025-09-07T11:00:08.2083851Z triton_mm_3598 0.0082 ms 96.5% 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 2025-09-07T11:00:08.2084514Z mm 0.0082 ms 95.7% 2025-09-07T11:00:08.2085112Z triton_mm_3602 0.0082 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:08.2086119Z triton_mm_3603 0.0085 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:08.2087118Z triton_mm_3594 0.0086 ms 91.1% 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 2025-09-07T11:00:08.2088216Z triton_mm_3601 0.0088 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 2025-09-07T11:00:08.2089187Z triton_mm_3593 0.0089 ms 88.8% 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 2025-09-07T11:00:08.2090158Z triton_mm_3605 0.0089 ms 88.5% 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 2025-09-07T11:00:08.2091708Z triton_mm_3592 0.0091 ms 86.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:08.2092610Z SingleProcess AUTOTUNE benchmarking takes 0.2390 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:00:08.6951589Z Autotune Choices Stats: 2025-09-07T11:00:08.6952745Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3631", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007296000141650438, "best_triton_pos": 0} 2025-09-07T11:00:08.7018496Z AUTOTUNE mm(7x256, 256x2048) 2025-09-07T11:00:08.7018787Z strides: [256, 1], [1, 256] 2025-09-07T11:00:08.7019066Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:08.7019766Z triton_mm_3631 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:08.7021241Z triton_mm_3635 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:08.7022766Z triton_mm_3630 0.0073 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:08.7023908Z triton_mm_3634 0.0075 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:08.7024921Z triton_mm_3629 0.0076 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:08.7025933Z triton_mm_3638 0.0076 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:08.7026930Z triton_mm_3628 0.0076 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:08.7028072Z triton_mm_3643 0.0077 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:08.7029068Z triton_mm_3639 0.0077 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:08.7029708Z mm 0.0079 ms 92.3% 2025-09-07T11:00:08.7030160Z SingleProcess AUTOTUNE benchmarking takes 0.2136 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:00:09.2021222Z Autotune Choices Stats: 2025-09-07T11:00:09.2022294Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4036", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006591999903321266, "best_triton_pos": 0} 2025-09-07T11:00:09.2088045Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T11:00:09.2088375Z strides: [256, 1], [1, 256] 2025-09-07T11:00:09.2088664Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:09.2089348Z triton_mm_4036 0.0066 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:09.2090717Z triton_mm_4040 0.0067 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:09.2091346Z mm 0.0069 ms 95.8% 2025-09-07T11:00:09.2091944Z triton_mm_4039 0.0069 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:09.2092954Z triton_mm_4034 0.0069 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:09.2093933Z triton_mm_4048 0.0070 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:09.2095303Z triton_mm_4035 0.0071 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:09.2096267Z triton_mm_4033 0.0072 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:09.2097242Z triton_mm_4044 0.0072 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:09.2098456Z triton_mm_4043 0.0073 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:09.2099492Z SingleProcess AUTOTUNE benchmarking takes 0.2134 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:00:09.9109117Z Autotune Choices Stats: 2025-09-07T11:00:09.9110883Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.026464000344276428, "best_triton_pos": 1, "best_triton_time": 0.031199999153614044, "best_triton_kernel": "triton_mm_834", "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"} 2025-09-07T11:00:09.9177426Z AUTOTUNE mm(4096x1280, 1280x1280) 2025-09-07T11:00:09.9177732Z strides: [1280, 1], [1, 1280] 2025-09-07T11:00:09.9178016Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:09.9178323Z mm 0.0265 ms 100.0% 2025-09-07T11:00:09.9178952Z triton_mm_834 0.0312 ms 84.8% 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 2025-09-07T11:00:09.9179975Z triton_mm_835 0.0314 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 2025-09-07T11:00:09.9181166Z triton_mm_836 0.0335 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 2025-09-07T11:00:09.9182139Z triton_mm_829 0.0340 ms 77.9% 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 2025-09-07T11:00:09.9183226Z triton_mm_830 0.0399 ms 66.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:09.9184224Z triton_mm_828 0.0433 ms 61.1% 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 2025-09-07T11:00:09.9185197Z triton_mm_832 0.0455 ms 58.2% 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 2025-09-07T11:00:09.9186186Z triton_mm_831 0.0456 ms 58.1% 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 2025-09-07T11:00:09.9187163Z triton_mm_825 0.0470 ms 56.3% 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 2025-09-07T11:00:09.9188093Z SingleProcess AUTOTUNE benchmarking takes 0.3215 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:00:11.0328401Z Autotune Choices Stats: 2025-09-07T11:00:11.0329774Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_6", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.3245440125465393, "best_triton_pos": 0} 2025-09-07T11:00:11.0398578Z AUTOTUNE convolution(1x3x1024x1024, 1280x3x16x16) 2025-09-07T11:00:11.0399266Z strides: [3145728, 1048576, 1024, 1], [768, 256, 16, 1] 2025-09-07T11:00:11.0399832Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:11.0401337Z triton_convolution2d_6 0.3245 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:00:11.0403414Z triton_convolution2d_1 0.3351 ms 96.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:00:11.0406105Z triton_convolution2d_3 0.3486 ms 93.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:00:11.0407360Z convolution 0.3618 ms 89.7% 2025-09-07T11:00:11.0408668Z triton_convolution2d_5 0.5529 ms 58.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:00:11.0410161Z triton_convolution2d_4 0.5768 ms 56.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:00:11.0411512Z triton_convolution2d_0 0.6902 ms 47.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:00:11.0412753Z triton_convolution2d_2 1.6921 ms 19.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:00:11.0413723Z SingleProcess AUTOTUNE benchmarking takes 0.2936 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:00:11.5654135Z Autotune Choices Stats: 2025-09-07T11:00:11.5656129Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.07257600128650665, "best_triton_pos": 1, "best_triton_time": 0.09167999774217606, "best_triton_kernel": "triton_mm_24", "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"} 2025-09-07T11:00:11.5727375Z AUTOTUNE mm(4900x1280, 1280x3840) 2025-09-07T11:00:11.5727810Z strides: [1280, 1], [1, 1280] 2025-09-07T11:00:11.5728220Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:11.5728653Z mm 0.0726 ms 100.0% 2025-09-07T11:00:11.5729612Z triton_mm_24 0.0917 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=3, num_warps=4 2025-09-07T11:00:11.5731679Z triton_mm_25 0.0956 ms 75.9% 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 2025-09-07T11:00:11.5733294Z triton_mm_23 0.1004 ms 72.3% 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 2025-09-07T11:00:11.5734838Z triton_mm_18 0.1177 ms 61.7% 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 2025-09-07T11:00:11.5736378Z triton_mm_19 0.1226 ms 59.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:11.5737935Z triton_mm_22 0.1324 ms 54.8% 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 2025-09-07T11:00:11.5739677Z triton_mm_17 0.1389 ms 52.2% 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 2025-09-07T11:00:11.5740690Z triton_mm_16 0.1430 ms 50.8% 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 2025-09-07T11:00:11.5741573Z triton_mm_21 0.1440 ms 50.4% 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 2025-09-07T11:00:11.5742433Z SingleProcess AUTOTUNE benchmarking takes 0.5319 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:00:11.7734882Z Autotune Choices Stats: 2025-09-07T11:00:11.7736525Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_33", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.012927999719977379, "best_triton_pos": 0} 2025-09-07T11:00:11.7806879Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T11:00:11.7807329Z strides: [448000, 80, 1], [1152, 1, 80] 2025-09-07T11:00:11.7807798Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:11.7808848Z triton_bmm_33 0.0129 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.7809932Z triton_bmm_40 0.0130 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.7811251Z triton_bmm_30 0.0132 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:11.7812221Z triton_bmm_36 0.0132 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:11.7813181Z triton_bmm_29 0.0133 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:11.7814145Z triton_bmm_37 0.0136 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.7815104Z triton_bmm_35 0.0137 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:11.7816074Z triton_bmm_38 0.0137 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:11.7817035Z triton_bmm_28 0.0138 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:11.7818003Z triton_bmm_39 0.0138 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T11:00:11.7818877Z SingleProcess AUTOTUNE benchmarking takes 0.2061 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:00:11.9794543Z Autotune Choices Stats: 2025-09-07T11:00:11.9795517Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_49", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013472000136971474, "best_triton_pos": 0} 2025-09-07T11:00:11.9871516Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T11:00:11.9871777Z strides: [80, 1120, 1], [1152, 1, 80] 2025-09-07T11:00:11.9872047Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:11.9872701Z triton_bmm_49 0.0135 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.9873699Z triton_bmm_56 0.0136 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.9874797Z triton_bmm_45 0.0139 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:11.9875878Z triton_bmm_51 0.0141 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:11.9876879Z triton_bmm_52 0.0141 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:11.9877860Z triton_bmm_46 0.0141 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:11.9878843Z triton_bmm_54 0.0141 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:11.9879807Z triton_bmm_50 0.0142 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.9881069Z triton_bmm_53 0.0142 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:11.9881971Z triton_bmm_48 0.0142 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:11.9882744Z SingleProcess AUTOTUNE benchmarking takes 0.2057 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:00:12.3208082Z Autotune Choices Stats: 2025-09-07T11:00:12.3210068Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.029759999364614487, "best_triton_pos": 1, "best_triton_time": 0.0344959981739521, "best_triton_kernel": "triton_mm_75", "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"} 2025-09-07T11:00:12.3277192Z AUTOTUNE mm(4900x1280, 1280x1280) 2025-09-07T11:00:12.3277476Z strides: [1280, 1], [1, 1280] 2025-09-07T11:00:12.3277732Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:12.3277995Z mm 0.0298 ms 100.0% 2025-09-07T11:00:12.3278584Z triton_mm_75 0.0345 ms 86.3% 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 2025-09-07T11:00:12.3280642Z triton_mm_76 0.0354 ms 84.1% 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 2025-09-07T11:00:12.3282236Z triton_mm_74 0.0366 ms 81.3% 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 2025-09-07T11:00:12.3283846Z triton_mm_69 0.0389 ms 76.5% 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 2025-09-07T11:00:12.3285391Z triton_mm_70 0.0468 ms 63.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:12.3287225Z triton_mm_68 0.0505 ms 58.9% 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 2025-09-07T11:00:12.3288808Z triton_mm_72 0.0531 ms 56.0% 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 2025-09-07T11:00:12.3290027Z triton_mm_65 0.0535 ms 55.6% 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 2025-09-07T11:00:12.3291280Z triton_mm_67 0.0562 ms 53.0% 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 2025-09-07T11:00:12.3292076Z SingleProcess AUTOTUNE benchmarking takes 0.3400 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:00:12.9332234Z Autotune Choices Stats: 2025-09-07T11:00:12.9334254Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.06515199691057205, "best_triton_pos": 1, "best_triton_time": 0.07865600287914276, "best_triton_kernel": "triton_mm_780", "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"} 2025-09-07T11:00:12.9402295Z AUTOTUNE addmm(4096x3840, 4096x1280, 1280x3840) 2025-09-07T11:00:12.9402838Z strides: [0, 1], [1280, 1], [1, 1280] 2025-09-07T11:00:12.9403338Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:12.9403845Z bias_addmm 0.0652 ms 100.0% 2025-09-07T11:00:12.9404845Z triton_mm_780 0.0787 ms 82.8% 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 2025-09-07T11:00:12.9406428Z triton_mm_781 0.0866 ms 75.3% 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 2025-09-07T11:00:12.9407987Z triton_mm_779 0.0931 ms 70.0% 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 2025-09-07T11:00:12.9409030Z addmm 0.0993 ms 65.6% 2025-09-07T11:00:12.9409958Z triton_mm_774 0.1008 ms 64.6% 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 2025-09-07T11:00:12.9411244Z triton_mm_775 0.1115 ms 58.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:12.9412141Z triton_mm_773 0.1168 ms 55.8% 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 2025-09-07T11:00:12.9413032Z triton_mm_777 0.1197 ms 54.4% 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 2025-09-07T11:00:12.9413928Z triton_mm_778 0.1212 ms 53.7% 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 2025-09-07T11:00:12.9414719Z SingleProcess AUTOTUNE benchmarking takes 0.5296 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T11:00:13.1643508Z Autotune Choices Stats: 2025-09-07T11:00:13.1645081Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_796", "best_kernel_desc": "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", "best_time": 0.01398400031030178, "best_triton_pos": 0} 2025-09-07T11:00:13.1714204Z AUTOTUNE bmm(64x1024x80, 64x80x64) 2025-09-07T11:00:13.1714478Z strides: [81920, 80, 1], [5120, 1, 80] 2025-09-07T11:00:13.1714750Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:13.1715386Z triton_bmm_796 0.0140 ms 100.0% 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 2025-09-07T11:00:13.1716386Z triton_bmm_793 0.0140 ms 99.8% 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=4 2025-09-07T11:00:13.1717468Z triton_bmm_791 0.0141 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:13.1718572Z triton_bmm_798 0.0141 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:13.1719562Z triton_bmm_795 0.0142 ms 98.4% 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 2025-09-07T11:00:13.1720164Z bmm 0.0143 ms 98.0% 2025-09-07T11:00:13.1720858Z triton_bmm_792 0.0143 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:13.1721751Z triton_bmm_788 0.0144 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:13.1722659Z triton_bmm_797 0.0144 ms 97.1% 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=2, num_warps=8 2025-09-07T11:00:13.1723554Z triton_bmm_787 0.0148 ms 94.2% 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 2025-09-07T11:00:13.1724330Z SingleProcess AUTOTUNE benchmarking takes 0.2300 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:00:13.6508580Z Autotune Choices Stats: 2025-09-07T11:00:13.6510531Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_3441", "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": 0.005535999778658152, "best_triton_pos": 0} 2025-09-07T11:00:13.6581585Z AUTOTUNE mm(2x2, 2x128) 2025-09-07T11:00:13.6581803Z strides: [2, 1], [128, 1] 2025-09-07T11:00:13.6582028Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:13.6582616Z triton_mm_3441 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:00:13.6583591Z triton_mm_3443 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:13.6584453Z triton_mm_3447 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:13.6585291Z triton_mm_3444 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:13.6586138Z triton_mm_3448 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:13.6586994Z triton_mm_3450 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:13.6588077Z triton_mm_3452 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:13.6588960Z triton_mm_3446 0.0057 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:13.6589953Z triton_mm_3451 0.0057 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T11:00:13.6591343Z triton_mm_3445 0.0057 ms 96.6% 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 2025-09-07T11:00:13.6592203Z SingleProcess AUTOTUNE benchmarking takes 0.1603 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T11:00:13.9009986Z Autotune Choices Stats: 2025-09-07T11:00:13.9012110Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_3457", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007040000054985285, "best_triton_pos": 0} 2025-09-07T11:00:13.9082961Z AUTOTUNE addmm(7x768, 7x256, 256x768) 2025-09-07T11:00:13.9083446Z strides: [0, 1], [256, 1], [768, 1] 2025-09-07T11:00:13.9083953Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:13.9085105Z triton_mm_3457 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:13.9086700Z triton_mm_3461 0.0072 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:13.9088246Z triton_mm_3456 0.0073 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:13.9089934Z triton_mm_3455 0.0073 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:13.9090983Z triton_mm_3460 0.0075 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:13.9091886Z triton_mm_3469 0.0076 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:13.9092785Z triton_mm_3454 0.0076 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:13.9093712Z triton_mm_3464 0.0078 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:13.9094631Z triton_mm_3465 0.0078 ms 90.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:13.9095547Z triton_mm_3467 0.0079 ms 88.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:13.9096336Z SingleProcess AUTOTUNE benchmarking takes 0.2495 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:00:14.1193597Z Autotune Choices Stats: 2025-09-07T11:00:14.1194588Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3473", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006688000168651342, "best_triton_pos": 0} 2025-09-07T11:00:14.1265953Z AUTOTUNE mm(7x256, 256x256) 2025-09-07T11:00:14.1266218Z strides: [256, 1], [1, 256] 2025-09-07T11:00:14.1266477Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:14.1267138Z triton_mm_3473 0.0067 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:14.1268311Z triton_mm_3478 0.0068 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:14.1269558Z triton_mm_3474 0.0068 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:14.1270789Z triton_mm_3477 0.0069 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:14.1271843Z triton_mm_3472 0.0069 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:14.1272898Z triton_mm_3486 0.0071 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:14.1273960Z triton_mm_3471 0.0071 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:14.1275028Z triton_mm_3482 0.0072 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:14.1276089Z triton_mm_3484 0.0072 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:14.1277147Z triton_mm_3481 0.0073 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:14.1278063Z SingleProcess AUTOTUNE benchmarking takes 0.2179 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:00:14.2812199Z Autotune Choices Stats: 2025-09-07T11:00:14.2813687Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013535999692976475, "best_triton_pos": 2, "best_triton_time": 0.035999998450279236, "best_triton_kernel": "triton_convolution2d_3529", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T11:00:14.2883129Z AUTOTUNE convolution(1x1280x64x64, 256x1280x1x1) 2025-09-07T11:00:14.2883495Z strides: [5242880, 4096, 64, 1], [1280, 1, 1, 1] 2025-09-07T11:00:14.2883816Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:14.2884119Z convolution 0.0135 ms 100.0% 2025-09-07T11:00:14.2884404Z conv1x1_via_mm 0.0245 ms 55.1% 2025-09-07T11:00:14.2885222Z triton_convolution2d_3529 0.0360 ms 37.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:00:14.2886578Z triton_convolution2d_3531 0.0444 ms 30.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:00:14.2887918Z triton_convolution2d_3528 0.0453 ms 29.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:00:14.2889419Z triton_convolution2d_3530 0.0472 ms 28.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:00:14.2891123Z triton_convolution2d_3525 0.0672 ms 20.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:00:14.2892568Z triton_convolution2d_3526 0.0684 ms 19.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:00:14.2894069Z triton_convolution2d_3527 0.0833 ms 16.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T11:00:14.2895141Z SingleProcess AUTOTUNE benchmarking takes 0.1589 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T11:00:14.4652814Z Autotune Choices Stats: 2025-09-07T11:00:14.4654276Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03177599981427193, "best_triton_pos": 1, "best_triton_time": 0.08908800035715103, "best_triton_kernel": "triton_convolution2d_3536", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:00:14.4724795Z AUTOTUNE convolution(1x256x64x64, 256x256x3x3) 2025-09-07T11:00:14.4725171Z strides: [1048576, 4096, 64, 1], [2304, 9, 3, 1] 2025-09-07T11:00:14.4725500Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:14.4725811Z convolution 0.0318 ms 100.0% 2025-09-07T11:00:14.4726617Z triton_convolution2d_3536 0.0891 ms 35.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:00:14.4727956Z triton_convolution2d_3535 0.0912 ms 34.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:00:14.4729291Z triton_convolution2d_3538 0.0945 ms 33.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:00:14.4730942Z triton_convolution2d_3533 0.1152 ms 27.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:00:14.4732306Z triton_convolution2d_3537 0.1160 ms 27.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:00:14.4733642Z triton_convolution2d_3532 0.1757 ms 18.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:00:14.4734982Z triton_convolution2d_3534 0.2845 ms 11.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:00:14.4736047Z SingleProcess AUTOTUNE benchmarking takes 0.1827 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:00:14.6827297Z Autotune Choices Stats: 2025-09-07T11:00:14.6828387Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_3543", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00595200015231967, "best_triton_pos": 0} 2025-09-07T11:00:14.6900501Z AUTOTUNE mm(4096x2, 2x128) 2025-09-07T11:00:14.6900791Z strides: [2, 1], [128, 1] 2025-09-07T11:00:14.6901064Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:14.6901776Z triton_mm_3543 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:14.6903057Z triton_mm_3544 0.0060 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:14.6904345Z triton_mm_3545 0.0060 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:00:14.6905420Z triton_mm_3546 0.0060 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:14.6906475Z triton_mm_3547 0.0061 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:14.6907543Z triton_mm_3549 0.0062 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:14.6908616Z triton_mm_3548 0.0062 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:14.6909681Z triton_mm_3551 0.0063 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:14.6910913Z triton_mm_3550 0.0063 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:14.6911987Z triton_mm_3553 0.0066 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:14.6912915Z SingleProcess AUTOTUNE benchmarking takes 0.2162 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T11:00:14.9244761Z Autotune Choices Stats: 2025-09-07T11:00:14.9245879Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_3562", "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": 0.008671999908983707, "best_triton_pos": 0} 2025-09-07T11:00:14.9316708Z AUTOTUNE mm(4096x256, 256x256) 2025-09-07T11:00:14.9316996Z strides: [256, 1], [256, 1] 2025-09-07T11:00:14.9317278Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:14.9317993Z triton_mm_3562 0.0087 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 2025-09-07T11:00:14.9319128Z triton_mm_3566 0.0088 ms 98.5% 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 2025-09-07T11:00:14.9320699Z triton_mm_3567 0.0089 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:14.9321828Z triton_mm_3565 0.0089 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=4, num_warps=8 2025-09-07T11:00:14.9322718Z mm 0.0090 ms 96.4% 2025-09-07T11:00:14.9323364Z triton_mm_3569 0.0090 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 2025-09-07T11:00:14.9324465Z triton_mm_3573 0.0092 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:14.9325570Z triton_mm_3564 0.0094 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 2025-09-07T11:00:14.9326988Z triton_mm_3572 0.0096 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 2025-09-07T11:00:14.9328104Z triton_mm_3568 0.0097 ms 89.7% 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 2025-09-07T11:00:14.9329070Z SingleProcess AUTOTUNE benchmarking takes 0.2410 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:00:15.1728112Z Autotune Choices Stats: 2025-09-07T11:00:15.1729222Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_3582", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006943999789655209, "best_triton_pos": 0} 2025-09-07T11:00:15.1804586Z AUTOTUNE addmm(7x128, 7x256, 256x128) 2025-09-07T11:00:15.1804919Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:00:15.1805274Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:15.1806081Z triton_mm_3582 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:15.1807216Z triton_mm_3577 0.0071 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:15.1808326Z triton_mm_3578 0.0071 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:15.1809435Z triton_mm_3586 0.0071 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:15.1810667Z triton_mm_3581 0.0072 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.1811732Z triton_mm_3575 0.0073 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:15.1812791Z triton_mm_3576 0.0073 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:15.1813843Z triton_mm_3590 0.0074 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:15.1814531Z bias_addmm 0.0076 ms 91.9% 2025-09-07T11:00:15.1815172Z triton_mm_3588 0.0076 ms 91.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:15.1816103Z SingleProcess AUTOTUNE benchmarking takes 0.2483 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:00:15.3913425Z Autotune Choices Stats: 2025-09-07T11:00:15.3914782Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3617", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.006111999973654747, "best_triton_pos": 0} 2025-09-07T11:00:15.3988616Z AUTOTUNE mm(7x128, 128x256) 2025-09-07T11:00:15.3988901Z strides: [128, 1], [1, 128] 2025-09-07T11:00:15.3989185Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:15.3989917Z triton_mm_3617 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.3991608Z triton_mm_3613 0.0062 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:15.3992905Z triton_mm_3612 0.0063 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:15.3994012Z triton_mm_3621 0.0064 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.3995115Z triton_mm_3624 0.0065 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:15.3996209Z triton_mm_3626 0.0066 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:15.3997318Z triton_mm_3620 0.0067 ms 91.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:15.3998411Z triton_mm_3623 0.0068 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.3999507Z triton_mm_3618 0.0068 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:15.4000748Z triton_mm_3619 0.0069 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.4001664Z SingleProcess AUTOTUNE benchmarking takes 0.2179 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:00:15.6226193Z Autotune Choices Stats: 2025-09-07T11:00:15.6227281Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3648", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.00940799992531538, "best_triton_pos": 0} 2025-09-07T11:00:15.6303581Z AUTOTUNE mm(7x2048, 2048x256) 2025-09-07T11:00:15.6303858Z strides: [2048, 1], [1, 2048] 2025-09-07T11:00:15.6304147Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:15.6304863Z triton_mm_3648 0.0094 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:15.6305543Z mm 0.0095 ms 99.3% 2025-09-07T11:00:15.6306165Z triton_mm_3652 0.0101 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:15.6307226Z triton_mm_3656 0.0123 ms 76.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:15.6308273Z triton_mm_3660 0.0143 ms 65.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:15.6309584Z triton_mm_3647 0.0153 ms 61.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:15.6311280Z triton_mm_3646 0.0165 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:15.6312408Z triton_mm_3651 0.0168 ms 56.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.6313781Z triton_mm_3645 0.0172 ms 54.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:15.6314894Z triton_mm_3655 0.0190 ms 49.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:15.6315849Z SingleProcess AUTOTUNE benchmarking takes 0.2309 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:00:15.8948668Z Autotune Choices Stats: 2025-09-07T11:00:15.8949804Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_3708", "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": 0.0077760000713169575, "best_triton_pos": 0} 2025-09-07T11:00:15.9026865Z AUTOTUNE mm(4096x128, 128x256) 2025-09-07T11:00:15.9027274Z strides: [128, 1], [1, 128] 2025-09-07T11:00:15.9027659Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:15.9028673Z triton_mm_3708 0.0078 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 2025-09-07T11:00:15.9030619Z triton_mm_3707 0.0079 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:15.9031355Z mm 0.0080 ms 97.2% 2025-09-07T11:00:15.9032037Z triton_mm_3711 0.0083 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 2025-09-07T11:00:15.9033191Z triton_mm_3713 0.0084 ms 92.4% 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 2025-09-07T11:00:15.9034353Z triton_mm_3696 0.0092 ms 84.7% 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 2025-09-07T11:00:15.9035511Z triton_mm_3710 0.0098 ms 79.7% 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 2025-09-07T11:00:15.9036665Z triton_mm_3695 0.0105 ms 74.1% 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 2025-09-07T11:00:15.9037817Z triton_mm_3706 0.0140 ms 55.7% 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 2025-09-07T11:00:15.9038976Z triton_mm_3705 0.0159 ms 49.0% 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 2025-09-07T11:00:15.9039986Z SingleProcess AUTOTUNE benchmarking takes 0.2671 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:00:16.1585397Z Autotune Choices Stats: 2025-09-07T11:00:16.1587004Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_3722", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.007040000054985285, "best_triton_pos": 0} 2025-09-07T11:00:16.1666266Z AUTOTUNE addmm(7x256, 7x256, 256x256) 2025-09-07T11:00:16.1666743Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:00:16.1667237Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:16.1668362Z triton_mm_3722 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:16.1670840Z triton_mm_3721 0.0072 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:16.1672083Z triton_mm_3717 0.0073 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:16.1673072Z triton_mm_3718 0.0073 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:16.1674060Z triton_mm_3730 0.0074 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:16.1675057Z triton_mm_3726 0.0076 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:16.1676037Z triton_mm_3728 0.0076 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:16.1677010Z triton_mm_3725 0.0076 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:16.1677989Z triton_mm_3724 0.0078 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:16.1678969Z triton_mm_3727 0.0082 ms 85.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:16.1679821Z SingleProcess AUTOTUNE benchmarking takes 0.2633 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:00:16.4413665Z Autotune Choices Stats: 2025-09-07T11:00:16.4415305Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_3807", "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": 0.008352000266313553, "best_triton_pos": 0} 2025-09-07T11:00:16.4487374Z AUTOTUNE addmm(4096x128, 4096x256, 256x128) 2025-09-07T11:00:16.4487876Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:00:16.4488384Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:16.4489585Z triton_mm_3807 0.0084 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 2025-09-07T11:00:16.4491297Z triton_mm_3802 0.0085 ms 97.8% 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 2025-09-07T11:00:16.4492338Z triton_mm_3806 0.0085 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=8 2025-09-07T11:00:16.4492992Z bias_addmm 0.0088 ms 95.3% 2025-09-07T11:00:16.4493609Z triton_mm_3810 0.0090 ms 92.6% 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 2025-09-07T11:00:16.4494828Z triton_mm_3811 0.0090 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:16.4495846Z triton_mm_3800 0.0092 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:16.4496843Z triton_mm_3809 0.0092 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=4, num_warps=8 2025-09-07T11:00:16.4498140Z triton_mm_3801 0.0092 ms 90.3% 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 2025-09-07T11:00:16.4499143Z triton_mm_3813 0.0093 ms 90.0% 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 2025-09-07T11:00:16.4500065Z SingleProcess AUTOTUNE benchmarking takes 0.2722 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T11:00:16.6462671Z Autotune Choices Stats: 2025-09-07T11:00:16.6464401Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_4076", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006432000081986189, "best_triton_pos": 0} 2025-09-07T11:00:16.6537167Z AUTOTUNE addmm(1x32, 1x256, 256x32) 2025-09-07T11:00:16.6537634Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:00:16.6538131Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:16.6539290Z triton_mm_4076 0.0064 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:16.6541215Z triton_mm_4069 0.0066 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:16.6542230Z triton_mm_4075 0.0067 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=2 2025-09-07T11:00:16.6543284Z triton_mm_4068 0.0069 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:16.6544270Z triton_mm_4072 0.0069 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=2 2025-09-07T11:00:16.6545259Z triton_mm_4067 0.0069 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:16.6546247Z triton_mm_4074 0.0072 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=2 2025-09-07T11:00:16.6546996Z bias_addmm 0.0076 ms 85.2% 2025-09-07T11:00:16.6547594Z triton_mm_4073 0.0077 ms 83.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=2 2025-09-07T11:00:16.6548217Z addmm 0.0095 ms 67.7% 2025-09-07T11:00:16.6548671Z SingleProcess AUTOTUNE benchmarking takes 0.1798 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T11:00:16.8281618Z Autotune Choices Stats: 2025-09-07T11:00:16.8282718Z {"num_choices": 14, "num_triton_choices": 13, "best_kernel": "triton_mm_4212", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.008031999692320824, "best_triton_pos": 0} 2025-09-07T11:00:16.8355276Z AUTOTUNE mm(4x32, 32x65536) 2025-09-07T11:00:16.8355534Z strides: [32, 1], [1, 32] 2025-09-07T11:00:16.8355800Z dtypes: torch.float16, torch.float16 2025-09-07T11:00:16.8356516Z triton_mm_4212 0.0080 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:00:16.8357581Z triton_mm_4217 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:16.8359022Z triton_mm_4221 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:16.8360099Z triton_mm_4222 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:16.8361298Z triton_mm_4223 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T11:00:16.8362281Z triton_mm_4224 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:16.8363247Z triton_mm_4218 0.0082 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:16.8364212Z triton_mm_4219 0.0083 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:16.8365186Z triton_mm_4220 0.0083 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:16.8366150Z triton_mm_4214 0.0083 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:16.8366992Z SingleProcess AUTOTUNE benchmarking takes 0.1746 seconds and 0.0002 seconds precompiling for 14 choices 2025-09-07T11:00:17.0050794Z Autotune Choices Stats: 2025-09-07T11:00:17.0052408Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_4269", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1", "best_time": 0.006207999773323536, "best_triton_pos": 0} 2025-09-07T11:00:17.0125906Z AUTOTUNE addmm(1x4, 1x256, 256x4) 2025-09-07T11:00:17.0126381Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:00:17.0126894Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:00:17.0128054Z triton_mm_4269 0.0062 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T11:00:17.0129642Z triton_mm_4265 0.0066 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T11:00:17.0131333Z triton_mm_4261 0.0067 ms 92.8% 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 2025-09-07T11:00:17.0132318Z triton_mm_4262 0.0068 ms 91.9% 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 2025-09-07T11:00:17.0133288Z triton_mm_4268 0.0068 ms 91.9% 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 2025-09-07T11:00:17.0134451Z triton_mm_4260 0.0068 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T11:00:17.0135446Z triton_mm_4267 0.0069 ms 89.8% 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 2025-09-07T11:00:17.0136064Z bias_addmm 0.0073 ms 85.1% 2025-09-07T11:00:17.0136745Z triton_mm_4266 0.0074 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T11:00:17.0137356Z addmm 0.0090 ms 69.3% 2025-09-07T11:00:17.0137981Z SingleProcess AUTOTUNE benchmarking takes 0.1765 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T11:00:29.9991219Z pass 2025-09-07T11:00:35.5825073Z /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. 2025-09-07T11:00:35.5826939Z import pynvml # type: ignore[import] 2025-09-07T11:00:38.2433998Z 2025-09-07T11:00:39.4716143Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:00:39.4716560Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:00:39.4718768Z cuda eval soft_actor_critic 2025-09-07T11:00:44.8352379Z Autotune Choices Stats: 2025-09-07T11:00:44.8353638Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_7", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006016000173985958, "best_triton_pos": 0} 2025-09-07T11:00:44.8393683Z AUTOTUNE mm(256x3, 3x1024) 2025-09-07T11:00:44.8393957Z strides: [3, 1], [1, 3] 2025-09-07T11:00:44.8394179Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:00:44.8394728Z triton_mm_7 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:44.8395541Z triton_mm_2 0.0062 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:44.8396341Z triton_mm_10 0.0062 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:44.8397123Z triton_mm_0 0.0062 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:00:44.8397902Z triton_mm_1 0.0062 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:44.8434200Z triton_mm_4 0.0062 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:44.8436309Z triton_mm_5 0.0062 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:00:44.8438393Z triton_mm_3 0.0063 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:44.8440655Z triton_mm_6 0.0064 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:00:44.8443162Z triton_mm_9 0.0066 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:44.8445086Z SingleProcess AUTOTUNE benchmarking takes 0.1859 seconds and 0.0095 seconds precompiling for 17 choices 2025-09-07T11:00:46.8267933Z Autotune Choices Stats: 2025-09-07T11:00:46.8269148Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_20", "best_kernel_desc": "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", "best_time": 0.009119999594986439, "best_triton_pos": 0} 2025-09-07T11:00:46.8344552Z AUTOTUNE mm(256x1024, 1024x1024) 2025-09-07T11:00:46.8344834Z strides: [1024, 1], [1, 1024] 2025-09-07T11:00:46.8345438Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:00:46.8346129Z triton_mm_20 0.0091 ms 100.0% 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 2025-09-07T11:00:46.8347164Z triton_mm_24 0.0094 ms 96.9% 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 2025-09-07T11:00:46.8347782Z mm 0.0098 ms 93.1% 2025-09-07T11:00:46.8348402Z triton_mm_28 0.0105 ms 86.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:46.8349490Z triton_mm_19 0.0121 ms 75.6% 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 2025-09-07T11:00:46.8350602Z triton_mm_23 0.0124 ms 73.6% 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 2025-09-07T11:00:46.8351575Z triton_mm_34 0.0125 ms 73.1% 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 2025-09-07T11:00:46.8352537Z triton_mm_18 0.0127 ms 72.0% 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 2025-09-07T11:00:46.8353486Z triton_mm_27 0.0129 ms 70.7% 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 2025-09-07T11:00:46.8354459Z triton_mm_17 0.0132 ms 68.8% 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 2025-09-07T11:00:46.8355317Z SingleProcess AUTOTUNE benchmarking takes 0.2375 seconds and 1.3998 seconds precompiling for 20 choices 2025-09-07T11:00:47.5305324Z Autotune Choices Stats: 2025-09-07T11:00:47.5306406Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_39", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.008128000423312187, "best_triton_pos": 0} 2025-09-07T11:00:47.5387332Z AUTOTUNE addmm(256x2, 256x1024, 1024x2) 2025-09-07T11:00:47.5387747Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T11:00:47.5388063Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:00:47.5388770Z triton_mm_39 0.0081 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:47.5389799Z triton_mm_45 0.0085 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:47.5391440Z triton_mm_50 0.0097 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:00:47.5392393Z triton_mm_37 0.0109 ms 74.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:00:47.5393341Z triton_mm_42 0.0109 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:47.5394432Z triton_mm_38 0.0113 ms 72.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:00:47.5395595Z triton_mm_36 0.0117 ms 69.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:00:47.5396561Z triton_mm_49 0.0119 ms 68.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:00:47.5397511Z triton_mm_44 0.0124 ms 65.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:00:47.5398462Z triton_mm_47 0.0132 ms 61.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:00:47.5399311Z SingleProcess AUTOTUNE benchmarking takes 0.2382 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:00:48.1353668Z pass 2025-09-07T11:00:50.8095762Z /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. 2025-09-07T11:00:50.8097033Z import pynvml # type: ignore[import] 2025-09-07T11:00:53.3449284Z 2025-09-07T11:00:55.0506827Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:00:55.0507206Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:00:55.0571237Z cuda eval speech_transformer 2025-09-07T11:01:02.4689543Z W0907 11:01:02.468000 211630 site-packages/torch/_inductor/utils.py:2298] [7/0_1] DeviceCopy in input program 2025-09-07T11:01:06.2444529Z Autotune Choices Stats: 2025-09-07T11:01:06.2445721Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_111", "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": 0.014175999909639359, "best_triton_pos": 0} 2025-09-07T11:01:06.2523023Z AUTOTUNE mm(2040x512, 512x2048) 2025-09-07T11:01:06.2523318Z strides: [512, 1], [1, 512] 2025-09-07T11:01:06.2523580Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:06.2524310Z triton_mm_111 0.0142 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 2025-09-07T11:01:06.2525111Z mm 0.0147 ms 96.3% 2025-09-07T11:01:06.2525736Z triton_mm_110 0.0161 ms 87.9% 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 2025-09-07T11:01:06.2526745Z triton_mm_112 0.0165 ms 86.0% 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 2025-09-07T11:01:06.2527749Z triton_mm_105 0.0175 ms 81.0% 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 2025-09-07T11:01:06.2529088Z triton_mm_103 0.0180 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 2025-09-07T11:01:06.2530067Z triton_mm_107 0.0184 ms 77.0% 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 2025-09-07T11:01:06.2531619Z triton_mm_108 0.0190 ms 74.7% 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 2025-09-07T11:01:06.2532595Z triton_mm_104 0.0190 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=4, num_warps=8 2025-09-07T11:01:06.2534006Z triton_mm_100 0.0199 ms 71.2% 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 2025-09-07T11:01:06.2534903Z SingleProcess AUTOTUNE benchmarking takes 0.2487 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:01:06.8390692Z Autotune Choices Stats: 2025-09-07T11:01:06.8391784Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_87", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009375999681651592, "best_triton_pos": 0} 2025-09-07T11:01:06.8468639Z AUTOTUNE mm(2040x512, 512x512) 2025-09-07T11:01:06.8468954Z strides: [512, 1], [1, 512] 2025-09-07T11:01:06.8469255Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:06.8469939Z triton_mm_87 0.0094 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:06.8470771Z mm 0.0094 ms 99.7% 2025-09-07T11:01:06.8471337Z triton_mm_82 0.0101 ms 92.4% 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 2025-09-07T11:01:06.8472305Z triton_mm_86 0.0104 ms 90.4% 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 2025-09-07T11:01:06.8473261Z triton_mm_93 0.0105 ms 89.1% 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 2025-09-07T11:01:06.8474353Z triton_mm_85 0.0111 ms 84.7% 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 2025-09-07T11:01:06.8475436Z triton_mm_89 0.0111 ms 84.7% 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 2025-09-07T11:01:06.8476415Z triton_mm_92 0.0111 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 2025-09-07T11:01:06.8477376Z triton_mm_83 0.0115 ms 81.4% 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 2025-09-07T11:01:06.8478322Z triton_mm_84 0.0125 ms 75.1% 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 2025-09-07T11:01:06.8479162Z SingleProcess AUTOTUNE benchmarking takes 0.2329 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:08.1349154Z Autotune Choices Stats: 2025-09-07T11:01:08.1351904Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.008895999751985073, "best_triton_pos": 1, "best_triton_time": 0.008927999995648861, "best_triton_kernel": "triton_mm_12", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T11:01:08.1424195Z AUTOTUNE mm(2040x320, 320x512) 2025-09-07T11:01:08.1424812Z strides: [320, 1], [1, 320] 2025-09-07T11:01:08.1425241Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:08.1425691Z mm 0.0089 ms 100.0% 2025-09-07T11:01:08.1426665Z triton_mm_12 0.0089 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:08.1428539Z triton_mm_11 0.0090 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 2025-09-07T11:01:08.1430682Z triton_mm_7 0.0091 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:08.1432291Z triton_mm_10 0.0094 ms 94.2% 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 2025-09-07T11:01:08.1433836Z triton_mm_14 0.0095 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 2025-09-07T11:01:08.1435571Z triton_mm_17 0.0097 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=3, num_warps=4 2025-09-07T11:01:08.1436537Z triton_mm_18 0.0097 ms 91.7% 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 2025-09-07T11:01:08.1437499Z triton_mm_9 0.0101 ms 88.0% 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 2025-09-07T11:01:08.1438466Z triton_mm_13 0.0102 ms 86.9% 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 2025-09-07T11:01:08.1439300Z SingleProcess AUTOTUNE benchmarking takes 0.2302 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:08.3714742Z Autotune Choices Stats: 2025-09-07T11:01:08.3716114Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_30", "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": 0.012223999947309494, "best_triton_pos": 0} 2025-09-07T11:01:08.3789765Z AUTOTUNE mm(2040x512, 512x1536) 2025-09-07T11:01:08.3790535Z strides: [512, 1], [1536, 1] 2025-09-07T11:01:08.3791016Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:08.3792117Z triton_mm_30 0.0122 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 2025-09-07T11:01:08.3793125Z mm 0.0124 ms 98.2% 2025-09-07T11:01:08.3794053Z triton_mm_36 0.0132 ms 92.3% 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 2025-09-07T11:01:08.3795765Z triton_mm_29 0.0135 ms 90.3% 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 2025-09-07T11:01:08.3796724Z triton_mm_28 0.0141 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 2025-09-07T11:01:08.3797679Z triton_mm_33 0.0144 ms 85.1% 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 2025-09-07T11:01:08.3798841Z triton_mm_32 0.0147 ms 83.2% 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 2025-09-07T11:01:08.3799804Z triton_mm_35 0.0147 ms 83.2% 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 2025-09-07T11:01:08.3801015Z triton_mm_37 0.0158 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=5, num_warps=8 2025-09-07T11:01:08.3802070Z triton_mm_26 0.0175 ms 70.0% 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 2025-09-07T11:01:08.3803044Z SingleProcess AUTOTUNE benchmarking takes 0.2358 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:08.6070798Z Autotune Choices Stats: 2025-09-07T11:01:08.6071767Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_47", "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": 0.011071999557316303, "best_triton_pos": 0} 2025-09-07T11:01:08.6152623Z AUTOTUNE bmm(80x204x64, 80x64x204) 2025-09-07T11:01:08.6152935Z strides: [13056, 64, 1], [13056, 1, 64] 2025-09-07T11:01:08.6153300Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:08.6153992Z triton_bmm_47 0.0111 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 2025-09-07T11:01:08.6155120Z triton_bmm_54 0.0114 ms 97.2% 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 2025-09-07T11:01:08.6156232Z triton_bmm_51 0.0116 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 2025-09-07T11:01:08.6157282Z triton_bmm_45 0.0124 ms 89.6% 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 2025-09-07T11:01:08.6158320Z triton_bmm_46 0.0127 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:08.6159367Z triton_bmm_49 0.0127 ms 86.9% 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 2025-09-07T11:01:08.6160629Z triton_bmm_52 0.0128 ms 86.7% 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 2025-09-07T11:01:08.6161696Z triton_bmm_50 0.0128 ms 86.5% 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=4, num_warps=4 2025-09-07T11:01:08.6162743Z triton_bmm_48 0.0129 ms 85.9% 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 2025-09-07T11:01:08.6163771Z triton_bmm_44 0.0131 ms 84.4% 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 2025-09-07T11:01:08.6164680Z SingleProcess AUTOTUNE benchmarking takes 0.2354 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:08.8298941Z Autotune Choices Stats: 2025-09-07T11:01:08.8309361Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_66", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.012128000147640705, "best_triton_pos": 0} 2025-09-07T11:01:08.8374026Z AUTOTUNE bmm(80x204x204, 80x204x64) 2025-09-07T11:01:08.8374344Z strides: [41664, 204, 1], [13056, 64, 1] 2025-09-07T11:01:08.8374644Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:08.8375350Z triton_bmm_66 0.0121 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:08.8376367Z triton_bmm_68 0.0122 ms 99.2% 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=4 2025-09-07T11:01:08.8377721Z triton_bmm_67 0.0126 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:01:08.8378726Z triton_bmm_64 0.0127 ms 95.5% 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 2025-09-07T11:01:08.8379735Z triton_bmm_70 0.0128 ms 95.0% 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 2025-09-07T11:01:08.8380958Z triton_bmm_71 0.0128 ms 94.8% 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=4, num_warps=8 2025-09-07T11:01:08.8381945Z triton_bmm_63 0.0137 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:08.8383016Z triton_bmm_59 0.0139 ms 87.1% 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 2025-09-07T11:01:08.8383997Z triton_bmm_72 0.0146 ms 83.3% 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=2, num_warps=8 2025-09-07T11:01:08.8384994Z triton_bmm_73 0.0147 ms 82.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:08.8385775Z SingleProcess AUTOTUNE benchmarking takes 0.2221 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:01:09.0810372Z Autotune Choices Stats: 2025-09-07T11:01:09.0811643Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.014688000082969666, "best_triton_pos": 1, "best_triton_time": 0.016863999888300896, "best_triton_kernel": "triton_mm_125", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T11:01:09.0885308Z AUTOTUNE mm(2040x2048, 2048x512) 2025-09-07T11:01:09.0885632Z strides: [2048, 1], [1, 2048] 2025-09-07T11:01:09.0885954Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:09.0886288Z mm 0.0147 ms 100.0% 2025-09-07T11:01:09.0886913Z triton_mm_125 0.0169 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:09.0887909Z triton_mm_131 0.0191 ms 76.9% 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 2025-09-07T11:01:09.0888890Z triton_mm_121 0.0202 ms 72.9% 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 2025-09-07T11:01:09.0889855Z triton_mm_124 0.0214 ms 68.5% 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 2025-09-07T11:01:09.0891183Z triton_mm_120 0.0218 ms 67.4% 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 2025-09-07T11:01:09.0892171Z triton_mm_130 0.0233 ms 63.0% 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 2025-09-07T11:01:09.0893147Z triton_mm_123 0.0247 ms 59.4% 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 2025-09-07T11:01:09.0894208Z triton_mm_127 0.0253 ms 58.1% 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 2025-09-07T11:01:09.0895400Z triton_mm_117 0.0277 ms 53.1% 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 2025-09-07T11:01:09.0896200Z SingleProcess AUTOTUNE benchmarking takes 0.2507 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:09.1493226Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1493829Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1494332Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1494795Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1495320Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1495801Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1496084Z cudagraph partition due to non gpu ops 2025-09-07T11:01:09.1496350Z cudagraph partition due to DeviceCopy ops 2025-09-07T11:01:09.1753152Z cudagraph partition into 2 partitions 2025-09-07T11:01:24.0416708Z W0907 11:01:24.041000 211630 site-packages/torch/_inductor/utils.py:2298] [13/0_1] DeviceCopy in input program 2025-09-07T11:01:29.0646515Z Autotune Choices Stats: 2025-09-07T11:01:29.0647539Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_911", "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": 0.00886400043964386, "best_triton_pos": 0} 2025-09-07T11:01:29.0726741Z AUTOTUNE mm(220x512, 512x2048) 2025-09-07T11:01:29.0726998Z strides: [512, 1], [1, 512] 2025-09-07T11:01:29.0727246Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:29.0727863Z triton_mm_911 0.0089 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 2025-09-07T11:01:29.0728786Z triton_mm_915 0.0089 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:29.0729371Z mm 0.0096 ms 92.6% 2025-09-07T11:01:29.0729894Z triton_mm_910 0.0098 ms 90.2% 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 2025-09-07T11:01:29.0731174Z triton_mm_914 0.0101 ms 87.4% 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 2025-09-07T11:01:29.0732115Z triton_mm_921 0.0103 ms 86.0% 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 2025-09-07T11:01:29.0733043Z triton_mm_906 0.0104 ms 85.5% 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 2025-09-07T11:01:29.0733956Z triton_mm_907 0.0104 ms 85.5% 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 2025-09-07T11:01:29.0735219Z triton_mm_913 0.0106 ms 83.7% 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 2025-09-07T11:01:29.0736131Z triton_mm_917 0.0108 ms 82.2% 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 2025-09-07T11:01:29.0736924Z SingleProcess AUTOTUNE benchmarking takes 0.2444 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T11:01:29.6618763Z Autotune Choices Stats: 2025-09-07T11:01:29.6619829Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_742", "best_kernel_desc": "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", "best_time": 0.007584000006318092, "best_triton_pos": 0} 2025-09-07T11:01:29.6696494Z AUTOTUNE mm(220x512, 512x512) 2025-09-07T11:01:29.6696780Z strides: [512, 1], [1, 512] 2025-09-07T11:01:29.6697057Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:29.6697744Z triton_mm_742 0.0076 ms 100.0% 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 2025-09-07T11:01:29.6698404Z mm 0.0080 ms 95.2% 2025-09-07T11:01:29.6698996Z triton_mm_746 0.0080 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 2025-09-07T11:01:29.6699974Z triton_mm_750 0.0086 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:29.6701221Z triton_mm_741 0.0091 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:29.6702133Z triton_mm_745 0.0091 ms 83.2% 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 2025-09-07T11:01:29.6703160Z triton_mm_739 0.0092 ms 82.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:29.6704056Z triton_mm_740 0.0092 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:29.6704950Z triton_mm_749 0.0095 ms 80.1% 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 2025-09-07T11:01:29.6705878Z triton_mm_748 0.0100 ms 75.7% 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 2025-09-07T11:01:29.6706666Z SingleProcess AUTOTUNE benchmarking takes 0.2446 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:30.5599277Z Autotune Choices Stats: 2025-09-07T11:01:30.5600576Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_705", "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": 0.008576000109314919, "best_triton_pos": 0} 2025-09-07T11:01:30.5678120Z AUTOTUNE mm(220x512, 512x1536) 2025-09-07T11:01:30.5678456Z strides: [512, 1], [1536, 1] 2025-09-07T11:01:30.5678755Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:30.5679414Z triton_mm_705 0.0086 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 2025-09-07T11:01:30.5680049Z mm 0.0088 ms 97.5% 2025-09-07T11:01:30.5680737Z triton_mm_709 0.0092 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:30.5681968Z triton_mm_708 0.0095 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:30.5682888Z triton_mm_704 0.0097 ms 88.7% 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 2025-09-07T11:01:30.5683779Z triton_mm_715 0.0102 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 2025-09-07T11:01:30.5684959Z triton_mm_707 0.0103 ms 83.0% 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 2025-09-07T11:01:30.5685864Z triton_mm_701 0.0105 ms 81.7% 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 2025-09-07T11:01:30.5686749Z triton_mm_711 0.0106 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 2025-09-07T11:01:30.5687626Z triton_mm_700 0.0107 ms 80.2% 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 2025-09-07T11:01:30.5688394Z SingleProcess AUTOTUNE benchmarking takes 0.2364 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:30.6945350Z Autotune Choices Stats: 2025-09-07T11:01:30.6946957Z {"num_choices": 11, "num_triton_choices": 10, "best_kernel": "triton_bmm_718", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006496000103652477, "best_triton_pos": 0} 2025-09-07T11:01:30.7021041Z AUTOTUNE bmm(80x22x64, 80x64x22) 2025-09-07T11:01:30.7021521Z strides: [1408, 64, 1], [1408, 1, 64] 2025-09-07T11:01:30.7021999Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:30.7023201Z triton_bmm_718 0.0065 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:30.7024811Z triton_bmm_725 0.0065 ms 100.0% 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=4, num_warps=4 2025-09-07T11:01:30.7026404Z triton_bmm_722 0.0065 ms 99.5% 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=3, num_warps=4 2025-09-07T11:01:30.7027978Z triton_bmm_723 0.0065 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:30.7029578Z triton_bmm_717 0.0066 ms 99.0% 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 2025-09-07T11:01:30.7031492Z triton_bmm_719 0.0066 ms 98.5% 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=5, num_warps=4 2025-09-07T11:01:30.7032709Z triton_bmm_724 0.0067 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:30.7033674Z triton_bmm_721 0.0069 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:30.7034281Z bmm 0.0075 ms 87.1% 2025-09-07T11:01:30.7035019Z triton_bmm_716 0.0075 ms 87.1% 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 2025-09-07T11:01:30.7035861Z SingleProcess AUTOTUNE benchmarking takes 0.1337 seconds and 0.0002 seconds precompiling for 11 choices 2025-09-07T11:01:30.8511499Z Autotune Choices Stats: 2025-09-07T11:01:30.8512821Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_bmm_727", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.006304000038653612, "best_triton_pos": 0} 2025-09-07T11:01:30.8587206Z AUTOTUNE bmm(80x22x22, 80x22x64) 2025-09-07T11:01:30.8587706Z strides: [484, 22, 1], [1408, 64, 1] 2025-09-07T11:01:30.8588176Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:30.8589833Z triton_bmm_727 0.0063 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:30.8592063Z triton_bmm_737 0.0063 ms 100.0% 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=2, num_warps=8 2025-09-07T11:01:30.8593123Z triton_bmm_729 0.0063 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:30.8594170Z triton_bmm_728 0.0064 ms 99.0% 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 2025-09-07T11:01:30.8595219Z triton_bmm_735 0.0064 ms 98.5% 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=4, num_warps=8 2025-09-07T11:01:30.8596261Z triton_bmm_732 0.0065 ms 97.5% 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=3, num_warps=8 2025-09-07T11:01:30.8597326Z triton_bmm_731 0.0068 ms 93.4% 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=2, num_warps=4 2025-09-07T11:01:30.8598379Z triton_bmm_733 0.0068 ms 93.4% 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=4 2025-09-07T11:01:30.8599424Z triton_bmm_726 0.0068 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:01:30.8600599Z triton_bmm_734 0.0068 ms 92.1% 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=3, num_warps=4 2025-09-07T11:01:30.8601526Z SingleProcess AUTOTUNE benchmarking takes 0.1561 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T11:01:31.0767310Z Autotune Choices Stats: 2025-09-07T11:01:31.0768317Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_856", "best_kernel_desc": "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=5, num_warps=4", "best_time": 0.0077760000713169575, "best_triton_pos": 0} 2025-09-07T11:01:31.0843919Z AUTOTUNE bmm(80x22x64, 80x64x204) 2025-09-07T11:01:31.0844258Z strides: [1408, 64, 1], [13056, 1, 64] 2025-09-07T11:01:31.0844570Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:31.0845265Z triton_bmm_856 0.0078 ms 100.0% 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=5, num_warps=4 2025-09-07T11:01:31.0846319Z triton_bmm_853 0.0079 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:31.0847608Z triton_bmm_868 0.0079 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:31.0848604Z triton_bmm_860 0.0080 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:31.0849595Z triton_bmm_859 0.0081 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:31.0852312Z triton_bmm_855 0.0081 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:31.0853217Z triton_bmm_865 0.0082 ms 95.3% 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=3, num_warps=4 2025-09-07T11:01:31.0854121Z triton_bmm_866 0.0082 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:01:31.0855008Z triton_bmm_858 0.0083 ms 94.2% 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=2, num_warps=4 2025-09-07T11:01:31.0855921Z triton_bmm_864 0.0083 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:31.0856711Z SingleProcess AUTOTUNE benchmarking takes 0.2133 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:01:31.2684841Z Autotune Choices Stats: 2025-09-07T11:01:31.2686453Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_bmm_871", "best_kernel_desc": "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", "best_time": 0.00848000030964613, "best_triton_pos": 0} 2025-09-07T11:01:31.2761039Z AUTOTUNE bmm(80x22x204, 80x204x64) 2025-09-07T11:01:31.2761344Z strides: [4544, 204, 1], [13056, 64, 1] 2025-09-07T11:01:31.2761897Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:31.2763075Z triton_bmm_871 0.0085 ms 100.0% 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 2025-09-07T11:01:31.2764694Z triton_bmm_872 0.0086 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:31.2766299Z triton_bmm_877 0.0086 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:31.2767870Z triton_bmm_879 0.0087 ms 97.8% 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=4, num_warps=8 2025-09-07T11:01:31.2769427Z triton_bmm_881 0.0087 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:31.2771502Z triton_bmm_883 0.0087 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:31.2772763Z triton_bmm_876 0.0087 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:31.2773674Z triton_bmm_880 0.0088 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:31.2774730Z triton_bmm_873 0.0089 ms 95.0% 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=5, num_warps=4 2025-09-07T11:01:31.2775645Z triton_bmm_870 0.0092 ms 92.3% 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 2025-09-07T11:01:31.2776439Z SingleProcess AUTOTUNE benchmarking takes 0.1913 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T11:01:31.5162246Z Autotune Choices Stats: 2025-09-07T11:01:31.5164669Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010688000358641148, "best_triton_pos": 1, "best_triton_time": 0.010944000445306301, "best_triton_kernel": "triton_mm_926", "best_triton_kernel_desc": "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"} 2025-09-07T11:01:31.5238682Z AUTOTUNE mm(220x2048, 2048x512) 2025-09-07T11:01:31.5238938Z strides: [2048, 1], [1, 2048] 2025-09-07T11:01:31.5239195Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:31.5239456Z mm 0.0107 ms 100.0% 2025-09-07T11:01:31.5240051Z triton_mm_926 0.0109 ms 97.7% 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 2025-09-07T11:01:31.5241322Z triton_mm_930 0.0120 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:31.5242552Z triton_mm_934 0.0135 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:31.5243556Z triton_mm_940 0.0174 ms 61.5% 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 2025-09-07T11:01:31.5244578Z triton_mm_925 0.0177 ms 60.4% 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 2025-09-07T11:01:31.5245549Z triton_mm_924 0.0184 ms 58.1% 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 2025-09-07T11:01:31.5246541Z triton_mm_929 0.0188 ms 56.7% 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 2025-09-07T11:01:31.5247534Z triton_mm_923 0.0189 ms 56.6% 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 2025-09-07T11:01:31.5248520Z triton_mm_933 0.0190 ms 56.1% 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 2025-09-07T11:01:31.5249391Z SingleProcess AUTOTUNE benchmarking takes 0.2473 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:31.8335687Z Autotune Choices Stats: 2025-09-07T11:01:31.8337286Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1785", "best_kernel_desc": "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", "best_time": 0.007840000092983246, "best_triton_pos": 0} 2025-09-07T11:01:31.8419462Z AUTOTUNE mm(220x512, 512x1014) 2025-09-07T11:01:31.8419884Z strides: [512, 1], [1, 512] 2025-09-07T11:01:31.8420539Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:31.8421622Z triton_mm_1785 0.0078 ms 100.0% 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 2025-09-07T11:01:31.8423116Z triton_mm_1789 0.0084 ms 92.8% 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 2025-09-07T11:01:31.8424100Z triton_mm_1784 0.0093 ms 84.5% 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 2025-09-07T11:01:31.8425080Z triton_mm_1793 0.0093 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:31.8426310Z triton_mm_1783 0.0096 ms 81.4% 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 2025-09-07T11:01:31.8427283Z triton_mm_1782 0.0097 ms 80.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:31.8428250Z triton_mm_1788 0.0097 ms 80.9% 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 2025-09-07T11:01:31.8429213Z triton_mm_1792 0.0100 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 2025-09-07T11:01:31.8430194Z triton_mm_1799 0.0108 ms 72.7% 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 2025-09-07T11:01:31.8431377Z triton_mm_1795 0.0108 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 2025-09-07T11:01:31.8432256Z SingleProcess AUTOTUNE benchmarking takes 0.2320 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:31.8617481Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8617934Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8618358Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8618775Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8619189Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8619602Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8620013Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8620656Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8621078Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8621555Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8622042Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8622383Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8622645Z cudagraph partition due to non gpu ops 2025-09-07T11:01:31.8622994Z cudagraph partition due to DeviceCopy ops 2025-09-07T11:01:31.9029809Z cudagraph partition into 2 partitions 2025-09-07T11:01:34.2928763Z pass 2025-09-07T11:01:37.6649120Z /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. 2025-09-07T11:01:37.6651595Z import pynvml # type: ignore[import] 2025-09-07T11:01:40.1590497Z 2025-09-07T11:01:41.1205911Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:01:41.1206309Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:01:41.1221292Z cuda eval squeezenet1_1 2025-09-07T11:01:50.2001588Z Autotune Choices Stats: 2025-09-07T11:01:50.2002708Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_7", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2", "best_time": 0.006912000011652708, "best_triton_pos": 0} 2025-09-07T11:01:50.2090679Z AUTOTUNE addmm(12100x16, 12100x64, 64x16) 2025-09-07T11:01:50.2090997Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:01:50.2091323Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:50.2092066Z triton_mm_7 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:01:50.2093076Z triton_mm_10 0.0072 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:50.2094604Z triton_mm_13 0.0072 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.2095594Z triton_mm_9 0.0072 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:50.2096573Z triton_mm_14 0.0072 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.2097505Z triton_mm_16 0.0072 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:50.2098346Z triton_mm_17 0.0073 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.2099189Z triton_mm_18 0.0073 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:01:50.2100014Z triton_mm_12 0.0074 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:50.2101014Z triton_mm_15 0.0074 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:50.2101751Z SingleProcess AUTOTUNE benchmarking takes 0.2533 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T11:01:50.6512249Z Autotune Choices Stats: 2025-09-07T11:01:50.6513336Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_57", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.008031999692320824, "best_triton_pos": 0} 2025-09-07T11:01:50.6599080Z AUTOTUNE addmm(12100x16, 12100x128, 128x16) 2025-09-07T11:01:50.6599433Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T11:01:50.6599749Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:50.6600743Z triton_mm_57 0.0080 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.6601655Z triton_mm_50 0.0081 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.6602568Z triton_mm_58 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:50.6603464Z triton_mm_46 0.0082 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:50.6604382Z triton_mm_45 0.0083 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:01:50.6605596Z triton_mm_52 0.0084 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:50.6606473Z triton_mm_51 0.0085 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.6607426Z triton_mm_55 0.0086 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:01:50.6608719Z triton_mm_54 0.0086 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:50.6609681Z triton_mm_47 0.0087 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:50.6610676Z SingleProcess AUTOTUNE benchmarking takes 0.2289 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:01:51.2398858Z Autotune Choices Stats: 2025-09-07T11:01:51.2399909Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_87", "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=3, num_warps=8", "best_time": 0.00687999976798892, "best_triton_pos": 0} 2025-09-07T11:01:51.2479200Z AUTOTUNE addmm(2916x32, 2916x128, 128x32) 2025-09-07T11:01:51.2479508Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T11:01:51.2479837Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:51.2480737Z triton_mm_87 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:51.2481757Z triton_mm_82 0.0069 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:51.2482712Z triton_mm_90 0.0070 ms 98.6% 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=3, num_warps=4 2025-09-07T11:01:51.2483652Z triton_mm_83 0.0070 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:51.2484615Z triton_mm_81 0.0071 ms 96.4% 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 2025-09-07T11:01:51.2485566Z triton_mm_88 0.0072 ms 95.6% 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=3, num_warps=4 2025-09-07T11:01:51.2486505Z triton_mm_89 0.0072 ms 95.6% 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=4, num_warps=8 2025-09-07T11:01:51.2487553Z triton_mm_96 0.0072 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:51.2488440Z triton_mm_95 0.0073 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:51.2489338Z triton_mm_93 0.0075 ms 91.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:01:51.2490127Z SingleProcess AUTOTUNE benchmarking takes 0.2449 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:01:51.7085280Z Autotune Choices Stats: 2025-09-07T11:01:51.7086378Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_132", "best_kernel_desc": "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=4, num_warps=4", "best_time": 0.007391999941319227, "best_triton_pos": 0} 2025-09-07T11:01:51.7166809Z AUTOTUNE addmm(2916x32, 2916x256, 256x32) 2025-09-07T11:01:51.7167162Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:01:51.7167508Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:51.7168900Z triton_mm_132 0.0074 ms 100.0% 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=4, num_warps=4 2025-09-07T11:01:51.7170599Z triton_mm_125 0.0077 ms 95.5% 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 2025-09-07T11:01:51.7171626Z triton_mm_123 0.0079 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:51.7172605Z triton_mm_131 0.0079 ms 93.1% 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=3, num_warps=4 2025-09-07T11:01:51.7173562Z triton_mm_124 0.0080 ms 92.4% 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 2025-09-07T11:01:51.7174529Z triton_mm_137 0.0081 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:51.7175500Z triton_mm_122 0.0082 ms 90.6% 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 2025-09-07T11:01:51.7176459Z triton_mm_128 0.0084 ms 88.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:51.7177516Z triton_mm_130 0.0084 ms 88.5% 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=4, num_warps=8 2025-09-07T11:01:51.7178413Z triton_mm_136 0.0084 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:01:51.7179211Z SingleProcess AUTOTUNE benchmarking takes 0.2482 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:01:52.3607933Z Autotune Choices Stats: 2025-09-07T11:01:52.3609026Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_254", "best_kernel_desc": "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", "best_time": 0.007968000136315823, "best_triton_pos": 0} 2025-09-07T11:01:52.3689886Z AUTOTUNE addmm(676x64, 676x384, 384x64) 2025-09-07T11:01:52.3690183Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T11:01:52.3690681Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:52.3691410Z triton_mm_254 0.0080 ms 100.0% 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 2025-09-07T11:01:52.3692426Z triton_mm_262 0.0080 ms 99.6% 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 2025-09-07T11:01:52.3693410Z triton_mm_258 0.0082 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:52.3694817Z triton_mm_261 0.0082 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=3, num_warps=4 2025-09-07T11:01:52.3695774Z triton_mm_253 0.0087 ms 91.5% 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 2025-09-07T11:01:52.3696744Z triton_mm_251 0.0088 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:52.3697938Z triton_mm_252 0.0089 ms 89.2% 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 2025-09-07T11:01:52.3699051Z triton_mm_257 0.0090 ms 88.9% 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 2025-09-07T11:01:52.3699949Z triton_mm_267 0.0092 ms 86.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:52.3700990Z triton_mm_260 0.0093 ms 85.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:01:52.3701764Z SingleProcess AUTOTUNE benchmarking takes 0.2689 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:52.8314036Z Autotune Choices Stats: 2025-09-07T11:01:52.8315058Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_298", "best_kernel_desc": "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", "best_time": 0.007552000228315592, "best_triton_pos": 0} 2025-09-07T11:01:52.8397660Z AUTOTUNE addmm(676x64, 676x512, 512x64) 2025-09-07T11:01:52.8397939Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:01:52.8398253Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:52.8398942Z triton_mm_298 0.0076 ms 100.0% 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 2025-09-07T11:01:52.8399938Z triton_mm_306 0.0077 ms 97.9% 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=4, num_warps=4 2025-09-07T11:01:52.8401334Z triton_mm_302 0.0079 ms 95.5% 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 2025-09-07T11:01:52.8401954Z bias_addmm 0.0084 ms 90.1% 2025-09-07T11:01:52.8402571Z triton_mm_305 0.0089 ms 84.9% 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=4 2025-09-07T11:01:52.8403545Z triton_mm_311 0.0089 ms 84.6% 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 2025-09-07T11:01:52.8404505Z triton_mm_301 0.0091 ms 83.4% 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 2025-09-07T11:01:52.8405460Z triton_mm_297 0.0091 ms 83.1% 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 2025-09-07T11:01:52.8406417Z triton_mm_296 0.0091 ms 82.8% 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 2025-09-07T11:01:52.8407384Z triton_mm_295 0.0093 ms 81.1% 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 2025-09-07T11:01:52.8408444Z SingleProcess AUTOTUNE benchmarking takes 0.2538 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:53.7770992Z Autotune Choices Stats: 2025-09-07T11:01:53.7772037Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_174", "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": 0.006912000011652708, "best_triton_pos": 0} 2025-09-07T11:01:53.7857086Z AUTOTUNE addmm(676x48, 676x256, 256x48) 2025-09-07T11:01:53.7857389Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:01:53.7857715Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:53.7858738Z triton_mm_174 0.0069 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 2025-09-07T11:01:53.7859785Z triton_mm_166 0.0072 ms 95.6% 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 2025-09-07T11:01:53.7861116Z triton_mm_170 0.0074 ms 93.9% 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 2025-09-07T11:01:53.7862107Z triton_mm_163 0.0074 ms 93.1% 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 2025-09-07T11:01:53.7863168Z triton_mm_165 0.0075 ms 91.9% 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 2025-09-07T11:01:53.7864139Z triton_mm_173 0.0075 ms 91.9% 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=4 2025-09-07T11:01:53.7865096Z triton_mm_164 0.0076 ms 91.1% 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 2025-09-07T11:01:53.7866045Z triton_mm_169 0.0076 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:53.7866990Z triton_mm_172 0.0078 ms 88.5% 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 2025-09-07T11:01:53.7868109Z triton_mm_179 0.0079 ms 87.4% 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 2025-09-07T11:01:53.7868969Z SingleProcess AUTOTUNE benchmarking takes 0.5047 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:54.2597585Z Autotune Choices Stats: 2025-09-07T11:01:54.2598812Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_210", "best_kernel_desc": "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", "best_time": 0.007968000136315823, "best_triton_pos": 0} 2025-09-07T11:01:54.2683360Z AUTOTUNE addmm(676x48, 676x384, 384x48) 2025-09-07T11:01:54.2683674Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T11:01:54.2684014Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:54.2684774Z triton_mm_210 0.0080 ms 100.0% 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 2025-09-07T11:01:54.2685823Z triton_mm_214 0.0084 ms 94.7% 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 2025-09-07T11:01:54.2687119Z triton_mm_218 0.0084 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:54.2688172Z triton_mm_209 0.0086 ms 92.2% 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 2025-09-07T11:01:54.2689102Z triton_mm_223 0.0087 ms 91.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:54.2690118Z triton_mm_217 0.0087 ms 91.2% 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=4 2025-09-07T11:01:54.2691422Z triton_mm_213 0.0088 ms 90.2% 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 2025-09-07T11:01:54.2691999Z bias_addmm 0.0089 ms 89.6% 2025-09-07T11:01:54.2692541Z triton_mm_208 0.0090 ms 88.9% 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 2025-09-07T11:01:54.2693433Z triton_mm_207 0.0090 ms 88.6% 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 2025-09-07T11:01:54.2694234Z SingleProcess AUTOTUNE benchmarking takes 0.2644 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:01:54.8156333Z Autotune Choices Stats: 2025-09-07T11:01:54.8157437Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_4", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.016543999314308167, "best_triton_pos": 0} 2025-09-07T11:01:54.8251262Z AUTOTUNE convolution(4x3x224x224, 64x3x3x3) 2025-09-07T11:01:54.8251593Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T11:01:54.8251904Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:54.8252687Z triton_convolution2d_4 0.0165 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:54.8253940Z triton_convolution2d_0 0.0181 ms 91.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:54.8255171Z triton_convolution2d_3 0.0183 ms 90.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:54.8256388Z triton_convolution2d_5 0.0221 ms 74.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:54.8257607Z triton_convolution2d_2 0.0257 ms 64.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:01:54.8258404Z convolution 0.0270 ms 61.2% 2025-09-07T11:01:54.8259037Z triton_convolution2d_1 0.0457 ms 36.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:54.8259872Z SingleProcess AUTOTUNE benchmarking takes 0.1277 seconds and 0.0005 seconds precompiling for 7 choices 2025-09-07T11:01:55.0395095Z Autotune Choices Stats: 2025-09-07T11:01:55.0396037Z {"num_choices": 17, "num_triton_choices": 15, "best_kernel": "triton_mm_24", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.006527999881654978, "best_triton_pos": 0} 2025-09-07T11:01:55.0482051Z AUTOTUNE addmm(12100x64, 12100x16, 16x64) 2025-09-07T11:01:55.0482360Z strides: [0, 1], [16, 1], [1, 16] 2025-09-07T11:01:55.0482705Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:55.0483438Z triton_mm_24 0.0065 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:55.0484596Z triton_mm_25 0.0065 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:01:55.0485808Z triton_mm_32 0.0066 ms 99.0% 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=4, num_warps=4 2025-09-07T11:01:55.0486810Z triton_mm_23 0.0066 ms 98.6% 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=2, num_warps=4 2025-09-07T11:01:55.0487768Z triton_mm_29 0.0066 ms 98.6% 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=5, num_warps=4 2025-09-07T11:01:55.0488787Z triton_mm_31 0.0067 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=4, num_warps=8 2025-09-07T11:01:55.0489665Z triton_mm_27 0.0067 ms 97.1% 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 2025-09-07T11:01:55.0490857Z triton_mm_30 0.0067 ms 97.1% 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=3, num_warps=4 2025-09-07T11:01:55.0491741Z triton_mm_26 0.0068 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:55.0492616Z triton_mm_28 0.0068 ms 96.2% 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=3, num_warps=8 2025-09-07T11:01:55.0493384Z SingleProcess AUTOTUNE benchmarking takes 0.2226 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:01:55.1337975Z Autotune Choices Stats: 2025-09-07T11:01:55.1339033Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_41", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.010304000228643417, "best_triton_pos": 0} 2025-09-07T11:01:55.1422357Z AUTOTUNE convolution(4x16x55x55, 64x16x3x3) 2025-09-07T11:01:55.1422690Z strides: [48400, 1, 880, 16], [144, 1, 48, 16] 2025-09-07T11:01:55.1423083Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:55.1423888Z triton_convolution2d_41 0.0103 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.1425148Z triton_convolution2d_37 0.0103 ms 99.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.1426385Z triton_convolution2d_40 0.0105 ms 98.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.1427788Z triton_convolution2d_42 0.0115 ms 89.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.1428698Z convolution 0.0116 ms 88.5% 2025-09-07T11:01:55.1429409Z triton_convolution2d_38 0.0117 ms 88.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.1430772Z triton_convolution2d_39 0.0152 ms 67.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:01:55.1431986Z SingleProcess AUTOTUNE benchmarking takes 0.0935 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:01:55.3793059Z Autotune Choices Stats: 2025-09-07T11:01:55.3794026Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_104", "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=8", "best_time": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T11:01:55.3878232Z AUTOTUNE addmm(2916x128, 2916x32, 32x128) 2025-09-07T11:01:55.3878593Z strides: [0, 1], [32, 1], [1, 32] 2025-09-07T11:01:55.3878967Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:55.3879762Z triton_mm_104 0.0061 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=8 2025-09-07T11:01:55.3880956Z triton_mm_99 0.0062 ms 99.5% 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 2025-09-07T11:01:55.3881943Z triton_mm_100 0.0062 ms 99.5% 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 2025-09-07T11:01:55.3882953Z triton_mm_98 0.0062 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.3883915Z triton_mm_101 0.0062 ms 98.5% 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=4 2025-09-07T11:01:55.3884875Z triton_mm_108 0.0064 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=4 2025-09-07T11:01:55.3885832Z triton_mm_105 0.0064 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:55.3886781Z triton_mm_103 0.0065 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.3887732Z triton_mm_97 0.0065 ms 94.1% 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 2025-09-07T11:01:55.3888781Z triton_mm_110 0.0065 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 2025-09-07T11:01:55.3889561Z SingleProcess AUTOTUNE benchmarking takes 0.2400 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:01:55.4840610Z Autotune Choices Stats: 2025-09-07T11:01:55.4842036Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009344000369310379, "best_triton_pos": 1, "best_triton_time": 0.010847999714314938, "best_triton_kernel": "triton_convolution2d_118", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:01:55.4924443Z AUTOTUNE convolution(4x32x27x27, 128x32x3x3) 2025-09-07T11:01:55.4924755Z strides: [23328, 1, 864, 32], [288, 1, 96, 32] 2025-09-07T11:01:55.4925062Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:55.4925350Z convolution 0.0093 ms 100.0% 2025-09-07T11:01:55.4926115Z triton_convolution2d_118 0.0108 ms 86.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.4927757Z triton_convolution2d_119 0.0112 ms 83.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.4929066Z triton_convolution2d_117 0.0124 ms 75.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.4930366Z triton_convolution2d_120 0.0134 ms 69.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.4931522Z triton_convolution2d_114 0.0137 ms 68.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.4932662Z triton_convolution2d_115 0.0168 ms 55.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.4933813Z triton_convolution2d_116 0.0251 ms 37.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:01:55.4934722Z SingleProcess AUTOTUNE benchmarking takes 0.1042 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:01:55.7539173Z Autotune Choices Stats: 2025-09-07T11:01:55.7540174Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_181", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.006207999773323536, "best_triton_pos": 0} 2025-09-07T11:01:55.7623326Z AUTOTUNE addmm(676x192, 676x48, 48x192) 2025-09-07T11:01:55.7623624Z strides: [0, 1], [48, 1], [1, 48] 2025-09-07T11:01:55.7623951Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:55.7624645Z triton_mm_181 0.0062 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.7625667Z triton_mm_187 0.0065 ms 95.6% 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 2025-09-07T11:01:55.7626657Z triton_mm_188 0.0065 ms 95.6% 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=5, num_warps=4 2025-09-07T11:01:55.7627628Z triton_mm_183 0.0067 ms 93.3% 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 2025-09-07T11:01:55.7628745Z triton_mm_182 0.0067 ms 92.8% 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 2025-09-07T11:01:55.7629961Z triton_mm_184 0.0067 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:55.7631080Z triton_mm_186 0.0068 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.7632037Z triton_mm_189 0.0068 ms 91.1% 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 2025-09-07T11:01:55.7633155Z triton_mm_191 0.0069 ms 90.2% 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 2025-09-07T11:01:55.7634372Z triton_mm_180 0.0069 ms 89.4% 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 2025-09-07T11:01:55.7635238Z SingleProcess AUTOTUNE benchmarking takes 0.2637 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T11:01:55.8676522Z Autotune Choices Stats: 2025-09-07T11:01:55.8677880Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010208000428974628, "best_triton_pos": 1, "best_triton_time": 0.017152000218629837, "best_triton_kernel": "triton_convolution2d_203", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:01:55.8765008Z AUTOTUNE convolution(4x48x13x13, 192x48x3x3) 2025-09-07T11:01:55.8765342Z strides: [8112, 1, 624, 48], [432, 1, 144, 48] 2025-09-07T11:01:55.8765651Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:55.8765937Z convolution 0.0102 ms 100.0% 2025-09-07T11:01:55.8766698Z triton_convolution2d_203 0.0172 ms 59.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.8767945Z triton_convolution2d_204 0.0181 ms 56.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.8769234Z triton_convolution2d_202 0.0220 ms 46.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.8770671Z triton_convolution2d_199 0.0228 ms 44.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.8771856Z triton_convolution2d_205 0.0235 ms 43.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:55.8772999Z triton_convolution2d_200 0.0260 ms 39.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:55.8774159Z triton_convolution2d_201 0.0366 ms 27.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:01:55.8775063Z SingleProcess AUTOTUNE benchmarking takes 0.1137 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:01:56.1392829Z Autotune Choices Stats: 2025-09-07T11:01:56.1393807Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_275", "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": 0.006496000103652477, "best_triton_pos": 0} 2025-09-07T11:01:56.1477742Z AUTOTUNE addmm(676x256, 676x64, 64x256) 2025-09-07T11:01:56.1478026Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:01:56.1478347Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:56.1479201Z triton_mm_275 0.0065 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 2025-09-07T11:01:56.1480673Z triton_mm_276 0.0066 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 2025-09-07T11:01:56.1482067Z triton_mm_280 0.0066 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 2025-09-07T11:01:56.1483113Z triton_mm_269 0.0066 ms 98.1% 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 2025-09-07T11:01:56.1484083Z triton_mm_271 0.0067 ms 97.1% 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 2025-09-07T11:01:56.1485042Z triton_mm_270 0.0067 ms 96.7% 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 2025-09-07T11:01:56.1486036Z triton_mm_272 0.0068 ms 95.3% 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 2025-09-07T11:01:56.1487009Z triton_mm_279 0.0069 ms 93.5% 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 2025-09-07T11:01:56.1487997Z triton_mm_278 0.0071 ms 91.0% 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 2025-09-07T11:01:56.1489051Z triton_mm_282 0.0072 ms 90.2% 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 2025-09-07T11:01:56.1489834Z SingleProcess AUTOTUNE benchmarking takes 0.2650 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T11:01:56.2475281Z Autotune Choices Stats: 2025-09-07T11:01:56.2476649Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010432000271975994, "best_triton_pos": 1, "best_triton_time": 0.0163199994713068, "best_triton_kernel": "triton_convolution2d_291", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:01:56.2561123Z AUTOTUNE convolution(4x64x13x13, 256x64x3x3) 2025-09-07T11:01:56.2561457Z strides: [10816, 1, 832, 64], [576, 1, 192, 64] 2025-09-07T11:01:56.2561815Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:01:56.2562117Z convolution 0.0104 ms 100.0% 2025-09-07T11:01:56.2562910Z triton_convolution2d_291 0.0163 ms 63.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:56.2564246Z triton_convolution2d_290 0.0184 ms 56.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:56.2565602Z triton_convolution2d_292 0.0186 ms 56.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:56.2567146Z triton_convolution2d_293 0.0232 ms 45.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:01:56.2568497Z triton_convolution2d_288 0.0284 ms 36.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:56.2569710Z triton_convolution2d_287 0.0288 ms 36.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:01:56.2571408Z triton_convolution2d_289 0.0485 ms 21.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:01:56.2572323Z SingleProcess AUTOTUNE benchmarking takes 0.1078 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:01:56.5196211Z Autotune Choices Stats: 2025-09-07T11:01:56.5197179Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_350", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009503999724984169, "best_triton_pos": 0} 2025-09-07T11:01:56.5280919Z AUTOTUNE addmm(676x1000, 676x512, 512x1000) 2025-09-07T11:01:56.5281226Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:01:56.5281519Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:01:56.5282164Z triton_mm_350 0.0095 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:01:56.5282746Z bias_addmm 0.0100 ms 95.5% 2025-09-07T11:01:56.5283295Z triton_mm_345 0.0104 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:01:56.5284177Z triton_mm_349 0.0106 ms 89.7% 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 2025-09-07T11:01:56.5285061Z triton_mm_348 0.0112 ms 84.9% 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 2025-09-07T11:01:56.5285968Z triton_mm_356 0.0113 ms 84.4% 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 2025-09-07T11:01:56.5286893Z triton_mm_352 0.0114 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=4, num_warps=8 2025-09-07T11:01:56.5287791Z triton_mm_346 0.0116 ms 82.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:01:56.5288693Z triton_mm_355 0.0117 ms 81.1% 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 2025-09-07T11:01:56.5289269Z addmm 0.0125 ms 75.8% 2025-09-07T11:01:56.5289702Z SingleProcess AUTOTUNE benchmarking takes 0.2658 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T11:01:59.8486831Z pass 2025-09-07T11:02:02.3381245Z accuracy pass_rate=87.50% 2025-09-07T11:02:02.3393405Z calls_captured gmean=0.00x mean=553.500x 2025-09-07T11:02:02.3397247Z unique_graphs gmean=0.00x mean=1.500x 2025-09-07T11:02:02.3400560Z graph_breaks gmean=0.00x mean=1.250x 2025-09-07T11:02:02.3404052Z unique_graph_breaks gmean=0.00x mean=0.250x 2025-09-07T11:02:02.3407602Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:02:02.3410527Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:02:02.3414159Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:02:02.3415275Z compilation_latency mean=32.811 seconds 2025-09-07T11:02:03.1447606Z + [[ 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* ]] 2025-09-07T11:02:03.1449491Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T11:02:03.1450633Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T11:02:03.1452333Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T11:02:03.6837445Z /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. 2025-09-07T11:02:03.6838626Z import pynvml # type: ignore[import] 2025-09-07T11:02:07.5146697Z /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. 2025-09-07T11:02:07.5148139Z import pynvml # type: ignore[import] 2025-09-07T11:02:10.0269633Z 2025-09-07T11:02:11.4985514Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:02:11.4985987Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:02:11.5056331Z cuda eval resnet50 2025-09-07T11:02:15.8534352Z pass 2025-09-07T11:02:18.2243628Z /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. 2025-09-07T11:02:18.2244942Z import pynvml # type: ignore[import] 2025-09-07T11:02:20.7807061Z 2025-09-07T11:02:20.9368804Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:02:20.9369166Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:02:20.9369484Z cuda eval resnet50_quantized_qat 2025-09-07T11:02:20.9375794Z Traceback (most recent call last): 2025-09-07T11:02:20.9376266Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:02:20.9376735Z ) = runner.load_model( 2025-09-07T11:02:20.9377213Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:02:20.9377730Z benchmark = benchmark_cls( 2025-09-07T11:02:20.9378112Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:02:20.9378541Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:02:20.9379068Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:02:20.9379686Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:02:20.9380139Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:02:20.9380573Z 2025-09-07T11:02:20.9380663Z model_fail_to_load 2025-09-07T11:02:22.4305479Z /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. 2025-09-07T11:02:22.4306540Z import pynvml # type: ignore[import] 2025-09-07T11:02:24.9513826Z 2025-09-07T11:02:26.3061389Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:02:26.3061750Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:02:26.3123763Z cuda eval resnext50_32x4d 2025-09-07T11:02:29.9458738Z pass 2025-09-07T11:02:31.6321784Z /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. 2025-09-07T11:02:31.6323289Z import pynvml # type: ignore[import] 2025-09-07T11:02:34.1252813Z 2025-09-07T11:02:42.2945665Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:02:42.2946222Z loading model: 0it [00:08, ?it/s] 2025-09-07T11:02:42.3060107Z cuda eval sam 2025-09-07T11:02:55.3072162Z pass 2025-09-07T11:02:57.4782660Z /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. 2025-09-07T11:02:57.4785395Z import pynvml # type: ignore[import] 2025-09-07T11:03:00.0748051Z 2025-09-07T11:03:13.8767486Z loading model: 0it [00:00, ?it/s]Warning: Custom flash attention kernels were written specifically for A100. 2025-09-07T11:03:13.8768353Z We will try to read previously created kernel configurations from /var/lib/jenkins/workspace/flash_4_configs.p. 2025-09-07T11:03:13.8769043Z You can disable this kernel by setting SEGMENT_ANYTHING_FAST_USE_FLASH_4=0 2025-09-07T11:03:13.8769615Z Loading best configs from file /var/lib/jenkins/workspace/flash_4_configs.p 2025-09-07T11:03:15.4696653Z 2025-09-07T11:03:15.4697254Z loading model: 0it [00:15, ?it/s] 2025-09-07T11:03:15.4736936Z cuda eval sam_fast 2025-09-07T11:04:02.0919981Z pass 2025-09-07T11:04:06.0788128Z /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. 2025-09-07T11:04:06.0789609Z import pynvml # type: ignore[import] 2025-09-07T11:04:08.6179824Z 2025-09-07T11:04:09.7639943Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:04:09.7640791Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:04:09.7701383Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:04:13.3989785Z pass 2025-09-07T11:04:15.1151215Z /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. 2025-09-07T11:04:15.1152646Z import pynvml # type: ignore[import] 2025-09-07T11:04:17.6068305Z 2025-09-07T11:04:18.5972335Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:04:18.5972701Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:04:18.5974303Z cuda eval soft_actor_critic 2025-09-07T11:04:21.2364850Z pass 2025-09-07T11:04:23.0958423Z /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. 2025-09-07T11:04:23.0959799Z import pynvml # type: ignore[import] 2025-09-07T11:04:25.6328321Z 2025-09-07T11:04:27.8300903Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:04:27.8301423Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:04:27.8361479Z cuda eval speech_transformer 2025-09-07T11:04:28.2538397Z ERROR:common: 2025-09-07T11:04:28.2538794Z Traceback (most recent call last): 2025-09-07T11:04:28.2539524Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2320, in check_accuracy 2025-09-07T11:04:28.2540976Z optimized_model_iter_fn = optimize_ctx( 2025-09-07T11:04:28.2541679Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1523, in export 2025-09-07T11:04:28.2542395Z ep = torch.export.export( 2025-09-07T11:04:28.2543241Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py", line 311, in export 2025-09-07T11:04:28.2543987Z raise e 2025-09-07T11:04:28.2544623Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py", line 277, in export 2025-09-07T11:04:28.2545627Z return _export( 2025-09-07T11:04:28.2546290Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1163, in wrapper 2025-09-07T11:04:28.2547025Z raise e 2025-09-07T11:04:28.2548063Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1129, in wrapper 2025-09-07T11:04:28.2548872Z ep = fn(*args, **kwargs) 2025-09-07T11:04:28.2549668Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/exported_program.py", line 124, in wrapper 2025-09-07T11:04:28.2550711Z return fn(*args, **kwargs) 2025-09-07T11:04:28.2551430Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 2255, in _export 2025-09-07T11:04:28.2552209Z ep = _export_for_training( 2025-09-07T11:04:28.2552936Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1163, in wrapper 2025-09-07T11:04:28.2553667Z raise e 2025-09-07T11:04:28.2554322Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1129, in wrapper 2025-09-07T11:04:28.2555087Z ep = fn(*args, **kwargs) 2025-09-07T11:04:28.2555855Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/exported_program.py", line 124, in wrapper 2025-09-07T11:04:28.2556665Z return fn(*args, **kwargs) 2025-09-07T11:04:28.2557466Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 2071, in _export_for_training 2025-09-07T11:04:28.2558315Z export_artifact = export_func( 2025-09-07T11:04:28.2559097Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1415, in _strict_export 2025-09-07T11:04:28.2559939Z gm_torch_level = _export_to_torch_ir( 2025-09-07T11:04:28.2560962Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 812, in _export_to_torch_ir 2025-09-07T11:04:28.2561831Z gm_torch_level, _ = torch._dynamo.export( 2025-09-07T11:04:28.2562664Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 2002, in inner 2025-09-07T11:04:28.2563464Z result_traced = opt_f(*args, **kwargs) 2025-09-07T11:04:28.2564244Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 414, in __call__ 2025-09-07T11:04:28.2565060Z return super().__call__(*args, **kwargs) 2025-09-07T11:04:28.2565932Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:04:28.2566805Z return self._call_impl(*args, **kwargs) 2025-09-07T11:04:28.2567606Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:04:28.2568417Z return forward_call(*args, **kwargs) 2025-09-07T11:04:28.2569241Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 841, in compile_wrapper 2025-09-07T11:04:28.2570442Z raise e.with_traceback(None) from e.__cause__ # User compiler error 2025-09-07T11:04:28.2571180Z torch._dynamo.exc.Unsupported: Dynamic slicing with Tensor arguments 2025-09-07T11:04:28.2572177Z Explanation: Creating slices with Tensor arguments is not supported. e.g. `l[:x]`, where `x` is a 1-element tensor. 2025-09-07T11:04:28.2573643Z 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. 2025-09-07T11:04:28.2584140Z 2025-09-07T11:04:28.2584893Z Developer debug context: SliceVariable start: TensorVariable(), stop: ConstantVariable(NoneType: None), step: ConstantVariable(NoneType: None) 2025-09-07T11:04:28.2585755Z 2025-09-07T11:04:28.2586387Z For more details about this graph break, please visit: https://meta-pytorch.github.io/compile-graph-break-site/gb/gb0038.html 2025-09-07T11:04:28.2587137Z 2025-09-07T11:04:28.2587277Z from user code: 2025-09-07T11:04:28.2588357Z File "/torchbench/torchbenchmark/models/speech_transformer/speech_transformer/transformer/transformer.py", line 27, in forward 2025-09-07T11:04:28.2589479Z encoder_padded_outputs, *_ = self.encoder(padded_input, input_lengths) 2025-09-07T11:04:28.2590946Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:04:28.2591806Z return forward_call(*args, **kwargs) 2025-09-07T11:04:28.2592737Z File "/torchbench/torchbenchmark/models/speech_transformer/speech_transformer/transformer/encoder.py", line 61, in forward 2025-09-07T11:04:28.2593807Z non_pad_mask = get_non_pad_mask(padded_input, input_lengths=input_lengths) 2025-09-07T11:04:28.2594880Z File "/torchbench/torchbenchmark/models/speech_transformer/speech_transformer/utils/utils.py", line 108, in get_non_pad_mask 2025-09-07T11:04:28.2595816Z non_pad_mask[i, input_lengths[i] :] = 0 2025-09-07T11:04:28.2596112Z 2025-09-07T11:04:28.2596937Z 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" 2025-09-07T11:04:28.2597884Z 2025-09-07T11:04:28.2598211Z TorchDynamo optimized model failed to run because of following error 2025-09-07T11:04:28.2749087Z fail_to_run 2025-09-07T11:04:29.8175691Z /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. 2025-09-07T11:04:29.8177160Z import pynvml # type: ignore[import] 2025-09-07T11:04:32.3178266Z 2025-09-07T11:04:33.3206443Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:04:33.3206930Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:04:33.3221927Z cuda eval squeezenet1_1 2025-09-07T11:04:35.5562610Z pass 2025-09-07T11:04:36.6706341Z accuracy pass_rate=77.78% 2025-09-07T11:04:36.6711596Z calls_captured gmean=0.00x mean=592.111x 2025-09-07T11:04:36.6714739Z unique_graphs gmean=0.00x mean=0.778x 2025-09-07T11:04:36.6718088Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:04:36.6721750Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:04:36.6724985Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:04:36.6728165Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:04:36.6731725Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:04:36.6732908Z compilation_latency mean=3.166 seconds 2025-09-07T11:04:37.5267449Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T11:04:38.0754522Z /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. 2025-09-07T11:04:38.0755921Z import pynvml # type: ignore[import] 2025-09-07T11:04:41.8806499Z /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. 2025-09-07T11:04:41.8808966Z import pynvml # type: ignore[import] 2025-09-07T11:04:44.3925030Z 2025-09-07T11:04:46.2774534Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:04:46.2775023Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:04:46.2839869Z cuda eval resnet50 2025-09-07T11:05:05.6509412Z pass 2025-09-07T11:05:08.5707445Z /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. 2025-09-07T11:05:08.5710791Z import pynvml # type: ignore[import] 2025-09-07T11:05:11.1329664Z 2025-09-07T11:05:11.2865932Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:05:11.2866250Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:05:11.2866528Z cuda eval resnet50_quantized_qat 2025-09-07T11:05:11.2872426Z Traceback (most recent call last): 2025-09-07T11:05:11.2872852Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:05:11.2873259Z ) = runner.load_model( 2025-09-07T11:05:11.2873657Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:05:11.2874116Z benchmark = benchmark_cls( 2025-09-07T11:05:11.2874495Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:05:11.2874905Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:05:11.2875397Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:05:11.2875972Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:05:11.2876397Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:05:11.2876634Z 2025-09-07T11:05:11.2876724Z model_fail_to_load 2025-09-07T11:05:12.6619926Z /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. 2025-09-07T11:05:12.6621658Z import pynvml # type: ignore[import] 2025-09-07T11:05:15.2962237Z 2025-09-07T11:05:17.1719974Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:05:17.1720727Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:05:17.1784402Z cuda eval resnext50_32x4d 2025-09-07T11:05:33.4039903Z pass 2025-09-07T11:05:36.5309019Z /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. 2025-09-07T11:05:36.5311279Z import pynvml # type: ignore[import] 2025-09-07T11:05:39.0241796Z 2025-09-07T11:05:45.8504539Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:05:45.8504894Z loading model: 0it [00:06, ?it/s] 2025-09-07T11:05:45.8627931Z cuda eval sam 2025-09-07T11:06:59.9076547Z pass 2025-09-07T11:07:04.9292524Z /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. 2025-09-07T11:07:04.9293805Z import pynvml # type: ignore[import] 2025-09-07T11:07:07.3378076Z 2025-09-07T11:07:08.3874691Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:07:08.3875142Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:07:08.3944362Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:07:25.3682432Z pass 2025-09-07T11:07:28.3345013Z /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. 2025-09-07T11:07:28.3346487Z import pynvml # type: ignore[import] 2025-09-07T11:07:30.8839348Z 2025-09-07T11:07:31.8723070Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:07:31.8723441Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:07:31.8751364Z cuda eval squeezenet1_1 2025-09-07T11:07:42.7437740Z pass 2025-09-07T11:07:45.0883647Z accuracy pass_rate=83.33% 2025-09-07T11:07:45.0888602Z calls_captured gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0892204Z unique_graphs gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0895998Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0899020Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0902525Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0905657Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0908825Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:07:45.0910627Z compilation_latency mean=0.000 seconds 2025-09-07T11:07:45.9405618Z + [[ 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* ]] 2025-09-07T11:07:45.9407205Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T11:07:45.9408807Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T11:07:46.4833773Z /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. 2025-09-07T11:07:46.4834977Z import pynvml # type: ignore[import] 2025-09-07T11:07:50.3204690Z /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. 2025-09-07T11:07:50.3206608Z import pynvml # type: ignore[import] 2025-09-07T11:07:52.8123024Z 2025-09-07T11:07:54.6116090Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:07:54.6116543Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:07:54.6175231Z cuda eval resnet50 2025-09-07T11:08:06.7102368Z Autotune Choices Stats: 2025-09-07T11:08:06.7103515Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_58", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009119999594986439, "best_triton_pos": 0} 2025-09-07T11:08:06.7195479Z AUTOTUNE mm(12544x64, 64x256) 2025-09-07T11:08:06.7195779Z strides: [64, 1], [1, 64] 2025-09-07T11:08:06.7196051Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:06.7196767Z triton_mm_58 0.0091 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 2025-09-07T11:08:06.7197872Z triton_mm_64 0.0092 ms 99.0% 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 2025-09-07T11:08:06.7198936Z triton_mm_66 0.0092 ms 99.0% 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 2025-09-07T11:08:06.7200680Z triton_mm_60 0.0092 ms 98.6% 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 2025-09-07T11:08:06.7201731Z triton_mm_59 0.0093 ms 97.6% 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 2025-09-07T11:08:06.7202777Z triton_mm_63 0.0093 ms 97.6% 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 2025-09-07T11:08:06.7204226Z triton_mm_56 0.0094 ms 97.3% 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 2025-09-07T11:08:06.7205277Z triton_mm_61 0.0094 ms 97.3% 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 2025-09-07T11:08:06.7206328Z triton_mm_62 0.0094 ms 97.3% 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=4, num_warps=4 2025-09-07T11:08:06.7207366Z triton_mm_68 0.0094 ms 97.3% 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 2025-09-07T11:08:06.7208284Z SingleProcess AUTOTUNE benchmarking takes 0.2423 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:08.1208700Z Autotune Choices Stats: 2025-09-07T11:08:08.1209837Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_164", "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": 0.010784000158309937, "best_triton_pos": 0} 2025-09-07T11:08:08.1296650Z AUTOTUNE mm(12544x256, 256x128) 2025-09-07T11:08:08.1296928Z strides: [256, 1], [1, 256] 2025-09-07T11:08:08.1297203Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:08.1297876Z triton_mm_164 0.0108 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 2025-09-07T11:08:08.1298862Z triton_mm_168 0.0108 ms 99.4% 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 2025-09-07T11:08:08.1299858Z triton_mm_175 0.0109 ms 98.5% 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 2025-09-07T11:08:08.1301009Z triton_mm_174 0.0112 ms 96.0% 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 2025-09-07T11:08:08.1301627Z mm 0.0113 ms 95.7% 2025-09-07T11:08:08.1302209Z triton_mm_171 0.0115 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:08:08.1303257Z triton_mm_167 0.0116 ms 93.4% 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 2025-09-07T11:08:08.1304228Z triton_mm_170 0.0116 ms 93.4% 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 2025-09-07T11:08:08.1305299Z triton_mm_166 0.0118 ms 91.6% 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 2025-09-07T11:08:08.1306193Z triton_mm_173 0.0121 ms 88.9% 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 2025-09-07T11:08:08.1307304Z SingleProcess AUTOTUNE benchmarking takes 0.2464 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:08.7129982Z Autotune Choices Stats: 2025-09-07T11:08:08.7131466Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_246", "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": 0.008287999778985977, "best_triton_pos": 0} 2025-09-07T11:08:08.7215311Z AUTOTUNE mm(3136x128, 128x512) 2025-09-07T11:08:08.7215574Z strides: [128, 1], [1, 128] 2025-09-07T11:08:08.7215846Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:08.7216868Z triton_mm_246 0.0083 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 2025-09-07T11:08:08.7217883Z triton_mm_244 0.0084 ms 98.5% 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 2025-09-07T11:08:08.7218847Z triton_mm_249 0.0085 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:08:08.7219801Z triton_mm_248 0.0085 ms 97.0% 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 2025-09-07T11:08:08.7220960Z triton_mm_245 0.0086 ms 96.6% 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 2025-09-07T11:08:08.7221947Z triton_mm_253 0.0086 ms 96.6% 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 2025-09-07T11:08:08.7222570Z mm 0.0086 ms 96.3% 2025-09-07T11:08:08.7223257Z triton_mm_252 0.0086 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 2025-09-07T11:08:08.7224264Z triton_mm_247 0.0087 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:08.7225332Z triton_mm_251 0.0087 ms 95.6% 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 2025-09-07T11:08:08.7226136Z SingleProcess AUTOTUNE benchmarking takes 0.2428 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:10.0270897Z Autotune Choices Stats: 2025-09-07T11:08:10.0271970Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_13", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.007455999962985516, "best_triton_pos": 0} 2025-09-07T11:08:10.0361919Z AUTOTUNE mm(12544x64, 64x64) 2025-09-07T11:08:10.0362177Z strides: [64, 1], [1, 64] 2025-09-07T11:08:10.0362462Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:10.0363145Z triton_mm_13 0.0075 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:08:10.0364195Z triton_mm_15 0.0076 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 2025-09-07T11:08:10.0365232Z triton_mm_14 0.0076 ms 98.3% 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 2025-09-07T11:08:10.0366593Z triton_mm_17 0.0076 ms 98.3% 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 2025-09-07T11:08:10.0367577Z triton_mm_18 0.0076 ms 98.3% 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 2025-09-07T11:08:10.0368531Z triton_mm_7 0.0076 ms 97.9% 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 2025-09-07T11:08:10.0369626Z triton_mm_22 0.0076 ms 97.9% 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 2025-09-07T11:08:10.0370983Z triton_mm_23 0.0076 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:08:10.0371949Z triton_mm_10 0.0076 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:08:10.0372905Z triton_mm_20 0.0076 ms 97.5% 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 2025-09-07T11:08:10.0373756Z SingleProcess AUTOTUNE benchmarking takes 0.2307 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:08:10.5820776Z Autotune Choices Stats: 2025-09-07T11:08:10.5821904Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_86", "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": 0.010080000385642052, "best_triton_pos": 0} 2025-09-07T11:08:10.5906968Z AUTOTUNE mm(12544x256, 256x64) 2025-09-07T11:08:10.5907241Z strides: [256, 1], [1, 256] 2025-09-07T11:08:10.5907514Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:10.5908217Z triton_mm_86 0.0101 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 2025-09-07T11:08:10.5909217Z triton_mm_80 0.0101 ms 99.4% 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=4 2025-09-07T11:08:10.5909836Z mm 0.0104 ms 96.9% 2025-09-07T11:08:10.5910555Z triton_mm_76 0.0105 ms 96.3% 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 2025-09-07T11:08:10.5911549Z triton_mm_85 0.0106 ms 95.5% 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 2025-09-07T11:08:10.5912521Z triton_mm_70 0.0107 ms 94.0% 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 2025-09-07T11:08:10.5913498Z triton_mm_83 0.0108 ms 93.2% 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 2025-09-07T11:08:10.5914457Z triton_mm_79 0.0109 ms 92.4% 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 2025-09-07T11:08:10.5915549Z triton_mm_72 0.0111 ms 90.5% 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 2025-09-07T11:08:10.5916632Z triton_mm_78 0.0112 ms 90.0% 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 2025-09-07T11:08:10.5917929Z SingleProcess AUTOTUNE benchmarking takes 0.2320 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:08:10.8806331Z Autotune Choices Stats: 2025-09-07T11:08:10.8807728Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009472000412642956, "best_triton_pos": 1, "best_triton_time": 0.009920000098645687, "best_triton_kernel": "triton_mm_356", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T11:08:10.8893881Z AUTOTUNE mm(3136x512, 512x256) 2025-09-07T11:08:10.8894183Z strides: [512, 1], [1, 512] 2025-09-07T11:08:10.8894479Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:10.8894786Z mm 0.0095 ms 100.0% 2025-09-07T11:08:10.8895849Z triton_mm_356 0.0099 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:10.8896912Z triton_mm_351 0.0108 ms 87.8% 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 2025-09-07T11:08:10.8897883Z triton_mm_355 0.0109 ms 86.8% 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 2025-09-07T11:08:10.8898869Z triton_mm_362 0.0111 ms 85.1% 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 2025-09-07T11:08:10.8899851Z triton_mm_354 0.0115 ms 82.7% 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 2025-09-07T11:08:10.8901251Z triton_mm_358 0.0115 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:08:10.8902235Z triton_mm_361 0.0115 ms 82.2% 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 2025-09-07T11:08:10.8903350Z triton_mm_352 0.0116 ms 81.8% 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 2025-09-07T11:08:10.8904322Z triton_mm_345 0.0125 ms 75.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:08:10.8905198Z SingleProcess AUTOTUNE benchmarking takes 0.2448 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:11.4412354Z Autotune Choices Stats: 2025-09-07T11:08:11.4413505Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_433", "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": 0.008063999935984612, "best_triton_pos": 0} 2025-09-07T11:08:11.4501145Z AUTOTUNE mm(784x256, 256x1024) 2025-09-07T11:08:11.4501390Z strides: [256, 1], [1, 256] 2025-09-07T11:08:11.4501623Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:11.4502233Z triton_mm_433 0.0081 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 2025-09-07T11:08:11.4503260Z triton_mm_434 0.0084 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:11.4504168Z triton_mm_429 0.0084 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:08:11.4505038Z mm 0.0085 ms 94.7% 2025-09-07T11:08:11.4505553Z triton_mm_432 0.0085 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 2025-09-07T11:08:11.4506454Z triton_mm_436 0.0086 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:08:11.4507351Z triton_mm_440 0.0090 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=5, num_warps=8 2025-09-07T11:08:11.4508624Z triton_mm_431 0.0092 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:08:11.4509532Z triton_mm_439 0.0092 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:08:11.4510583Z triton_mm_435 0.0092 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:08:11.4511382Z SingleProcess AUTOTUNE benchmarking takes 0.2473 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:12.8893820Z Autotune Choices Stats: 2025-09-07T11:08:12.8894937Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_217", "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": 0.010048000141978264, "best_triton_pos": 0} 2025-09-07T11:08:12.8987128Z AUTOTUNE mm(3136x512, 512x128) 2025-09-07T11:08:12.8987413Z strides: [512, 1], [1, 512] 2025-09-07T11:08:12.8987699Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:12.8988419Z triton_mm_217 0.0100 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 2025-09-07T11:08:12.8989129Z mm 0.0103 ms 97.8% 2025-09-07T11:08:12.8989756Z triton_mm_221 0.0104 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:12.8991821Z triton_mm_220 0.0109 ms 92.4% 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 2025-09-07T11:08:12.8992892Z triton_mm_227 0.0114 ms 88.0% 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 2025-09-07T11:08:12.8993936Z triton_mm_223 0.0116 ms 87.0% 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 2025-09-07T11:08:12.8995005Z triton_mm_226 0.0121 ms 83.1% 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 2025-09-07T11:08:12.8996147Z triton_mm_219 0.0124 ms 81.1% 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 2025-09-07T11:08:12.8997249Z triton_mm_222 0.0132 ms 76.2% 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 2025-09-07T11:08:12.8998309Z triton_mm_218 0.0138 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 2025-09-07T11:08:12.8999227Z SingleProcess AUTOTUNE benchmarking takes 0.3177 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:13.5049415Z Autotune Choices Stats: 2025-09-07T11:08:13.5050941Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_629", "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": 0.009535999968647957, "best_triton_pos": 0} 2025-09-07T11:08:13.5143202Z AUTOTUNE mm(784x1024, 1024x512) 2025-09-07T11:08:13.5143493Z strides: [1024, 1], [1, 1024] 2025-09-07T11:08:13.5143779Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:13.5144989Z triton_mm_629 0.0095 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 2025-09-07T11:08:13.5145648Z mm 0.0100 ms 95.5% 2025-09-07T11:08:13.5146574Z triton_mm_633 0.0107 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:13.5147522Z triton_mm_625 0.0121 ms 78.6% 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 2025-09-07T11:08:13.5148409Z triton_mm_628 0.0122 ms 78.0% 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 2025-09-07T11:08:13.5149293Z triton_mm_632 0.0127 ms 75.3% 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 2025-09-07T11:08:13.5150199Z triton_mm_639 0.0127 ms 75.1% 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 2025-09-07T11:08:13.5151316Z triton_mm_638 0.0139 ms 68.5% 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 2025-09-07T11:08:13.5152231Z triton_mm_622 0.0142 ms 67.0% 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 2025-09-07T11:08:13.5153113Z triton_mm_624 0.0142 ms 67.0% 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 2025-09-07T11:08:13.5153890Z SingleProcess AUTOTUNE benchmarking takes 0.2444 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:14.0614102Z Autotune Choices Stats: 2025-09-07T11:08:14.0615195Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_707", "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": 0.009472000412642956, "best_triton_pos": 0} 2025-09-07T11:08:14.0705559Z AUTOTUNE mm(196x512, 512x2048) 2025-09-07T11:08:14.0705809Z strides: [512, 1], [1, 512] 2025-09-07T11:08:14.0706053Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:14.0706714Z triton_mm_707 0.0095 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 2025-09-07T11:08:14.0707732Z triton_mm_711 0.0098 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:14.0708362Z mm 0.0101 ms 93.7% 2025-09-07T11:08:14.0708940Z triton_mm_710 0.0104 ms 90.8% 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 2025-09-07T11:08:14.0709902Z triton_mm_706 0.0105 ms 90.2% 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 2025-09-07T11:08:14.0711572Z triton_mm_717 0.0106 ms 89.7% 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 2025-09-07T11:08:14.0712573Z triton_mm_703 0.0108 ms 88.1% 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 2025-09-07T11:08:14.0713572Z triton_mm_700 0.0112 ms 84.8% 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 2025-09-07T11:08:14.0714883Z triton_mm_702 0.0112 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:08:14.0715856Z triton_mm_716 0.0113 ms 84.1% 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 2025-09-07T11:08:14.0716718Z SingleProcess AUTOTUNE benchmarking takes 0.2397 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:15.0154542Z Autotune Choices Stats: 2025-09-07T11:08:15.0155533Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_400", "best_kernel_desc": "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", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:08:15.0247085Z AUTOTUNE mm(784x1024, 1024x256) 2025-09-07T11:08:15.0247493Z strides: [1024, 1], [1, 1024] 2025-09-07T11:08:15.0247886Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:15.0248849Z triton_mm_400 0.0092 ms 100.0% 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 2025-09-07T11:08:15.0250783Z triton_mm_404 0.0095 ms 97.0% 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 2025-09-07T11:08:15.0251687Z mm 0.0097 ms 95.4% 2025-09-07T11:08:15.0252518Z triton_mm_408 0.0104 ms 88.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:15.0253875Z triton_mm_399 0.0117 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:08:15.0255014Z triton_mm_403 0.0121 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 2025-09-07T11:08:15.0256435Z triton_mm_398 0.0122 ms 75.8% 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 2025-09-07T11:08:15.0257352Z triton_mm_414 0.0125 ms 73.8% 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 2025-09-07T11:08:15.0258155Z triton_mm_407 0.0125 ms 73.5% 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 2025-09-07T11:08:15.0258935Z triton_mm_397 0.0130 ms 70.8% 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 2025-09-07T11:08:15.0259647Z SingleProcess AUTOTUNE benchmarking takes 0.2432 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:15.6812167Z Autotune Choices Stats: 2025-09-07T11:08:15.6813473Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010528000071644783, "best_triton_pos": 1, "best_triton_time": 0.010847999714314938, "best_triton_kernel": "triton_mm_677", "best_triton_kernel_desc": "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"} 2025-09-07T11:08:15.6905384Z AUTOTUNE mm(196x2048, 2048x512) 2025-09-07T11:08:15.6905663Z strides: [2048, 1], [1, 2048] 2025-09-07T11:08:15.6905918Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:15.6906178Z mm 0.0105 ms 100.0% 2025-09-07T11:08:15.6906767Z triton_mm_677 0.0108 ms 97.1% 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 2025-09-07T11:08:15.6908383Z triton_mm_681 0.0120 ms 88.0% 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 2025-09-07T11:08:15.6909374Z triton_mm_685 0.0136 ms 77.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:15.6910742Z triton_mm_691 0.0175 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=5, num_warps=8 2025-09-07T11:08:15.6911715Z triton_mm_676 0.0177 ms 59.5% 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 2025-09-07T11:08:15.6912670Z triton_mm_675 0.0184 ms 57.3% 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 2025-09-07T11:08:15.6913630Z triton_mm_674 0.0190 ms 55.4% 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 2025-09-07T11:08:15.6914584Z triton_mm_680 0.0190 ms 55.4% 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 2025-09-07T11:08:15.6915537Z triton_mm_684 0.0192 ms 54.9% 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 2025-09-07T11:08:15.6916369Z SingleProcess AUTOTUNE benchmarking takes 0.2540 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:20.6347381Z pass 2025-09-07T11:08:23.8624832Z /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. 2025-09-07T11:08:23.8626334Z import pynvml # type: ignore[import] 2025-09-07T11:08:26.6087089Z 2025-09-07T11:08:26.7688401Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:08:26.7688789Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:08:26.7689098Z cuda eval resnet50_quantized_qat 2025-09-07T11:08:26.7693567Z Traceback (most recent call last): 2025-09-07T11:08:26.7694090Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:08:26.7694563Z ) = runner.load_model( 2025-09-07T11:08:26.7695022Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:08:26.7695535Z benchmark = benchmark_cls( 2025-09-07T11:08:26.7695950Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:08:26.7696377Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:08:26.7696914Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:08:26.7697547Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:08:26.7698340Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:08:26.7698613Z 2025-09-07T11:08:26.7698701Z model_fail_to_load 2025-09-07T11:08:28.3779882Z /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. 2025-09-07T11:08:28.3782256Z import pynvml # type: ignore[import] 2025-09-07T11:08:30.9219839Z 2025-09-07T11:08:32.4480862Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:08:32.4481593Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:08:32.4539798Z cuda eval resnext50_32x4d 2025-09-07T11:08:43.7939104Z Autotune Choices Stats: 2025-09-07T11:08:43.7941635Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_91", "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": 0.010143999941647053, "best_triton_pos": 0} 2025-09-07T11:08:43.8035930Z AUTOTUNE mm(12544x128, 128x256) 2025-09-07T11:08:43.8036343Z strides: [128, 1], [1, 128] 2025-09-07T11:08:43.8036721Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:43.8037653Z triton_mm_91 0.0101 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 2025-09-07T11:08:43.8039080Z triton_mm_93 0.0102 ms 99.7% 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 2025-09-07T11:08:43.8040686Z triton_mm_98 0.0103 ms 98.4% 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 2025-09-07T11:08:43.8042116Z triton_mm_95 0.0104 ms 97.8% 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 2025-09-07T11:08:43.8043033Z mm 0.0104 ms 97.5% 2025-09-07T11:08:43.8043878Z triton_mm_96 0.0105 ms 96.4% 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 2025-09-07T11:08:43.8045323Z triton_mm_92 0.0106 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 2025-09-07T11:08:43.8046787Z triton_mm_99 0.0106 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=3, num_warps=4 2025-09-07T11:08:43.8048203Z triton_mm_88 0.0106 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:08:43.8049642Z triton_mm_94 0.0108 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:43.8051000Z SingleProcess AUTOTUNE benchmarking takes 0.2664 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:44.1176319Z Autotune Choices Stats: 2025-09-07T11:08:44.1177456Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_150", "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": 0.011455999687314034, "best_triton_pos": 0} 2025-09-07T11:08:44.1268163Z AUTOTUNE mm(12544x256, 256x256) 2025-09-07T11:08:44.1268428Z strides: [256, 1], [1, 256] 2025-09-07T11:08:44.1268699Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:44.1269404Z triton_mm_150 0.0115 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 2025-09-07T11:08:44.1270828Z mm 0.0120 ms 95.7% 2025-09-07T11:08:44.1271443Z triton_mm_156 0.0123 ms 93.5% 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 2025-09-07T11:08:44.1272456Z triton_mm_148 0.0125 ms 91.8% 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 2025-09-07T11:08:44.1273456Z triton_mm_152 0.0126 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 2025-09-07T11:08:44.1274926Z triton_mm_155 0.0127 ms 90.4% 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 2025-09-07T11:08:44.1276092Z triton_mm_149 0.0127 ms 89.9% 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 2025-09-07T11:08:44.1277154Z triton_mm_153 0.0128 ms 89.7% 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 2025-09-07T11:08:44.1278207Z triton_mm_145 0.0138 ms 82.9% 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 2025-09-07T11:08:44.1279261Z triton_mm_154 0.0143 ms 80.1% 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 2025-09-07T11:08:44.1280191Z SingleProcess AUTOTUNE benchmarking takes 0.2440 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:44.7261328Z Autotune Choices Stats: 2025-09-07T11:08:44.7262461Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_14", "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": 0.007903999648988247, "best_triton_pos": 0} 2025-09-07T11:08:44.7359462Z AUTOTUNE mm(12544x64, 64x128) 2025-09-07T11:08:44.7359803Z strides: [64, 1], [1, 64] 2025-09-07T11:08:44.7360106Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:44.7361094Z triton_mm_14 0.0079 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 2025-09-07T11:08:44.7362282Z triton_mm_24 0.0081 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=5, num_warps=8 2025-09-07T11:08:44.7363446Z triton_mm_10 0.0082 ms 96.9% 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 2025-09-07T11:08:44.7364604Z triton_mm_23 0.0082 ms 96.1% 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 2025-09-07T11:08:44.7365759Z triton_mm_20 0.0083 ms 95.7% 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 2025-09-07T11:08:44.7366899Z triton_mm_18 0.0084 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=4, num_warps=4 2025-09-07T11:08:44.7368037Z triton_mm_22 0.0084 ms 94.3% 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 2025-09-07T11:08:44.7369176Z triton_mm_13 0.0084 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 2025-09-07T11:08:44.7370917Z triton_mm_19 0.0084 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 2025-09-07T11:08:44.7372060Z triton_mm_16 0.0085 ms 93.2% 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 2025-09-07T11:08:44.7373056Z SingleProcess AUTOTUNE benchmarking takes 0.2539 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:45.0773220Z Autotune Choices Stats: 2025-09-07T11:08:45.0774779Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_214", "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": 0.009151999838650227, "best_triton_pos": 0} 2025-09-07T11:08:45.0866292Z AUTOTUNE mm(3136x256, 256x512) 2025-09-07T11:08:45.0866594Z strides: [256, 1], [1, 256] 2025-09-07T11:08:45.0866872Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:45.0867590Z triton_mm_214 0.0092 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 2025-09-07T11:08:45.0868675Z triton_mm_210 0.0093 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:08:45.0869689Z triton_mm_217 0.0094 ms 96.9% 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 2025-09-07T11:08:45.0870664Z mm 0.0095 ms 96.0% 2025-09-07T11:08:45.0871264Z triton_mm_213 0.0096 ms 95.7% 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 2025-09-07T11:08:45.0872257Z triton_mm_221 0.0096 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 2025-09-07T11:08:45.0873259Z triton_mm_220 0.0096 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 2025-09-07T11:08:45.0874253Z triton_mm_212 0.0100 ms 92.0% 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 2025-09-07T11:08:45.0875394Z triton_mm_216 0.0100 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 2025-09-07T11:08:45.0876459Z triton_mm_219 0.0102 ms 89.4% 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 2025-09-07T11:08:45.0877374Z SingleProcess AUTOTUNE benchmarking takes 0.2458 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:45.4485260Z Autotune Choices Stats: 2025-09-07T11:08:45.4486416Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_316", "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": 0.010623999871313572, "best_triton_pos": 0} 2025-09-07T11:08:45.4581219Z AUTOTUNE mm(3136x512, 512x512) 2025-09-07T11:08:45.4581514Z strides: [512, 1], [1, 512] 2025-09-07T11:08:45.4581793Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:45.4582514Z triton_mm_316 0.0106 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 2025-09-07T11:08:45.4583540Z mm 0.0107 ms 99.1% 2025-09-07T11:08:45.4584156Z triton_mm_309 0.0110 ms 96.2% 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 2025-09-07T11:08:45.4585190Z triton_mm_305 0.0112 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:08:45.4586231Z triton_mm_315 0.0113 ms 93.8% 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 2025-09-07T11:08:45.4587657Z triton_mm_308 0.0118 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=4, num_warps=8 2025-09-07T11:08:45.4588685Z triton_mm_312 0.0119 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 2025-09-07T11:08:45.4589723Z triton_mm_310 0.0127 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:45.4591119Z triton_mm_311 0.0130 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=3, num_warps=4 2025-09-07T11:08:45.4592156Z triton_mm_307 0.0133 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 2025-09-07T11:08:45.4593063Z SingleProcess AUTOTUNE benchmarking takes 0.2574 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:46.1805817Z Autotune Choices Stats: 2025-09-07T11:08:46.1806818Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_374", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009151999838650227, "best_triton_pos": 0} 2025-09-07T11:08:46.1908198Z AUTOTUNE mm(784x512, 512x1024) 2025-09-07T11:08:46.1908621Z strides: [512, 1], [1, 512] 2025-09-07T11:08:46.1908979Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:46.1909866Z triton_mm_374 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:46.1911435Z mm 0.0096 ms 95.7% 2025-09-07T11:08:46.1912324Z triton_mm_373 0.0099 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:08:46.1913823Z triton_mm_380 0.0105 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=5, num_warps=8 2025-09-07T11:08:46.1915317Z triton_mm_376 0.0106 ms 86.4% 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 2025-09-07T11:08:46.1916886Z triton_mm_372 0.0108 ms 85.1% 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 2025-09-07T11:08:46.1918455Z triton_mm_379 0.0108 ms 85.1% 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 2025-09-07T11:08:46.1920109Z triton_mm_369 0.0108 ms 84.9% 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 2025-09-07T11:08:46.1921603Z triton_mm_370 0.0110 ms 83.4% 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 2025-09-07T11:08:46.1923322Z triton_mm_375 0.0122 ms 75.3% 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 2025-09-07T11:08:46.1924667Z SingleProcess AUTOTUNE benchmarking takes 0.2484 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:46.6140100Z Autotune Choices Stats: 2025-09-07T11:08:46.6142216Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010528000071644783, "best_triton_pos": 1, "best_triton_time": 0.010847999714314938, "best_triton_kernel": "triton_mm_545", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T11:08:46.6239598Z AUTOTUNE mm(784x1024, 1024x1024) 2025-09-07T11:08:46.6239923Z strides: [1024, 1], [1, 1024] 2025-09-07T11:08:46.6240426Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:46.6240754Z mm 0.0105 ms 100.0% 2025-09-07T11:08:46.6241431Z triton_mm_545 0.0108 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:46.6242505Z triton_mm_551 0.0130 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 2025-09-07T11:08:46.6243575Z triton_mm_541 0.0131 ms 80.6% 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 2025-09-07T11:08:46.6244624Z triton_mm_540 0.0131 ms 80.4% 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 2025-09-07T11:08:46.6245661Z triton_mm_544 0.0133 ms 79.3% 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 2025-09-07T11:08:46.6246707Z triton_mm_550 0.0145 ms 72.8% 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 2025-09-07T11:08:46.6247748Z triton_mm_543 0.0146 ms 72.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:08:46.6248800Z triton_mm_547 0.0147 ms 71.7% 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 2025-09-07T11:08:46.6249840Z triton_mm_537 0.0179 ms 58.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:08:46.6250946Z SingleProcess AUTOTUNE benchmarking takes 0.2580 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:08:47.4820871Z Autotune Choices Stats: 2025-09-07T11:08:47.4822330Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_605", "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": 0.010784000158309937, "best_triton_pos": 0} 2025-09-07T11:08:47.4918451Z AUTOTUNE mm(196x1024, 1024x2048) 2025-09-07T11:08:47.4918946Z strides: [1024, 1], [1, 1024] 2025-09-07T11:08:47.4919348Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:47.4920600Z triton_mm_605 0.0108 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 2025-09-07T11:08:47.4922154Z triton_mm_609 0.0116 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:47.4924232Z triton_mm_615 0.0127 ms 84.7% 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 2025-09-07T11:08:47.4925755Z triton_mm_601 0.0129 ms 83.8% 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 2025-09-07T11:08:47.4927317Z triton_mm_608 0.0138 ms 78.4% 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 2025-09-07T11:08:47.4929351Z triton_mm_614 0.0148 ms 73.1% 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 2025-09-07T11:08:47.4931076Z triton_mm_611 0.0154 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 2025-09-07T11:08:47.4932606Z triton_mm_607 0.0155 ms 69.8% 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 2025-09-07T11:08:47.4934058Z triton_mm_604 0.0163 ms 66.3% 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 2025-09-07T11:08:47.4935542Z triton_mm_599 0.0164 ms 65.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:08:47.4936847Z SingleProcess AUTOTUNE benchmarking takes 0.3052 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:47.8568568Z Autotune Choices Stats: 2025-09-07T11:08:47.8569875Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011487999930977821, "best_triton_pos": 1, "best_triton_time": 0.011680000461637974, "best_triton_kernel": "triton_mm_582", "best_triton_kernel_desc": "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"} 2025-09-07T11:08:47.8668389Z AUTOTUNE mm(196x2048, 2048x1024) 2025-09-07T11:08:47.8668715Z strides: [2048, 1], [1, 2048] 2025-09-07T11:08:47.8669008Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:08:47.8669305Z mm 0.0115 ms 100.0% 2025-09-07T11:08:47.8669967Z triton_mm_582 0.0117 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:08:47.8671257Z triton_mm_586 0.0125 ms 91.8% 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 2025-09-07T11:08:47.8672306Z triton_mm_590 0.0140 ms 82.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:08:47.8673353Z triton_mm_596 0.0178 ms 64.7% 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 2025-09-07T11:08:47.8674391Z triton_mm_580 0.0188 ms 61.0% 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 2025-09-07T11:08:47.8675435Z triton_mm_581 0.0190 ms 60.5% 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 2025-09-07T11:08:47.8676547Z triton_mm_585 0.0193 ms 59.5% 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 2025-09-07T11:08:47.8678100Z triton_mm_579 0.0197 ms 58.3% 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 2025-09-07T11:08:47.8679242Z triton_mm_589 0.0197 ms 58.2% 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 2025-09-07T11:08:47.8680439Z SingleProcess AUTOTUNE benchmarking takes 0.2696 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:08:53.1271903Z pass 2025-09-07T11:08:56.3197405Z /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. 2025-09-07T11:08:56.3198708Z import pynvml # type: ignore[import] 2025-09-07T11:08:58.7920176Z 2025-09-07T11:09:07.2108237Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:09:07.2108611Z loading model: 0it [00:08, ?it/s] 2025-09-07T11:09:07.2233367Z cuda eval sam 2025-09-07T11:09:51.4493609Z Autotune Choices Stats: 2025-09-07T11:09:51.4494743Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_4818", "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": 0.008224000222980976, "best_triton_pos": 0} 2025-09-07T11:09:51.4592741Z AUTOTUNE mm(4096x256, 256x128) 2025-09-07T11:09:51.4593023Z strides: [256, 1], [1, 256] 2025-09-07T11:09:51.4593259Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:09:51.4593870Z triton_mm_4818 0.0082 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 2025-09-07T11:09:51.4594875Z triton_mm_4817 0.0084 ms 97.3% 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 2025-09-07T11:09:51.4595485Z mm 0.0086 ms 95.2% 2025-09-07T11:09:51.4596053Z triton_mm_4821 0.0088 ms 93.5% 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 2025-09-07T11:09:51.4597022Z triton_mm_4813 0.0088 ms 93.1% 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 2025-09-07T11:09:51.4598002Z triton_mm_4822 0.0088 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:09:51.4598979Z triton_mm_4824 0.0089 ms 92.1% 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 2025-09-07T11:09:51.4599945Z triton_mm_4812 0.0090 ms 91.5% 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 2025-09-07T11:09:51.4601263Z triton_mm_4820 0.0090 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=4, num_warps=8 2025-09-07T11:09:51.4602238Z triton_mm_4828 0.0093 ms 88.0% 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 2025-09-07T11:09:51.4603085Z SingleProcess AUTOTUNE benchmarking takes 0.2466 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:10:10.3887033Z pass 2025-09-07T11:10:15.5737134Z /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. 2025-09-07T11:10:15.5738577Z import pynvml # type: ignore[import] 2025-09-07T11:10:18.1021244Z 2025-09-07T11:10:32.1697099Z loading model: 0it [00:00, ?it/s]Warning: Custom flash attention kernels were written specifically for A100. 2025-09-07T11:10:32.1697911Z We will try to read previously created kernel configurations from /var/lib/jenkins/workspace/flash_4_configs.p. 2025-09-07T11:10:32.1698571Z You can disable this kernel by setting SEGMENT_ANYTHING_FAST_USE_FLASH_4=0 2025-09-07T11:10:32.1699562Z Loading best configs from file /var/lib/jenkins/workspace/flash_4_configs.p 2025-09-07T11:10:32.5403523Z 2025-09-07T11:10:32.5403900Z loading model: 0it [00:14, ?it/s] 2025-09-07T11:10:32.5445832Z cuda eval sam_fast 2025-09-07T11:11:35.8124965Z pass 2025-09-07T11:11:41.3944953Z /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. 2025-09-07T11:11:41.3946822Z import pynvml # type: ignore[import] 2025-09-07T11:11:43.9187352Z 2025-09-07T11:11:45.0189166Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:11:45.0189518Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:11:45.0251528Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:11:56.0471510Z Autotune Choices Stats: 2025-09-07T11:11:56.0472615Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_25", "best_kernel_desc": "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", "best_time": 0.006624000146985054, "best_triton_pos": 0} 2025-09-07T11:11:56.0571291Z AUTOTUNE mm(12544x24, 24x58) 2025-09-07T11:11:56.0571566Z strides: [24, 1], [1, 24] 2025-09-07T11:11:56.0571838Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:11:56.0572516Z triton_mm_25 0.0066 ms 100.0% 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 2025-09-07T11:11:56.0573545Z triton_mm_30 0.0067 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:11:56.0574538Z triton_mm_31 0.0067 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:11:56.0575504Z triton_mm_23 0.0067 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:11:56.0576454Z triton_mm_24 0.0067 ms 98.6% 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 2025-09-07T11:11:56.0577410Z triton_mm_26 0.0067 ms 98.6% 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=4 2025-09-07T11:11:56.0578379Z triton_mm_34 0.0067 ms 98.6% 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 2025-09-07T11:11:56.0579354Z triton_mm_28 0.0068 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:11:56.0580680Z triton_mm_36 0.0068 ms 96.7% 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=2, num_warps=8 2025-09-07T11:11:56.0581523Z triton_mm_29 0.0069 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:11:56.0582904Z SingleProcess AUTOTUNE benchmarking takes 0.2128 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:11:56.6747182Z Autotune Choices Stats: 2025-09-07T11:11:56.6748261Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_191", "best_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", "best_time": 0.007360000163316727, "best_triton_pos": 0} 2025-09-07T11:11:56.6845403Z AUTOTUNE mm(3136x116, 116x116) 2025-09-07T11:11:56.6845706Z strides: [116, 1], [1, 116] 2025-09-07T11:11:56.6845955Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:11:56.6846995Z triton_mm_191 0.0074 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 2025-09-07T11:11:56.6847985Z triton_mm_187 0.0074 ms 99.6% 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 2025-09-07T11:11:56.6848912Z triton_mm_190 0.0074 ms 99.6% 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 2025-09-07T11:11:56.6849832Z triton_mm_184 0.0077 ms 95.4% 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 2025-09-07T11:11:56.6851209Z triton_mm_192 0.0078 ms 94.3% 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 2025-09-07T11:11:56.6852194Z triton_mm_195 0.0078 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:11:56.6853177Z triton_mm_185 0.0080 ms 92.0% 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 2025-09-07T11:11:56.6854147Z triton_mm_196 0.0080 ms 91.6% 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 2025-09-07T11:11:56.6855103Z triton_mm_186 0.0081 ms 91.3% 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 2025-09-07T11:11:56.6856071Z triton_mm_197 0.0081 ms 91.3% 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=4, num_warps=8 2025-09-07T11:11:56.6856922Z SingleProcess AUTOTUNE benchmarking takes 0.2636 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:11:57.2435657Z Autotune Choices Stats: 2025-09-07T11:11:57.2437138Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_57", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.0066559999249875546, "best_triton_pos": 0} 2025-09-07T11:11:57.2521540Z AUTOTUNE mm(3136x58, 58x58) 2025-09-07T11:11:57.2521822Z strides: [58, 1], [1, 58] 2025-09-07T11:11:57.2522298Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:11:57.2522890Z triton_mm_57 0.0067 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:11:57.2523743Z triton_mm_59 0.0067 ms 99.0% 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 2025-09-07T11:11:57.2524782Z triton_mm_67 0.0067 ms 99.0% 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=4 2025-09-07T11:11:57.2525580Z triton_mm_68 0.0068 ms 98.6% 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=4, num_warps=4 2025-09-07T11:11:57.2526363Z triton_mm_64 0.0068 ms 98.1% 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=5, num_warps=4 2025-09-07T11:11:57.2527365Z triton_mm_58 0.0068 ms 97.7% 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 2025-09-07T11:11:57.2528363Z triton_mm_63 0.0068 ms 97.2% 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 2025-09-07T11:11:57.2529134Z triton_mm_66 0.0069 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:11:57.2529918Z triton_mm_65 0.0071 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:11:57.2530952Z triton_mm_62 0.0071 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:11:57.2531651Z SingleProcess AUTOTUNE benchmarking takes 0.2384 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:11:57.8815542Z Autotune Choices Stats: 2025-09-07T11:11:57.8817067Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_509", "best_kernel_desc": "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", "best_time": 0.007391999941319227, "best_triton_pos": 0} 2025-09-07T11:11:57.8915683Z AUTOTUNE mm(784x232, 232x232) 2025-09-07T11:11:57.8916126Z strides: [232, 1], [1, 232] 2025-09-07T11:11:57.8916504Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:11:57.8917481Z triton_mm_509 0.0074 ms 100.0% 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 2025-09-07T11:11:57.8918994Z triton_mm_508 0.0076 ms 97.9% 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 2025-09-07T11:11:57.8921169Z triton_mm_510 0.0076 ms 97.9% 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 2025-09-07T11:11:57.8922111Z mm 0.0076 ms 97.1% 2025-09-07T11:11:57.8922961Z triton_mm_513 0.0076 ms 97.1% 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 2025-09-07T11:11:57.8924412Z triton_mm_514 0.0076 ms 97.1% 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 2025-09-07T11:11:57.8925866Z triton_mm_507 0.0080 ms 92.4% 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 2025-09-07T11:11:57.8927361Z triton_mm_517 0.0082 ms 90.2% 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 2025-09-07T11:11:57.8928744Z triton_mm_516 0.0083 ms 89.2% 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 2025-09-07T11:11:57.8930915Z triton_mm_518 0.0084 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:11:57.8932168Z SingleProcess AUTOTUNE benchmarking takes 0.2514 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:11:58.4899703Z Autotune Choices Stats: 2025-09-07T11:11:58.4901265Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_224", "best_kernel_desc": "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", "best_time": 0.00687999976798892, "best_triton_pos": 0} 2025-09-07T11:11:58.4996367Z AUTOTUNE mm(784x116, 116x116) 2025-09-07T11:11:58.4996643Z strides: [116, 1], [1, 116] 2025-09-07T11:11:58.4997239Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:11:58.4997951Z triton_mm_224 0.0069 ms 100.0% 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 2025-09-07T11:11:58.4999034Z triton_mm_225 0.0069 ms 99.5% 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 2025-09-07T11:11:58.5000077Z triton_mm_223 0.0069 ms 99.1% 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 2025-09-07T11:11:58.5001308Z triton_mm_222 0.0071 ms 97.3% 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 2025-09-07T11:11:58.5002288Z triton_mm_228 0.0071 ms 96.4% 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 2025-09-07T11:11:58.5002891Z mm 0.0072 ms 95.6% 2025-09-07T11:11:58.5003460Z triton_mm_229 0.0073 ms 94.7% 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 2025-09-07T11:11:58.5004432Z triton_mm_230 0.0076 ms 90.3% 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 2025-09-07T11:11:58.5005393Z triton_mm_233 0.0076 ms 90.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:11:58.5006362Z triton_mm_231 0.0076 ms 90.0% 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 2025-09-07T11:11:58.5007202Z SingleProcess AUTOTUNE benchmarking takes 0.2445 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:11:59.2174126Z Autotune Choices Stats: 2025-09-07T11:11:59.2175713Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_548", "best_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", "best_time": 0.007071999832987785, "best_triton_pos": 0} 2025-09-07T11:11:59.2269099Z AUTOTUNE mm(196x232, 232x232) 2025-09-07T11:11:59.2269527Z strides: [232, 1], [1, 232] 2025-09-07T11:11:59.2269922Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:11:59.2271392Z triton_mm_548 0.0071 ms 100.0% 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 2025-09-07T11:11:59.2272412Z mm 0.0071 ms 99.1% 2025-09-07T11:11:59.2273313Z triton_mm_547 0.0072 ms 98.7% 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 2025-09-07T11:11:59.2275155Z triton_mm_552 0.0072 ms 97.8% 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 2025-09-07T11:11:59.2276641Z triton_mm_551 0.0073 ms 97.4% 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 2025-09-07T11:11:59.2278384Z triton_mm_546 0.0074 ms 96.1% 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 2025-09-07T11:11:59.2280113Z triton_mm_545 0.0075 ms 94.8% 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 2025-09-07T11:11:59.2282277Z triton_mm_555 0.0080 ms 88.8% 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 2025-09-07T11:11:59.2283834Z triton_mm_554 0.0082 ms 86.3% 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 2025-09-07T11:11:59.2285371Z triton_mm_556 0.0082 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:11:59.2286691Z SingleProcess AUTOTUNE benchmarking takes 0.2490 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:12:00.0787361Z Autotune Choices Stats: 2025-09-07T11:12:00.0789060Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_4", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.015424000099301338, "best_triton_pos": 0} 2025-09-07T11:12:00.0887204Z AUTOTUNE convolution(4x3x224x224, 24x3x3x3) 2025-09-07T11:12:00.0887707Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T11:12:00.0888149Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:12:00.0889331Z triton_convolution2d_4 0.0154 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:12:00.0891448Z triton_convolution2d_2 0.0175 ms 88.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:12:00.0893394Z triton_convolution2d_0 0.0183 ms 84.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:12:00.0895290Z triton_convolution2d_3 0.0190 ms 81.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:12:00.0896464Z convolution 0.0196 ms 78.5% 2025-09-07T11:12:00.0897576Z triton_convolution2d_1 0.0252 ms 61.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:12:00.0899458Z triton_convolution2d_5 0.0258 ms 59.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:12:00.0901195Z SingleProcess AUTOTUNE benchmarking takes 0.1069 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:12:00.2897800Z Autotune Choices Stats: 2025-09-07T11:12:00.2899285Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_10", "best_kernel_desc": "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=4", "best_time": 0.0060800001956522465, "best_triton_pos": 0} 2025-09-07T11:12:00.2994446Z AUTOTUNE mm(3136x24, 24x58) 2025-09-07T11:12:00.2994866Z strides: [24, 1], [1, 24] 2025-09-07T11:12:00.2995247Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:12:00.2996194Z triton_mm_10 0.0061 ms 100.0% 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=4 2025-09-07T11:12:00.2997972Z triton_mm_7 0.0061 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:12:00.2999773Z triton_mm_9 0.0062 ms 98.4% 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 2025-09-07T11:12:00.3001498Z triton_mm_8 0.0062 ms 97.4% 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 2025-09-07T11:12:00.3002989Z triton_mm_15 0.0062 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:12:00.3004469Z triton_mm_6 0.0063 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:12:00.3006137Z triton_mm_12 0.0063 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:12:00.3007694Z triton_mm_14 0.0063 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:12:00.3009224Z triton_mm_17 0.0063 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:12:00.3010951Z triton_mm_13 0.0064 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:12:00.3012290Z SingleProcess AUTOTUNE benchmarking takes 0.2103 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T11:12:00.5926487Z Autotune Choices Stats: 2025-09-07T11:12:00.5928000Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_662", "best_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", "best_time": 0.00800000037997961, "best_triton_pos": 0} 2025-09-07T11:12:00.6023258Z AUTOTUNE mm(196x464, 464x1024) 2025-09-07T11:12:00.6023684Z strides: [464, 1], [1, 464] 2025-09-07T11:12:00.6024069Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:12:00.6025078Z triton_mm_662 0.0080 ms 100.0% 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 2025-09-07T11:12:00.6026632Z triton_mm_666 0.0081 ms 98.4% 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 2025-09-07T11:12:00.6027595Z mm 0.0084 ms 95.8% 2025-09-07T11:12:00.6028469Z triton_mm_661 0.0088 ms 91.2% 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 2025-09-07T11:12:00.6029957Z triton_mm_660 0.0091 ms 88.0% 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 2025-09-07T11:12:00.6031882Z triton_mm_665 0.0092 ms 87.4% 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 2025-09-07T11:12:00.6033532Z triton_mm_670 0.0092 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:12:00.6035037Z triton_mm_659 0.0097 ms 82.8% 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 2025-09-07T11:12:00.6036681Z triton_mm_669 0.0098 ms 81.4% 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 2025-09-07T11:12:00.6038416Z triton_mm_668 0.0100 ms 80.1% 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 2025-09-07T11:12:00.6039735Z SingleProcess AUTOTUNE benchmarking takes 0.2511 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:12:00.8457838Z Autotune Choices Stats: 2025-09-07T11:12:00.8459328Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_681", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.008671999908983707, "best_triton_pos": 0} 2025-09-07T11:12:00.8557123Z AUTOTUNE addmm(4x1000, 4x1024, 1024x1000) 2025-09-07T11:12:00.8557593Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T11:12:00.8558076Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:12:00.8559151Z triton_mm_681 0.0087 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:12:00.8560921Z triton_mm_685 0.0092 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:12:00.8561903Z bias_addmm 0.0092 ms 93.8% 2025-09-07T11:12:00.8562826Z triton_mm_689 0.0105 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:12:00.8564316Z triton_mm_693 0.0110 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:12:00.8565817Z triton_mm_680 0.0116 ms 74.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T11:12:00.8567474Z triton_mm_679 0.0123 ms 70.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:12:00.8568964Z triton_mm_684 0.0124 ms 69.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:12:00.8570638Z triton_mm_678 0.0126 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:12:00.8572139Z triton_mm_688 0.0130 ms 66.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:12:00.8573453Z SingleProcess AUTOTUNE benchmarking takes 0.2528 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:12:05.2968289Z pass 2025-09-07T11:12:08.6047278Z /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. 2025-09-07T11:12:08.6048959Z import pynvml # type: ignore[import] 2025-09-07T11:12:11.1548138Z 2025-09-07T11:12:12.9188732Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:12:12.9189305Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:12:12.9190802Z cuda eval soft_actor_critic 2025-09-07T11:12:17.0615376Z pass 2025-09-07T11:12:19.7446465Z /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. 2025-09-07T11:12:19.7448195Z import pynvml # type: ignore[import] 2025-09-07T11:12:22.2274639Z 2025-09-07T11:12:23.6866985Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:12:23.6867407Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:12:23.6931642Z cuda eval speech_transformer 2025-09-07T11:12:30.0797599Z W0907 11:12:30.079000 239869 site-packages/torch/_inductor/utils.py:2298] [7/0_1] DeviceCopy in input program 2025-09-07T11:12:33.7701649Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7702063Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7702379Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7702802Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7703104Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7703426Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7703734Z cudagraph partition due to non gpu ops 2025-09-07T11:12:33.7704031Z cudagraph partition due to DeviceCopy ops 2025-09-07T11:12:33.7966355Z cudagraph partition into 2 partitions 2025-09-07T11:12:46.6395768Z W0907 11:12:46.638000 239869 site-packages/torch/_inductor/utils.py:2298] [13/0_1] DeviceCopy in input program 2025-09-07T11:12:51.9236940Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9237321Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9237637Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9237920Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9238211Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9238489Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9238769Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9239046Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9239323Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9239629Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9239910Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9240203Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9240801Z cudagraph partition due to non gpu ops 2025-09-07T11:12:51.9241117Z cudagraph partition due to DeviceCopy ops 2025-09-07T11:12:51.9669283Z cudagraph partition into 2 partitions 2025-09-07T11:12:54.3277575Z pass 2025-09-07T11:12:57.5306044Z /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. 2025-09-07T11:12:57.5307465Z import pynvml # type: ignore[import] 2025-09-07T11:13:00.2311272Z 2025-09-07T11:13:01.2900575Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:13:01.2900986Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:13:01.2941093Z cuda eval squeezenet1_1 2025-09-07T11:13:12.6236938Z pass 2025-09-07T11:13:14.9418978Z accuracy pass_rate=88.89% 2025-09-07T11:13:14.9431645Z calls_captured gmean=0.00x mean=522.111x 2025-09-07T11:13:14.9435027Z unique_graphs gmean=0.00x mean=1.444x 2025-09-07T11:13:14.9438412Z graph_breaks gmean=0.00x mean=1.111x 2025-09-07T11:13:14.9442001Z unique_graph_breaks gmean=0.00x mean=0.222x 2025-09-07T11:13:14.9445365Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:13:14.9448572Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:13:14.9452424Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:13:14.9453554Z compilation_latency mean=24.471 seconds 2025-09-07T11:13:15.9291725Z + [[ 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* ]] 2025-09-07T11:13:15.9293474Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T11:13:15.9295848Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --quant --backend inductor --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv 2025-09-07T11:13:16.4390039Z /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. 2025-09-07T11:13:16.4392429Z import pynvml # type: ignore[import] 2025-09-07T11:13:18.8892615Z usage: torchbench.py 2025-09-07T11:13:18.8893044Z [-h] 2025-09-07T11:13:18.8893338Z [--filter FILTER] 2025-09-07T11:13:18.8893704Z [--exclude EXCLUDE] 2025-09-07T11:13:18.8894079Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T11:13:18.8894619Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T11:13:18.8895153Z [--partition-id PARTITION_ID] 2025-09-07T11:13:18.8895616Z [--devices DEVICES] 2025-09-07T11:13:18.8896038Z [--device-index DEVICE_INDEX] 2025-09-07T11:13:18.8896461Z [--repeat REPEAT] 2025-09-07T11:13:18.8896829Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T11:13:18.8897265Z [--randomize-input] 2025-09-07T11:13:18.8897586Z [--threads THREADS] 2025-09-07T11:13:18.8897901Z [--nopython] 2025-09-07T11:13:18.8898180Z [--no-skip] 2025-09-07T11:13:18.8898461Z [--prims-nvfuser] 2025-09-07T11:13:18.8898787Z [--dump-raw-metrics] 2025-09-07T11:13:18.8899128Z [--log-operator-inputs] 2025-09-07T11:13:18.8899472Z [--channels-last] 2025-09-07T11:13:18.8899793Z [--batch-size BATCH_SIZE] 2025-09-07T11:13:18.8900150Z [--iterations ITERATIONS] 2025-09-07T11:13:18.8900992Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T11:13:18.8901376Z [--cosine] 2025-09-07T11:13:18.8901642Z [--freezing] 2025-09-07T11:13:18.8901960Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T11:13:18.8902330Z [--ci] 2025-09-07T11:13:18.8902589Z [--dashboard] 2025-09-07T11:13:18.8902968Z [--skip-fp64-check] 2025-09-07T11:13:18.8903273Z [--fast] 2025-09-07T11:13:18.8903547Z [--only ONLY] 2025-09-07T11:13:18.8903839Z [--multiprocess] 2025-09-07T11:13:18.8904123Z [--ddp] 2025-09-07T11:13:18.8904378Z [--fsdp] 2025-09-07T11:13:18.8904689Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T11:13:18.8905173Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T11:13:18.8905621Z [--dynamic-shapes] 2025-09-07T11:13:18.8905962Z [--propagate-real-tensors] 2025-09-07T11:13:18.8906331Z [--dynamic-batch-only] 2025-09-07T11:13:18.8906670Z [--specialize-int] 2025-09-07T11:13:18.8906976Z [--use-eval-mode] 2025-09-07T11:13:18.8907298Z [--skip-accuracy-check] 2025-09-07T11:13:18.8907662Z [--generate-aot-autograd-stats] 2025-09-07T11:13:18.8908054Z [--inductor-settings] 2025-09-07T11:13:18.8908379Z [--suppress-errors] 2025-09-07T11:13:18.8908695Z [--output OUTPUT] 2025-09-07T11:13:18.8909048Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T11:13:18.8909918Z [--disable-output] 2025-09-07T11:13:18.8910420Z [--baseline BASELINE] 2025-09-07T11:13:18.8910740Z [--part PART] 2025-09-07T11:13:18.8911051Z [--export-profiler-trace] 2025-09-07T11:13:18.8911454Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T11:13:18.8911876Z [--profile-details] 2025-09-07T11:13:18.8912199Z [--export-perfdoctor] 2025-09-07T11:13:18.8912544Z [--diff-branch DIFF_BRANCH] 2025-09-07T11:13:18.8912890Z [--tag TAG] 2025-09-07T11:13:18.8913156Z [--explain] 2025-09-07T11:13:18.8913415Z [--stats] 2025-09-07T11:13:18.8913902Z [--use-warm-peak-memory] 2025-09-07T11:13:18.8914242Z [--print-memory] 2025-09-07T11:13:18.8914566Z [--print-compilation-time] 2025-09-07T11:13:18.8914940Z [--print-dataframe-summary] 2025-09-07T11:13:18.8915314Z [--disable-cudagraphs] 2025-09-07T11:13:18.8915964Z [--disable-split-reductions] 2025-09-07T11:13:18.8916399Z [--disable-persistent-reductions] 2025-09-07T11:13:18.8916836Z [--disable-divisible-by-16] 2025-09-07T11:13:18.8917305Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T11:13:18.8917780Z [--print-graph-breaks] 2025-09-07T11:13:18.8918152Z [--log-graph-breaks] 2025-09-07T11:13:18.8918497Z [--trace-on-xla] 2025-09-07T11:13:18.8918842Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T11:13:18.8919243Z [--collect-outputs] 2025-09-07T11:13:18.8919628Z [--enable-activation-checkpointing] 2025-09-07T11:13:18.8920030Z [--timing] 2025-09-07T11:13:18.8920524Z [--progress] 2025-09-07T11:13:18.8920853Z [--timeout TIMEOUT] 2025-09-07T11:13:18.8921310Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T11:13:18.8921842Z [--no-translation-validation] 2025-09-07T11:13:18.8922237Z [--minify] 2025-09-07T11:13:18.8922560Z [--compiled-autograd] 2025-09-07T11:13:18.8922936Z [--profile_dynamo_cache_lookup] 2025-09-07T11:13:18.8923347Z [--snapshot-memory] 2025-09-07T11:13:18.8923712Z [--retain-output] 2025-09-07T11:13:18.8924062Z [--caching-precompile] 2025-09-07T11:13:18.8924504Z [--cold-start-latency | --warm-start-latency] 2025-09-07T11:13:18.8924945Z [--nnc] 2025-09-07T11:13:18.8925280Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T11:13:18.8925731Z [--amp-dtype {bfloat16,float16}] 2025-09-07T11:13:18.8926141Z [--verbose | --quiet] 2025-09-07T11:13:18.8930848Z [--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] 2025-09-07T11:13:18.8935485Z (--accuracy | --performance | --tolerance) 2025-09-07T11:13:18.8935950Z (--training | --inference) 2025-09-07T11:13:18.8936495Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T11:13:19.4884603Z + true 2025-09-07T11:13:19.4885693Z + cp /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv 2025-09-07T11:13:19.4908513Z + for target in "${targets[@]}" 2025-09-07T11:13:19.4908790Z + target_flag=('--performance') 2025-09-07T11:13:19.4909308Z + local target_flag 2025-09-07T11:13:19.4909526Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T11:13:19.4909804Z + target_flag+=(--cold-start-latency) 2025-09-07T11:13:19.4911202Z + [[ 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* ]] 2025-09-07T11:13:19.4913147Z + [[ 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* ]] 2025-09-07T11:13:19.4915756Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 7 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv 2025-09-07T11:13:20.0052832Z /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. 2025-09-07T11:13:20.0053804Z import pynvml # type: ignore[import] 2025-09-07T11:13:23.8676066Z /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. 2025-09-07T11:13:23.8678540Z import pynvml # type: ignore[import] 2025-09-07T11:13:26.4653216Z 2025-09-07T11:13:27.9421093Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:13:27.9421480Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:13:27.9469457Z cuda eval resnet50 2025-09-07T11:13:37.9549776Z 2025-09-07T11:13:38.0617529Z running benchmark: 0% 0/30 [00:00 2025-09-07T11:27:51.6950954Z torchbench_main() 2025-09-07T11:27:51.6951493Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T11:27:51.6952089Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T11:27:51.6952617Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T11:27:51.6954457Z process_entry(0, runner, original_dir, args) 2025-09-07T11:27:51.6955038Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T11:27:51.6957423Z result = run(runner, args, original_dir) 2025-09-07T11:27:51.6957932Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4251, in run 2025-09-07T11:27:51.6961323Z assert marked, f"nothing in example_inputs had a dim with {batch_size}" 2025-09-07T11:27:51.6961861Z AssertionError: nothing in example_inputs had a dim with 32 2025-09-07T11:27:55.3277671Z Run failed with return code: 1 2025-09-07T11:27:55.3278008Z Output: None 2025-09-07T11:27:55.3278223Z Error: None 2025-09-07T11:27:55.8764094Z /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. 2025-09-07T11:27:55.8765978Z import pynvml # type: ignore[import] 2025-09-07T11:27:58.3804520Z 2025-09-07T11:27:59.5037137Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:27:59.5037477Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:27:59.5094937Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:28:11.9209848Z 2025-09-07T11:28:12.0225124Z running benchmark: 0% 0/30 [00:00> $GITHUB_ENV 2025-09-07T12:02:57.3942875Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-09-07T12:02:57.3957615Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:02:57.3957906Z env: 2025-09-07T12:02:57.3958078Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:02:57.3958329Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:02:57.3958663Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:02:57.3959098Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:02:57.3959443Z ##[endgroup] 2025-09-07T12:02:57.3992368Z + [[ -n '' ]] 2025-09-07T12:02:57.3992652Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T12:02:57.6703527Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T12:02:58.3915630Z Collecting boto3==1.35.33 2025-09-07T12:02:58.4500122Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-09-07T12:02:58.4857835Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 4.1 MB/s eta 0:00:00 2025-09-07T12:02:58.6331073Z Collecting psutil==7.0.0 2025-09-07T12:02:58.6439072Z 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) 2025-09-07T12:02:58.6851631Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 6.9 MB/s eta 0:00:00 2025-09-07T12:02:58.7061235Z Collecting pynvml==12.0.0 2025-09-07T12:02:58.7177412Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-09-07T12:02:58.7586814Z Collecting s3transfer<0.11.0,>=0.10.0 2025-09-07T12:02:58.7687695Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-09-07T12:02:58.7853211Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 5.2 MB/s eta 0:00:00 2025-09-07T12:02:58.8057278Z Collecting jmespath<2.0.0,>=0.7.1 2025-09-07T12:02:58.8159559Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-09-07T12:02:59.4985301Z Collecting botocore<1.36.0,>=1.35.33 2025-09-07T12:02:59.5094405Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-09-07T12:02:59.9337298Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 41.1 MB/s eta 0:00:00 2025-09-07T12:02:59.9982954Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-09-07T12:03:00.0100378Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-09-07T12:03:00.0194960Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 4.8 MB/s eta 0:00:00 2025-09-07T12:03:00.0253927Z 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) 2025-09-07T12:03:00.0265257Z 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) 2025-09-07T12:03:00.2660397Z Installing collected packages: nvidia-ml-py, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-09-07T12:03:00.2661158Z Attempting uninstall: nvidia-ml-py 2025-09-07T12:03:00.2666093Z Found existing installation: nvidia-ml-py 11.525.84 2025-09-07T12:03:00.2701838Z Uninstalling nvidia-ml-py-11.525.84: 2025-09-07T12:03:00.2727651Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-09-07T12:03:00.3447411Z Attempting uninstall: psutil 2025-09-07T12:03:00.3453831Z Found existing installation: psutil 5.9.8 2025-09-07T12:03:00.3613870Z Uninstalling psutil-5.9.8: 2025-09-07T12:03:00.3623040Z Successfully uninstalled psutil-5.9.8 2025-09-07T12:03:01.1182112Z 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 2025-09-07T12:03:01.2289742Z + DEVICE_NAME= 2025-09-07T12:03:01.2290028Z + DEVICE_TYPE= 2025-09-07T12:03:01.2290473Z + command -v nvidia-smi 2025-09-07T12:03:01.2296179Z + python3 -mpip install torch==2.7.1 2025-09-07T12:03:01.2296582Z /usr/bin/nvidia-smi 2025-09-07T12:03:01.5024167Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T12:03:01.7251025Z Collecting torch==2.7.1 2025-09-07T12:03:01.7799246Z Downloading torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) 2025-09-07T12:03:14.6281159Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 1.1 MB/s eta 0:00:00 2025-09-07T12:03:15.5035774Z Collecting nvidia-cusparselt-cu12==0.6.3 2025-09-07T12:03:15.5151390Z Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) 2025-09-07T12:03:16.9286759Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 13.4 MB/s eta 0:00:00 2025-09-07T12:03:17.1140013Z Collecting filelock 2025-09-07T12:03:17.1244003Z Downloading filelock-3.19.1-py3-none-any.whl (15 kB) 2025-09-07T12:03:17.1538978Z Collecting nvidia-cufft-cu12==11.3.0.4 2025-09-07T12:03:17.1641812Z Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) 2025-09-07T12:03:19.2118964Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 8.5 MB/s eta 0:00:00 2025-09-07T12:03:19.4239373Z Collecting nvidia-cuda-nvrtc-cu12==12.6.77 2025-09-07T12:03:19.4343153Z Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) 2025-09-07T12:03:19.6046631Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 93.5 MB/s eta 0:00:00 2025-09-07T12:03:19.6525819Z Collecting nvidia-cusolver-cu12==11.7.1.2 2025-09-07T12:03:19.6641697Z Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) 2025-09-07T12:03:21.0712843Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 13.4 MB/s eta 0:00:00 2025-09-07T12:03:21.2416717Z Collecting nvidia-cuda-runtime-cu12==12.6.77 2025-09-07T12:03:21.2523307Z Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) 2025-09-07T12:03:21.2656706Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 KB 79.2 MB/s eta 0:00:00 2025-09-07T12:03:21.2684550Z Requirement already satisfied: typing-extensions>=4.10.0 in /home/henry/.local/lib/python3.10/site-packages (from torch==2.7.1) (4.15.0) 2025-09-07T12:03:21.2895733Z Collecting nvidia-nccl-cu12==2.26.2 2025-09-07T12:03:21.2996875Z Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) 2025-09-07T12:03:23.4645094Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 7.8 MB/s eta 0:00:00 2025-09-07T12:03:23.6864939Z Collecting sympy>=1.13.3 2025-09-07T12:03:23.6967124Z Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB) 2025-09-07T12:03:23.7468532Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 131.3 MB/s eta 0:00:00 2025-09-07T12:03:23.7868498Z Collecting nvidia-nvjitlink-cu12==12.6.85 2025-09-07T12:03:23.7969900Z Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) 2025-09-07T12:03:23.9333877Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 110.3 MB/s eta 0:00:00 2025-09-07T12:03:23.9814732Z Collecting nvidia-cudnn-cu12==9.5.1.17 2025-09-07T12:03:23.9919903Z Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) 2025-09-07T12:03:31.7914429Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.9 MB/s eta 0:00:00 2025-09-07T12:03:32.3479187Z Collecting jinja2 2025-09-07T12:03:32.3582146Z Downloading jinja2-3.1.6-py3-none-any.whl (134 kB) 2025-09-07T12:03:32.3702306Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.9/134.9 KB 12.5 MB/s eta 0:00:00 2025-09-07T12:03:32.3958312Z Collecting nvidia-cublas-cu12==12.6.4.1 2025-09-07T12:03:32.4063947Z Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) 2025-09-07T12:03:40.7744121Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 1.5 MB/s eta 0:00:00 2025-09-07T12:03:41.4729091Z Collecting nvidia-curand-cu12==10.3.7.77 2025-09-07T12:03:41.4834393Z Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) 2025-09-07T12:03:43.1391862Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 7.1 MB/s eta 0:00:00 2025-09-07T12:03:43.3784580Z Collecting nvidia-cuda-cupti-cu12==12.6.80 2025-09-07T12:03:43.3887617Z Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) 2025-09-07T12:03:43.8622289Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 18.9 MB/s eta 0:00:00 2025-09-07T12:03:44.2386440Z Collecting nvidia-nvtx-cu12==12.6.77 2025-09-07T12:03:44.2494585Z Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) 2025-09-07T12:03:44.5176539Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.3/89.3 KB 297.0 kB/s eta 0:00:00 2025-09-07T12:03:44.5446852Z Collecting nvidia-cusparse-cu12==12.5.4.2 2025-09-07T12:03:44.5551813Z Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) 2025-09-07T12:03:46.8723887Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 7.2 MB/s eta 0:00:00 2025-09-07T12:03:47.1077954Z Collecting triton==3.3.1 2025-09-07T12:03:47.1202284Z Downloading triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) 2025-09-07T12:03:48.6073304Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 13.2 MB/s eta 0:00:00 2025-09-07T12:03:48.8187010Z Collecting fsspec 2025-09-07T12:03:48.8293659Z Downloading fsspec-2025.9.0-py3-none-any.whl (199 kB) 2025-09-07T12:03:48.8399716Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.3/199.3 KB 22.3 MB/s eta 0:00:00 2025-09-07T12:03:48.8578759Z Collecting nvidia-cufile-cu12==1.11.1.6 2025-09-07T12:03:48.8681700Z Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) 2025-09-07T12:03:48.8838008Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 85.4 MB/s eta 0:00:00 2025-09-07T12:03:48.9254588Z Collecting networkx 2025-09-07T12:03:48.9357359Z Downloading networkx-3.4.2-py3-none-any.whl (1.7 MB) 2025-09-07T12:03:48.9537897Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 104.3 MB/s eta 0:00:00 2025-09-07T12:03:48.9833022Z 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) 2025-09-07T12:03:49.0091532Z Collecting mpmath<1.4,>=1.1.0 2025-09-07T12:03:49.0192992Z Downloading mpmath-1.3.0-py3-none-any.whl (536 kB) 2025-09-07T12:03:49.0306026Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 55.2 MB/s eta 0:00:00 2025-09-07T12:03:49.2114130Z Collecting MarkupSafe>=2.0 2025-09-07T12:03:49.2216791Z Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) 2025-09-07T12:03:49.5512608Z 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 2025-09-07T12:03:55.0751608Z WARNING: The scripts proton and proton-viewer are installed in '/home/henry/.local/bin' which is not on PATH. 2025-09-07T12:03:55.0752524Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T12:03:59.4084683Z WARNING: The script isympy is installed in '/home/henry/.local/bin' which is not on PATH. 2025-09-07T12:03:59.4085509Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T12:04:32.5105338Z WARNING: The scripts torchfrtrace and torchrun are installed in '/home/henry/.local/bin' which is not on PATH. 2025-09-07T12:04:32.5106232Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T12:04:33.3543309Z 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 2025-09-07T12:04:34.0749226Z + echo DEVICE_NAME= 2025-09-07T12:04:34.0749532Z + echo DEVICE_TYPE= 2025-09-07T12:04:34.1056299Z ##[group]Run set -eux 2025-09-07T12:04:34.1056686Z set -eux 2025-09-07T12:04:34.1056869Z  2025-09-07T12:04:34.1057064Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-09-07T12:04:34.1057355Z  echo "Missing github-token input" 2025-09-07T12:04:34.1057619Z  exit 1 2025-09-07T12:04:34.1057793Z fi 2025-09-07T12:04:34.1072412Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:34.1072708Z env: 2025-09-07T12:04:34.1072872Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:34.1073131Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:34.1073467Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:34.1073912Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:34.1074302Z DEVICE_NAME: 2025-09-07T12:04:34.1074474Z DEVICE_TYPE: 2025-09-07T12:04:34.1074848Z GITHUB_TOKEN: *** 2025-09-07T12:04:34.1075036Z ##[endgroup] 2025-09-07T12:04:34.1463243Z + [[ -z *** ]] 2025-09-07T12:04:34.1869788Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-09-07T12:04:34.1870162Z with: 2025-09-07T12:04:34.1870941Z github-token: *** 2025-09-07T12:04:34.1871142Z env: 2025-09-07T12:04:34.1871317Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:34.1871601Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:34.1871977Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:34.1872446Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:34.1872848Z DEVICE_NAME: 2025-09-07T12:04:34.1873027Z DEVICE_TYPE: 2025-09-07T12:04:34.1873400Z ##[endgroup] 2025-09-07T12:04:34.3616507Z ##[group]Run set -eux 2025-09-07T12:04:34.3616750Z set -eux 2025-09-07T12:04:34.3616933Z  2025-09-07T12:04:34.3617318Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T12:04:34.3632316Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:34.3632629Z env: 2025-09-07T12:04:34.3632792Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:34.3633039Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:34.3633373Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:34.3633796Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:34.3634151Z DEVICE_NAME: 2025-09-07T12:04:34.3634330Z DEVICE_TYPE: 2025-09-07T12:04:34.3634627Z GITHUB_TOKEN: *** 2025-09-07T12:04:34.3634806Z ##[endgroup] 2025-09-07T12:04:34.4796730Z + python3 /home/henry/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525296438 i-0b7d0f7dc0527ca9b-1008 2025-09-07T12:04:35.3248830Z setting job-id=49775781863 2025-09-07T12:04:35.3249338Z setting job-name=test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T12:04:35.3615409Z ##[group]Run set -eux 2025-09-07T12:04:35.3615662Z set -eux 2025-09-07T12:04:35.3615849Z  2025-09-07T12:04:35.3616019Z if [[ -n "" ]]; then 2025-09-07T12:04:35.3616234Z  source "" 2025-09-07T12:04:35.3616438Z fi 2025-09-07T12:04:35.3616605Z  2025-09-07T12:04:35.3616919Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-09-07T12:04:35.3617337Z  --schema-version "${SCHEMA_VERSION}" \ 2025-09-07T12:04:35.3617621Z  --repo "${REPO}" \ 2025-09-07T12:04:35.3617856Z  --head-branch "${HEAD_BRANCH}" \ 2025-09-07T12:04:35.3618128Z  --head-sha "${HEAD_SHA}" \ 2025-09-07T12:04:35.3618685Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-09-07T12:04:35.3618982Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-09-07T12:04:35.3619243Z  --job-id "${JOB_ID}" \ 2025-09-07T12:04:35.3619479Z  --job-name "${JOB_NAME}" 2025-09-07T12:04:35.3633718Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:35.3634140Z env: 2025-09-07T12:04:35.3634303Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:35.3634549Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:35.3634890Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:35.3635312Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:35.3635664Z DEVICE_NAME: 2025-09-07T12:04:35.3635831Z DEVICE_TYPE: 2025-09-07T12:04:35.3635999Z SCHEMA_VERSION: v3 2025-09-07T12:04:35.3636178Z REPO: pytorch/pytorch 2025-09-07T12:04:35.3636379Z HEAD_BRANCH: refs/heads/main 2025-09-07T12:04:35.3636613Z HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T12:04:35.3636861Z WORKFLOW_RUN_ID: 17525296438 2025-09-07T12:04:35.3637042Z RUN_ATTEMPT: 1 2025-09-07T12:04:35.3637206Z JOB_ID: 49775781863 2025-09-07T12:04:35.3637513Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T12:04:35.3637854Z ##[endgroup] 2025-09-07T12:04:35.4108881Z + [[ -n '' ]] 2025-09-07T12:04:35.4110558Z + python3 /home/henry/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha 93fb23d6fae7c4e82c4239a1033e522088742634 --workflow-id 17525296438 --run-attempt 1 --job-id 49775781863 --job-name 'test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)' 2025-09-07T12:04:35.4557527Z ##[group]Run set -eux 2025-09-07T12:04:35.4557930Z set -eux 2025-09-07T12:04:35.4558122Z  2025-09-07T12:04:35.4558317Z if [[ -n "" ]]; then 2025-09-07T12:04:35.4558554Z  source "" 2025-09-07T12:04:35.4558763Z fi 2025-09-07T12:04:35.4558939Z  2025-09-07T12:04:35.4559290Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-09-07T12:04:35.4572963Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:35.4573269Z env: 2025-09-07T12:04:35.4573431Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:35.4573680Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:35.4574005Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:35.4574424Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:35.4574784Z DEVICE_NAME: 2025-09-07T12:04:35.4574953Z DEVICE_TYPE: 2025-09-07T12:04:35.4575116Z ##[endgroup] 2025-09-07T12:04:35.5038346Z + [[ -n '' ]] 2025-09-07T12:04:35.5039016Z + python3 /home/henry/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-09-07T12:04:36.4982481Z /home/henry/.local/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:276: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:81.) 2025-09-07T12:04:36.4984382Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-09-07T12:04:38.1896481Z ##[group]Run set -eux 2025-09-07T12:04:38.1896711Z set -eux 2025-09-07T12:04:38.1896894Z  2025-09-07T12:04:38.1897094Z # TODO (huydhn): Implement this part 2025-09-07T12:04:38.1897414Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-09-07T12:04:38.1912043Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:38.1912323Z env: 2025-09-07T12:04:38.1912492Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:38.1912742Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:38.1913322Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:38.1913749Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:38.1914109Z DEVICE_NAME: 2025-09-07T12:04:38.1914288Z DEVICE_TYPE: 2025-09-07T12:04:38.1914565Z ##[endgroup] 2025-09-07T12:04:38.3998591Z + echo 'dependencies={}' 2025-09-07T12:04:38.4556714Z ##[group]Run set -eux 2025-09-07T12:04:38.4556974Z set -eux 2025-09-07T12:04:38.4557175Z  2025-09-07T12:04:38.4557366Z if [[ -n "" ]]; then 2025-09-07T12:04:38.4557603Z  source "" 2025-09-07T12:04:38.4557812Z fi 2025-09-07T12:04:38.4557988Z  2025-09-07T12:04:38.4558218Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-09-07T12:04:38.4558605Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-09-07T12:04:38.4559044Z  # We don't want the job to fail if the directory doesn't exist 2025-09-07T12:04:38.4559394Z  exit 0 2025-09-07T12:04:38.4559582Z fi 2025-09-07T12:04:38.4559766Z  2025-09-07T12:04:38.4559973Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-09-07T12:04:38.4560549Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T12:04:38.4561037Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T12:04:38.4561412Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T12:04:38.4561717Z  --runners "${RUNNER_INFO}" \ 2025-09-07T12:04:38.4562016Z  --dependencies "${DEPENDENCIES}" \ 2025-09-07T12:04:38.4562292Z  --dry-run 2025-09-07T12:04:38.4562503Z else 2025-09-07T12:04:38.4562828Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T12:04:38.4563298Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T12:04:38.4563820Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T12:04:38.4564138Z  --runners "${RUNNER_INFO}" \ 2025-09-07T12:04:38.4564432Z  --dependencies "${DEPENDENCIES}" 2025-09-07T12:04:38.4564708Z fi 2025-09-07T12:04:38.4578998Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:38.4579284Z env: 2025-09-07T12:04:38.4579454Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:38.4579709Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:38.4580058Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:38.4580617Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:38.4580967Z DEVICE_NAME: 2025-09-07T12:04:38.4581135Z DEVICE_TYPE: 2025-09-07T12:04:38.4581323Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-09-07T12:04:38.4581552Z DRY_RUN: false 2025-09-07T12:04:38.4582478Z BENCHMARK_METADATA: {"timestamp": 1757246675, "schema_version": "v3", "name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525296438, "run_attempt": 1, "job_id": 49775781863} 2025-09-07T12:04:38.4583910Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 192, "avail_mem_in_gb": 1999, "extra_info": {"hostname": "304d8fe70f44"}, "name": "cuda", "type": "NVIDIA H100 80GB HBM3", "gpu_count": 1, "avail_gpu_mem_in_gb": 79}] 2025-09-07T12:04:38.4584470Z DEPENDENCIES: {} 2025-09-07T12:04:38.4584648Z ##[endgroup] 2025-09-07T12:04:38.5062735Z + [[ -n '' ]] 2025-09-07T12:04:38.5063098Z + [[ ! -d test/test-reports ]] 2025-09-07T12:04:38.5063371Z + [[ false == \t\r\u\e ]] 2025-09-07T12:04:38.5066036Z + python3 /home/henry/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757246675, "schema_version": "v3", "name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525296438, "run_attempt": 1, "job_id": 49775781863}' --runners '[{"cpu_info": "x86_64", "cpu_count": 192, "avail_mem_in_gb": 1999, "extra_info": {"hostname": "304d8fe70f44"}, "name": "cuda", "type": "NVIDIA H100 80GB HBM3", "gpu_count": 1, "avail_gpu_mem_in_gb": 79}]' --dependencies '{}' 2025-09-07T12:04:38.6280869Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:38.6678429Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role 2025-09-07T12:04:38.9152146Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:39.0542793Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T12:04:39.1904566Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:39.3287899Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:39.4764484Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:39.6719635Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:39.8119063Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:39.9495771Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T12:04:40.2162176Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:40.3497733Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T12:04:40.4837838Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T12:04:40.5909536Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T12:04:40.7163348Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T12:04:40.8378398Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:40.9992929Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:41.1509414Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:41.3045607Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:41.4788514Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:41.6498602Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T12:04:41.7919748Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:41.9762082Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:42.1116466Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:42.2622127Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:42.3893799Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:42.5240396Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:42.6904467Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:42.8250754Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:42.9659218Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:43.1448101Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:43.2911833Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:43.4543966Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:43.5970645Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T12:04:43.7521850Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:43.8876073Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:44.1383702Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T12:04:44.2738671Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T12:04:44.4399151Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T12:04:44.6020883Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T12:04:44.7659670Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781863/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T12:04:45.0419477Z ##[group]Run cat test/**/*_toprint.log || true 2025-09-07T12:04:45.0419865Z cat test/**/*_toprint.log || true 2025-09-07T12:04:45.0434563Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:45.0434844Z env: 2025-09-07T12:04:45.0435007Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:45.0435263Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:45.0435607Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:45.0446944Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:45.0447351Z DEVICE_NAME: 2025-09-07T12:04:45.0447526Z DEVICE_TYPE: 2025-09-07T12:04:45.0447696Z ##[endgroup] 2025-09-07T12:04:45.0953486Z cat: 'test/**/*_toprint.log': No such file or directory 2025-09-07T12:04:45.1353092Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-09-07T12:04:45.1353566Z kill "$MONITOR_SCRIPT_PID" 2025-09-07T12:04:45.1370127Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:45.1370818Z env: 2025-09-07T12:04:45.1371091Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:45.1371501Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:45.1372031Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:45.1372578Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:45.1372945Z DEVICE_NAME: 2025-09-07T12:04:45.1373112Z DEVICE_TYPE: 2025-09-07T12:04:45.1373281Z MONITOR_SCRIPT_PID: 7913 2025-09-07T12:04:45.1373692Z ##[endgroup] 2025-09-07T12:04:45.1925263Z Prepare all required actions 2025-09-07T12:04:45.1925659Z Getting action download info 2025-09-07T12:04:45.4431466Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T12:04:46.0827462Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-09-07T12:04:47.6573355Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-09-07T12:04:47.6573642Z with: 2025-09-07T12:04:47.6573952Z file-suffix: test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T12:04:47.6574337Z s3-bucket: gha-artifacts 2025-09-07T12:04:47.6574542Z env: 2025-09-07T12:04:47.6574706Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:47.6574966Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:47.6575309Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:47.6575811Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:47.6576189Z DEVICE_NAME: 2025-09-07T12:04:47.6576363Z DEVICE_TYPE: 2025-09-07T12:04:47.6576548Z ##[endgroup] 2025-09-07T12:04:47.6834119Z ##[group]Run # Remove any previous test jsons if they exist 2025-09-07T12:04:47.6834576Z # Remove any previous test jsons if they exist 2025-09-07T12:04:47.6834954Z rm -f test-jsons-*.zip 2025-09-07T12:04:47.6835355Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-09-07T12:04:47.6850533Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:47.6850846Z env: 2025-09-07T12:04:47.6851024Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:47.6851321Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:47.6851669Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:47.6852107Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:47.6852499Z DEVICE_NAME: 2025-09-07T12:04:47.6852673Z DEVICE_TYPE: 2025-09-07T12:04:47.6852976Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T12:04:47.6853322Z ##[endgroup] 2025-09-07T12:04:47.7458474Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.7472487Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T12:04:47.7483077Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7495447Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7507995Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7568524Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.7609376Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.7622325Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.7632988Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7651184Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.7663953Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.7673318Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7681761Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7694782Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.7763716Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.7790747Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 98%) 2025-09-07T12:04:47.7843062Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.7899208Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.7919739Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.7932689Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.7946675Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T12:04:47.7958963Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.7979551Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8027735Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.8041720Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T12:04:47.8091572Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.8141477Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.8162050Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8222550Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.8240184Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8298984Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.8319502Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8334800Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8343603Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.8357558Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T12:04:47.8372889Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8381689Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json (deflated 98%) 2025-09-07T12:04:47.8395779Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T12:04:47.8414566Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 98%) 2025-09-07T12:04:47.8461951Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T12:04:47.8681446Z ##[group]Run # Remove any previous test reports if they exist 2025-09-07T12:04:47.8681887Z # Remove any previous test reports if they exist 2025-09-07T12:04:47.8682229Z rm -f test-reports-*.zip 2025-09-07T12:04:47.8682647Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-09-07T12:04:47.8697275Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:47.8697566Z env: 2025-09-07T12:04:47.8697737Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:47.8697994Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:47.8698350Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:47.8698783Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:47.8699138Z DEVICE_NAME: 2025-09-07T12:04:47.8699307Z DEVICE_TYPE: 2025-09-07T12:04:47.8699606Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T12:04:47.8699958Z ##[endgroup] 2025-09-07T12:04:47.9192345Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9193402Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9194349Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9195241Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9196250Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9197277Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9198137Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9199261Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 48%) 2025-09-07T12:04:47.9200166Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9201312Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T12:04:47.9202236Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9203227Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T12:04:47.9204188Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9204991Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 57%) 2025-09-07T12:04:47.9205769Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9206638Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 53%) 2025-09-07T12:04:47.9207471Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T12:04:47.9208496Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9209174Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9209820Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9210683Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T12:04:47.9211444Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9212207Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 48%) 2025-09-07T12:04:47.9212977Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9213677Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9214328Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9215031Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T12:04:47.9215752Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T12:04:47.9216439Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 48%) 2025-09-07T12:04:47.9217171Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 48%) 2025-09-07T12:04:47.9217880Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 50%) 2025-09-07T12:04:47.9218591Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T12:04:47.9219278Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9219979Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 50%) 2025-09-07T12:04:47.9220740Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv (deflated 49%) 2025-09-07T12:04:47.9221457Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 50%) 2025-09-07T12:04:47.9222267Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 54%) 2025-09-07T12:04:47.9223170Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T12:04:47.9224123Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 50%) 2025-09-07T12:04:47.9224820Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9225540Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T12:04:47.9226229Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T12:04:47.9581050Z ##[group]Run # Remove any previous usage logs if they exist 2025-09-07T12:04:47.9581438Z # Remove any previous usage logs if they exist 2025-09-07T12:04:47.9581751Z rm -f logs-*.zip 2025-09-07T12:04:47.9582254Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true 2025-09-07T12:04:47.9582677Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true 2025-09-07T12:04:47.9595733Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:47.9596029Z env: 2025-09-07T12:04:47.9596207Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:47.9596460Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:47.9596799Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:47.9597230Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:47.9597589Z DEVICE_NAME: 2025-09-07T12:04:47.9597765Z DEVICE_TYPE: 2025-09-07T12:04:47.9598073Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T12:04:47.9598421Z ##[endgroup] 2025-09-07T12:04:48.0175310Z adding: usage_log.txt (deflated 90%) 2025-09-07T12:04:48.0191745Z 2025-09-07T12:04:48.0192708Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip) 2025-09-07T12:04:48.0994996Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-09-07T12:04:48.0995482Z # Remove any previous debugging artifacts if they exist 2025-09-07T12:04:48.0995860Z rm -f debug-*.zip 2025-09-07T12:04:48.0996130Z if [ -d 'test/debug' ]; then 2025-09-07T12:04:48.0996468Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-09-07T12:04:48.0996799Z fi 2025-09-07T12:04:48.1009865Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:48.1010156Z env: 2025-09-07T12:04:48.1010488Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:48.1010753Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:48.1011098Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:48.1011550Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:48.1011919Z DEVICE_NAME: 2025-09-07T12:04:48.1012086Z DEVICE_TYPE: 2025-09-07T12:04:48.1012390Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863 2025-09-07T12:04:48.1012739Z ##[endgroup] 2025-09-07T12:04:48.1896779Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T12:04:48.1897163Z with: 2025-09-07T12:04:48.1897341Z s3-bucket: gha-artifacts 2025-09-07T12:04:48.1897605Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:48.1897881Z retention-days: 14 2025-09-07T12:04:48.1898064Z if-no-files-found: warn 2025-09-07T12:04:48.1898268Z path: test-jsons-*.zip 2025-09-07T12:04:48.1898460Z name: artifact 2025-09-07T12:04:48.1898630Z region: us-east-1 2025-09-07T12:04:48.1898795Z env: 2025-09-07T12:04:48.1898953Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:48.1899207Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:48.1899551Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:48.1899995Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:48.1900547Z DEVICE_NAME: 2025-09-07T12:04:48.1900718Z DEVICE_TYPE: 2025-09-07T12:04:48.1900885Z ##[endgroup] 2025-09-07T12:04:48.4912313Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T12:04:48.4912761Z With the provided path, there will be 1 file uploaded 2025-09-07T12:04:48.4913155Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:48.4921198Z Starting upload of test-jsons-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:04:48.6855394Z Finished upload of test-jsons-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:04:48.7380386Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T12:04:48.7380725Z with: 2025-09-07T12:04:48.7380954Z s3-bucket: gha-artifacts 2025-09-07T12:04:48.7381265Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:48.7382019Z retention-days: 14 2025-09-07T12:04:48.7382294Z if-no-files-found: error 2025-09-07T12:04:48.7382568Z path: test-reports-*.zip 2025-09-07T12:04:48.7382947Z name: artifact 2025-09-07T12:04:48.7383167Z region: us-east-1 2025-09-07T12:04:48.7383412Z env: 2025-09-07T12:04:48.7383645Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:48.7383997Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:48.7384419Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:48.7384956Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:48.7385407Z DEVICE_NAME: 2025-09-07T12:04:48.7385637Z DEVICE_TYPE: 2025-09-07T12:04:48.7385861Z ##[endgroup] 2025-09-07T12:04:49.0353350Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T12:04:49.0353769Z With the provided path, there will be 1 file uploaded 2025-09-07T12:04:49.0354149Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:49.0361942Z Starting upload of test-reports-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:04:49.2126058Z Finished upload of test-reports-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:04:49.2565078Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T12:04:49.2565519Z with: 2025-09-07T12:04:49.2565791Z s3-bucket: gha-artifacts 2025-09-07T12:04:49.2566189Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:49.2566614Z retention-days: 14 2025-09-07T12:04:49.2566928Z if-no-files-found: ignore 2025-09-07T12:04:49.2567270Z path: logs-*.zip 2025-09-07T12:04:49.2567555Z name: artifact 2025-09-07T12:04:49.2567832Z region: us-east-1 2025-09-07T12:04:49.2568114Z env: 2025-09-07T12:04:49.2568370Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:49.2568787Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:49.2569350Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:49.2570054Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:49.2570824Z DEVICE_NAME: 2025-09-07T12:04:49.2571105Z DEVICE_TYPE: 2025-09-07T12:04:49.2571375Z ##[endgroup] 2025-09-07T12:04:49.5604763Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T12:04:49.5605368Z With the provided path, there will be 1 file uploaded 2025-09-07T12:04:49.5605802Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:49.5613791Z Starting upload of logs-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:04:49.7609728Z Finished upload of logs-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:04:49.8176406Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T12:04:49.8176733Z with: 2025-09-07T12:04:49.8176941Z s3-bucket: gha-artifacts 2025-09-07T12:04:49.8177299Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T12:04:49.8177731Z retention-days: 14 2025-09-07T12:04:49.8177970Z if-no-files-found: ignore 2025-09-07T12:04:49.8178234Z path: debug-*.zip 2025-09-07T12:04:49.8178448Z name: artifact 2025-09-07T12:04:49.8178660Z region: us-east-1 2025-09-07T12:04:49.8178868Z env: 2025-09-07T12:04:49.8179057Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:49.8179379Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:49.8179805Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:49.8180515Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:49.8180994Z DEVICE_NAME: 2025-09-07T12:04:49.8181203Z DEVICE_TYPE: 2025-09-07T12:04:49.8181409Z ##[endgroup] 2025-09-07T12:04:50.1192559Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-09-07T12:04:50.1492050Z ##[group]Run # shellcheck disable=SC2156 2025-09-07T12:04:50.1492529Z # shellcheck disable=SC2156 2025-09-07T12:04:50.1492980Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-09-07T12:04:50.1507419Z shell: /usr/bin/bash -e {0} 2025-09-07T12:04:50.1507628Z env: 2025-09-07T12:04:50.1507788Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:50.1508036Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:50.1508378Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:50.1508818Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:50.1509174Z DEVICE_NAME: 2025-09-07T12:04:50.1509341Z DEVICE_TYPE: 2025-09-07T12:04:50.1509497Z ##[endgroup] 2025-09-07T12:04:50.9636391Z Prepare all required actions 2025-09-07T12:04:50.9636765Z Getting action download info 2025-09-07T12:04:51.1109330Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-09-07T12:04:51.1109607Z with: 2025-09-07T12:04:51.1109779Z job_id: 49775781863 2025-09-07T12:04:51.1110095Z job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T12:04:51.1110667Z workflow_name: inductor-perf-nightly-h100 2025-09-07T12:04:51.1110925Z workflow_run_id: 17525296438 2025-09-07T12:04:51.1111131Z workflow_attempt: 1 2025-09-07T12:04:51.1111327Z env: 2025-09-07T12:04:51.1111498Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:51.1111749Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:51.1112099Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:51.1112519Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:51.1112874Z DEVICE_NAME: 2025-09-07T12:04:51.1113064Z DEVICE_TYPE: 2025-09-07T12:04:51.1113220Z ##[endgroup] 2025-09-07T12:04:51.2550480Z ##[group]Run echo "workflow_id: 17525296438" 2025-09-07T12:04:51.2550830Z echo "workflow_id: 17525296438" 2025-09-07T12:04:51.2551148Z echo "workflow_attempt: 1" 2025-09-07T12:04:51.2551516Z echo "workflow_Name: inductor-perf-nightly-h100" 2025-09-07T12:04:51.2551888Z echo "job_id: 49775781863" 2025-09-07T12:04:51.2552376Z echo "job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)" 2025-09-07T12:04:51.2552878Z echo "artifact_prefix: " 2025-09-07T12:04:51.2553301Z python3 --version 2025-09-07T12:04:51.2568000Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:04:51.2568305Z env: 2025-09-07T12:04:51.2568471Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:51.2568741Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:51.2569094Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:51.2569537Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:51.2569909Z DEVICE_NAME: 2025-09-07T12:04:51.2570083Z DEVICE_TYPE: 2025-09-07T12:04:51.2570408Z ##[endgroup] 2025-09-07T12:04:51.3036413Z workflow_id: 17525296438 2025-09-07T12:04:51.3036678Z workflow_attempt: 1 2025-09-07T12:04:51.3036947Z workflow_Name: inductor-perf-nightly-h100 2025-09-07T12:04:51.3037253Z job_id: 49775781863 2025-09-07T12:04:51.3037657Z job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100) 2025-09-07T12:04:51.3038115Z artifact_prefix: 2025-09-07T12:04:51.3053306Z Python 3.10.12 2025-09-07T12:04:51.3452676Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T12:04:51.3452958Z with: 2025-09-07T12:04:51.3453133Z shell: bash 2025-09-07T12:04:51.3453331Z timeout_minutes: 5 2025-09-07T12:04:51.3453539Z max_attempts: 5 2025-09-07T12:04:51.3453743Z retry_wait_seconds: 30 2025-09-07T12:04:51.3454229Z 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 2025-09-07T12:04:51.3454754Z polling_interval_seconds: 1 2025-09-07T12:04:51.3455000Z warning_on_retry: true 2025-09-07T12:04:51.3455367Z continue_on_error: false 2025-09-07T12:04:51.3455583Z env: 2025-09-07T12:04:51.3455768Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:04:51.3456058Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:04:51.3456445Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:04:51.3456943Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:04:51.3457376Z DEVICE_NAME: 2025-09-07T12:04:51.3457576Z DEVICE_TYPE: 2025-09-07T12:04:51.3457768Z ##[endgroup] 2025-09-07T12:04:51.6864633Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T12:04:52.1356875Z Collecting python-dateutil==2.8.2 2025-09-07T12:04:52.1966684Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-09-07T12:04:52.6234343Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 247.7/247.7 KB 561.8 kB/s eta 0:00:00 2025-09-07T12:04:53.4727116Z Collecting boto3==1.35.42 2025-09-07T12:04:53.4863141Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-09-07T12:04:53.5261108Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.2/139.2 KB 3.5 MB/s eta 0:00:00 2025-09-07T12:04:53.8403534Z Collecting pandas==2.1.3 2025-09-07T12:04:53.8528759Z Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-09-07T12:04:54.7300161Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.3/12.3 MB 12.0 MB/s eta 0:00:00 2025-09-07T12:04:54.7709114Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/henry/.local/lib/python3.10/site-packages (0.6.7) 2025-09-07T12:04:54.7726600Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil==2.8.2) (1.16.0) 2025-09-07T12:04:54.7776689Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/henry/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.35.99) 2025-09-07T12:04:54.7781591Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/henry/.local/lib/python3.10/site-packages (from boto3==1.35.42) (0.10.4) 2025-09-07T12:04:54.7786303Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/henry/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.0.1) 2025-09-07T12:04:55.2738086Z Collecting tzdata>=2022.1 2025-09-07T12:04:55.2856132Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-09-07T12:04:55.6446446Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 347.8/347.8 KB 945.7 kB/s eta 0:00:00 2025-09-07T12:04:56.1536228Z Collecting pytz>=2020.1 2025-09-07T12:04:56.1662936Z Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) 2025-09-07T12:04:56.4708395Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 509.2/509.2 KB 1.7 MB/s eta 0:00:00 2025-09-07T12:04:57.2646108Z Collecting numpy<2,>=1.22.4 2025-09-07T12:04:57.2776187Z Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-09-07T12:04:57.9552063Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 16.2 MB/s eta 0:00:00 2025-09-07T12:04:57.9840813Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/henry/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-09-07T12:04:57.9845739Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/henry/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-09-07T12:04:57.9901397Z 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) 2025-09-07T12:04:58.0012430Z Requirement already satisfied: packaging>=17.0 in /home/henry/.local/lib/python3.10/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-09-07T12:04:58.0110905Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/henry/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-09-07T12:04:58.0119810Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/henry/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0) 2025-09-07T12:04:58.2792076Z Installing collected packages: pytz, tzdata, python-dateutil, numpy, pandas, boto3 2025-09-07T12:05:01.4607467Z WARNING: The script f2py is installed in '/home/henry/.local/bin' which is not on PATH. 2025-09-07T12:05:01.4608389Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T12:05:05.7609346Z Attempting uninstall: boto3 2025-09-07T12:05:05.7615498Z Found existing installation: boto3 1.35.33 2025-09-07T12:05:05.7835381Z Uninstalling boto3-1.35.33: 2025-09-07T12:05:05.7856034Z Successfully uninstalled boto3-1.35.33 2025-09-07T12:05:06.4452072Z 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 2025-09-07T12:05:07.4309884Z Command completed after 1 attempt(s). 2025-09-07T12:05:07.4421746Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T12:05:07.4425243Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T12:05:07.4425896Z  --workflow-run-id "17525296438" \ 2025-09-07T12:05:07.4426412Z  --workflow-name "inductor-perf-nightly-h100" \ 2025-09-07T12:05:07.4426919Z  --workflow-run-attempt "1" \ 2025-09-07T12:05:07.4427333Z  --job-id "49775781863" \ 2025-09-07T12:05:07.4427955Z  --job-name "test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)" \ 2025-09-07T12:05:07.4428613Z  --local-path "" \ 2025-09-07T12:05:07.4428969Z  --artifact-prefix "" 2025-09-07T12:05:07.4447950Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T12:05:07.4448431Z env: 2025-09-07T12:05:07.4448690Z GIT_DEFAULT_BRANCH: main 2025-09-07T12:05:07.4449091Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T12:05:07.4449644Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5234 2025-09-07T12:05:07.4450525Z DOCKER_CONTAINER_ID: 89b2388ff74207c8793f98bca44b92a3752127be21a1a14c25818ccef1760869 2025-09-07T12:05:07.4451138Z DEVICE_NAME: 2025-09-07T12:05:07.4451418Z DEVICE_TYPE: 2025-09-07T12:05:07.4451694Z ##[endgroup] 2025-09-07T12:05:09.4448415Z repo: pytorch/pytorch 2025-09-07T12:05:09.4448810Z Search for test log in s3 bucket: ossci-utilization 2025-09-07T12:05:09.4449737Z Downloading logs-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:05:09.4450841Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf_cuda_h100-8-9-linux.aws.h100_49775781863.zip 2025-09-07T12:05:09.4451465Z Converted Log Model: UtilizationMetadata: 2025-09-07T12:05:09.4452796Z UtilizationMetadata(level='metadata', workflow_id='17525296438', job_id='49775781863', workflow_name='inductor-perf-nightly-h100', job_name='test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757237044, gpu_count=1, cpu_count=192, gpu_type='pynvml', error=None) 2025-09-07T12:05:09.4454221Z [Db Segments] detected pytest cmd: 4, generated segments: 4 2025-09-07T12:05:09.4454532Z [db model] Peek db timeseries 2025-09-07T12:05:09.4454739Z :{ 2025-09-07T12:05:09.4454888Z "created_at": 1757246709, 2025-09-07T12:05:09.4455096Z "type": "utilization", 2025-09-07T12:05:09.4455286Z "tags": [ 2025-09-07T12:05:09.4455448Z "record" 2025-09-07T12:05:09.4455606Z ], 2025-09-07T12:05:09.4455764Z "time_stamp": 1757237044, 2025-09-07T12:05:09.4455977Z "repo": "pytorch/pytorch", 2025-09-07T12:05:09.4456190Z "workflow_id": 17525296438, 2025-09-07T12:05:09.4456394Z "run_attempt": 1, 2025-09-07T12:05:09.4456579Z "job_id": 49775781863, 2025-09-07T12:05:09.4456815Z "workflow_name": "inductor-perf-nightly-h100", 2025-09-07T12:05:09.4457229Z "job_name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 8, 9, linux.aws.h100)", 2025-09-07T12:05:09.4457592Z "json_data": "{}" 2025-09-07T12:05:09.4457768Z } 2025-09-07T12:05:09.4458143Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525296438/1/49775781863/metadata 2025-09-07T12:05:09.4458841Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525296438/1/49775781863/metadata 2025-09-07T12:05:09.4459550Z Writing 640 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525296438/1/49775781863/time_series 2025-09-07T12:05:09.4460400Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525296438/1/49775781863/time_series 2025-09-07T12:05:09.5458753Z Post job cleanup. 2025-09-07T12:05:09.5493038Z Post job cleanup. 2025-09-07T12:05:09.6406958Z [command]/usr/bin/git version 2025-09-07T12:05:09.6444523Z git version 2.50.1 2025-09-07T12:05:09.6484131Z Temporarily overriding HOME='/home/henry/_work/_temp/35d90765-fe06-49b0-8f44-a0c69464752a' before making global git config changes 2025-09-07T12:05:09.6484853Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T12:05:09.6488556Z [command]/usr/bin/git config --global --add safe.directory /home/henry/_work/pytorch/pytorch 2025-09-07T12:05:09.6525859Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T12:05:09.6568131Z [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' || :" 2025-09-07T12:05:09.6841209Z Entering 'android/libs/fbjni' 2025-09-07T12:05:09.6892772Z Entering 'third_party/FP16' 2025-09-07T12:05:09.6940723Z Entering 'third_party/FXdiv' 2025-09-07T12:05:09.6988675Z Entering 'third_party/NNPACK' 2025-09-07T12:05:09.7036942Z Entering 'third_party/NVTX' 2025-09-07T12:05:09.7086603Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T12:05:09.7137109Z Entering 'third_party/XNNPACK' 2025-09-07T12:05:09.7198860Z Entering 'third_party/aiter' 2025-09-07T12:05:09.7247858Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T12:05:09.7306402Z Entering 'third_party/benchmark' 2025-09-07T12:05:09.7355349Z Entering 'third_party/composable_kernel' 2025-09-07T12:05:09.7411710Z Entering 'third_party/cpp-httplib' 2025-09-07T12:05:09.7459638Z Entering 'third_party/cpuinfo' 2025-09-07T12:05:09.7509053Z Entering 'third_party/cudnn_frontend' 2025-09-07T12:05:09.7557526Z Entering 'third_party/cutlass' 2025-09-07T12:05:09.7614712Z Entering 'third_party/fbgemm' 2025-09-07T12:05:09.7665055Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T12:05:09.7714926Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T12:05:09.7770189Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T12:05:09.7819855Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T12:05:09.7876803Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T12:05:09.7925522Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T12:05:09.7973105Z Entering 'third_party/fbgemm/external/json' 2025-09-07T12:05:09.8026545Z Entering 'third_party/flash-attention' 2025-09-07T12:05:09.8075297Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T12:05:09.8128760Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T12:05:09.8187084Z Entering 'third_party/flatbuffers' 2025-09-07T12:05:09.8238065Z Entering 'third_party/fmt' 2025-09-07T12:05:09.8286359Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T12:05:09.8334848Z Entering 'third_party/gloo' 2025-09-07T12:05:09.8384083Z Entering 'third_party/googletest' 2025-09-07T12:05:09.8434231Z Entering 'third_party/ideep' 2025-09-07T12:05:09.8480864Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T12:05:09.8537024Z Entering 'third_party/ittapi' 2025-09-07T12:05:09.8585216Z Entering 'third_party/kineto' 2025-09-07T12:05:09.8633691Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T12:05:09.8678103Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T12:05:09.8722413Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T12:05:09.8765393Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T12:05:09.8808742Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T12:05:09.8850545Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T12:05:09.8896180Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T12:05:09.8940744Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T12:05:09.8988234Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T12:05:09.9040902Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T12:05:09.9092695Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T12:05:09.9137949Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T12:05:09.9185985Z Entering 'third_party/kleidiai' 2025-09-07T12:05:09.9245518Z Entering 'third_party/mimalloc' 2025-09-07T12:05:09.9298798Z Entering 'third_party/nlohmann' 2025-09-07T12:05:09.9349018Z Entering 'third_party/onnx' 2025-09-07T12:05:09.9413008Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T12:05:09.9467468Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T12:05:09.9517372Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T12:05:09.9562726Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T12:05:09.9608190Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T12:05:09.9657926Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T12:05:09.9708010Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T12:05:09.9755705Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T12:05:09.9801686Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T12:05:09.9846295Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T12:05:09.9891632Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T12:05:09.9938358Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T12:05:10.0009093Z Entering 'third_party/pocketfft' 2025-09-07T12:05:10.0058219Z Entering 'third_party/protobuf' 2025-09-07T12:05:10.0106346Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T12:05:10.0153868Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T12:05:10.0204579Z Entering 'third_party/psimd' 2025-09-07T12:05:10.0257921Z Entering 'third_party/pthreadpool' 2025-09-07T12:05:10.0307350Z Entering 'third_party/pybind11' 2025-09-07T12:05:10.0355034Z Entering 'third_party/python-peachpy' 2025-09-07T12:05:10.0404220Z Entering 'third_party/sleef' 2025-09-07T12:05:10.0457647Z Entering 'third_party/tensorpipe' 2025-09-07T12:05:10.0503950Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T12:05:10.0547574Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T12:05:10.0592321Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T12:05:10.0635151Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T12:05:10.0677273Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T12:05:10.0749771Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T12:05:10.0776728Z http.https://github.com/.extraheader 2025-09-07T12:05:10.0790364Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-09-07T12:05:10.0825034Z [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' || :" 2025-09-07T12:05:10.1058525Z Entering 'android/libs/fbjni' 2025-09-07T12:05:10.1093543Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1136152Z Entering 'third_party/FP16' 2025-09-07T12:05:10.1165336Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1201568Z Entering 'third_party/FXdiv' 2025-09-07T12:05:10.1231139Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1266578Z Entering 'third_party/NNPACK' 2025-09-07T12:05:10.1294584Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1331242Z Entering 'third_party/NVTX' 2025-09-07T12:05:10.1356304Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1391689Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T12:05:10.1417018Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1453762Z Entering 'third_party/XNNPACK' 2025-09-07T12:05:10.1482421Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1531773Z Entering 'third_party/aiter' 2025-09-07T12:05:10.1561467Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1596679Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T12:05:10.1625010Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1668410Z Entering 'third_party/benchmark' 2025-09-07T12:05:10.1698646Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1735945Z Entering 'third_party/composable_kernel' 2025-09-07T12:05:10.1767261Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1811184Z Entering 'third_party/cpp-httplib' 2025-09-07T12:05:10.1839663Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1875723Z Entering 'third_party/cpuinfo' 2025-09-07T12:05:10.1903955Z http.https://github.com/.extraheader 2025-09-07T12:05:10.1939705Z Entering 'third_party/cudnn_frontend' 2025-09-07T12:05:10.1968974Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2007157Z Entering 'third_party/cutlass' 2025-09-07T12:05:10.2032234Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2078495Z Entering 'third_party/fbgemm' 2025-09-07T12:05:10.2103889Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2139339Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T12:05:10.2163686Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2201649Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T12:05:10.2227374Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2267168Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T12:05:10.2291712Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2324525Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T12:05:10.2348278Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2392553Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T12:05:10.2416766Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2449254Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T12:05:10.2473434Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2506212Z Entering 'third_party/fbgemm/external/json' 2025-09-07T12:05:10.2530025Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2566996Z Entering 'third_party/flash-attention' 2025-09-07T12:05:10.2591667Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2630863Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T12:05:10.2656800Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2699719Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T12:05:10.2725188Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2772376Z Entering 'third_party/flatbuffers' 2025-09-07T12:05:10.2798865Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2836912Z Entering 'third_party/fmt' 2025-09-07T12:05:10.2862182Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2895085Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T12:05:10.2919669Z http.https://github.com/.extraheader 2025-09-07T12:05:10.2953976Z Entering 'third_party/gloo' 2025-09-07T12:05:10.2979234Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3013034Z Entering 'third_party/googletest' 2025-09-07T12:05:10.3037884Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3072408Z Entering 'third_party/ideep' 2025-09-07T12:05:10.3097295Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3129029Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T12:05:10.3153681Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3195140Z Entering 'third_party/ittapi' 2025-09-07T12:05:10.3219649Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3253577Z Entering 'third_party/kineto' 2025-09-07T12:05:10.3291031Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3328168Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T12:05:10.3358522Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3392978Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T12:05:10.3420676Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3458347Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T12:05:10.3486721Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3526742Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T12:05:10.3555510Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3591365Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T12:05:10.3618170Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3653030Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T12:05:10.3682550Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3723481Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T12:05:10.3751133Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3787853Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T12:05:10.3814412Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3849908Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T12:05:10.3876215Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3912157Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T12:05:10.3938210Z http.https://github.com/.extraheader 2025-09-07T12:05:10.3976666Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T12:05:10.4004723Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4042573Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T12:05:10.4071560Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4111005Z Entering 'third_party/kleidiai' 2025-09-07T12:05:10.4139926Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4176959Z Entering 'third_party/mimalloc' 2025-09-07T12:05:10.4204881Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4240810Z Entering 'third_party/nlohmann' 2025-09-07T12:05:10.4268747Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4306221Z Entering 'third_party/onnx' 2025-09-07T12:05:10.4333851Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4384995Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T12:05:10.4413324Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4455385Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T12:05:10.4483928Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4521212Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T12:05:10.4548542Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4584214Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T12:05:10.4611660Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4651760Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T12:05:10.4679743Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4715386Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T12:05:10.4742112Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4778933Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T12:05:10.4806127Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4843345Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T12:05:10.4871918Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4907227Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T12:05:10.4935394Z http.https://github.com/.extraheader 2025-09-07T12:05:10.4970685Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T12:05:10.4998162Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5037064Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T12:05:10.5062902Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5100621Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T12:05:10.5128147Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5182985Z Entering 'third_party/pocketfft' 2025-09-07T12:05:10.5211983Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5247042Z Entering 'third_party/protobuf' 2025-09-07T12:05:10.5274647Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5312116Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T12:05:10.5338097Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5372104Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T12:05:10.5398258Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5437064Z Entering 'third_party/psimd' 2025-09-07T12:05:10.5464751Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5500372Z Entering 'third_party/pthreadpool' 2025-09-07T12:05:10.5531076Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5568478Z Entering 'third_party/pybind11' 2025-09-07T12:05:10.5596498Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5632288Z Entering 'third_party/python-peachpy' 2025-09-07T12:05:10.5659840Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5695298Z Entering 'third_party/sleef' 2025-09-07T12:05:10.5724562Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5763725Z Entering 'third_party/tensorpipe' 2025-09-07T12:05:10.5791249Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5825913Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T12:05:10.5852686Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5888235Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T12:05:10.5917023Z http.https://github.com/.extraheader 2025-09-07T12:05:10.5952878Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T12:05:10.5979498Z http.https://github.com/.extraheader 2025-09-07T12:05:10.6014953Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T12:05:10.6044133Z http.https://github.com/.extraheader 2025-09-07T12:05:10.6078196Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T12:05:10.6106356Z http.https://github.com/.extraheader 2025-09-07T12:05:10.6296456Z Post job cleanup. 2025-09-07T12:05:10.7189751Z [command]/usr/bin/git version 2025-09-07T12:05:10.7228213Z git version 2.50.1 2025-09-07T12:05:10.7266659Z Temporarily overriding HOME='/home/henry/_work/_temp/be97a12f-8b49-4cae-a8c0-bee739b23aa3' before making global git config changes 2025-09-07T12:05:10.7267371Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T12:05:10.7271358Z [command]/usr/bin/git config --global --add safe.directory /home/henry/_work/pytorch/pytorch 2025-09-07T12:05:10.7306319Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T12:05:10.7351956Z [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' || :" 2025-09-07T12:05:10.7627613Z Entering 'android/libs/fbjni' 2025-09-07T12:05:10.7679473Z Entering 'third_party/FP16' 2025-09-07T12:05:10.7728634Z Entering 'third_party/FXdiv' 2025-09-07T12:05:10.7778342Z Entering 'third_party/NNPACK' 2025-09-07T12:05:10.7828226Z Entering 'third_party/NVTX' 2025-09-07T12:05:10.7877935Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T12:05:10.7927305Z Entering 'third_party/XNNPACK' 2025-09-07T12:05:10.7990783Z Entering 'third_party/aiter' 2025-09-07T12:05:10.8040490Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T12:05:10.8099233Z Entering 'third_party/benchmark' 2025-09-07T12:05:10.8152964Z Entering 'third_party/composable_kernel' 2025-09-07T12:05:10.8211779Z Entering 'third_party/cpp-httplib' 2025-09-07T12:05:10.8261010Z Entering 'third_party/cpuinfo' 2025-09-07T12:05:10.8310512Z Entering 'third_party/cudnn_frontend' 2025-09-07T12:05:10.8360699Z Entering 'third_party/cutlass' 2025-09-07T12:05:10.8418408Z Entering 'third_party/fbgemm' 2025-09-07T12:05:10.8469189Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T12:05:10.8517182Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T12:05:10.8572022Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T12:05:10.8621883Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T12:05:10.8678482Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T12:05:10.8726238Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T12:05:10.8774215Z Entering 'third_party/fbgemm/external/json' 2025-09-07T12:05:10.8825875Z Entering 'third_party/flash-attention' 2025-09-07T12:05:10.8876150Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T12:05:10.8928002Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T12:05:10.8984365Z Entering 'third_party/flatbuffers' 2025-09-07T12:05:10.9036740Z Entering 'third_party/fmt' 2025-09-07T12:05:10.9086720Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T12:05:10.9136617Z Entering 'third_party/gloo' 2025-09-07T12:05:10.9187220Z Entering 'third_party/googletest' 2025-09-07T12:05:10.9236848Z Entering 'third_party/ideep' 2025-09-07T12:05:10.9284832Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T12:05:10.9343765Z Entering 'third_party/ittapi' 2025-09-07T12:05:10.9390138Z Entering 'third_party/kineto' 2025-09-07T12:05:10.9438541Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T12:05:10.9484686Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T12:05:10.9534234Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T12:05:10.9580673Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T12:05:10.9627418Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T12:05:10.9672565Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 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2025-09-07T12:05:11.0330560Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T12:05:11.0377841Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T12:05:11.0424324Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T12:05:11.0470099Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T12:05:11.0516879Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T12:05:11.0562816Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T12:05:11.0608679Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T12:05:11.0655437Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T12:05:11.0706355Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T12:05:11.0755789Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T12:05:11.0823639Z Entering 'third_party/pocketfft' 2025-09-07T12:05:11.0873094Z Entering 'third_party/protobuf' 2025-09-07T12:05:11.0924574Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T12:05:11.0972302Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T12:05:11.1021869Z Entering 'third_party/psimd' 2025-09-07T12:05:11.1071352Z Entering 'third_party/pthreadpool' 2025-09-07T12:05:11.1119869Z Entering 'third_party/pybind11' 2025-09-07T12:05:11.1169548Z Entering 'third_party/python-peachpy' 2025-09-07T12:05:11.1218545Z Entering 'third_party/sleef' 2025-09-07T12:05:11.1268558Z Entering 'third_party/tensorpipe' 2025-09-07T12:05:11.1317011Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T12:05:11.1364699Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T12:05:11.1410569Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T12:05:11.1458253Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T12:05:11.1503282Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T12:05:11.1579782Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T12:05:11.1612534Z [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' || :" 2025-09-07T12:05:11.1877191Z Entering 'android/libs/fbjni' 2025-09-07T12:05:11.1926960Z Entering 'third_party/FP16' 2025-09-07T12:05:11.1975974Z Entering 'third_party/FXdiv' 2025-09-07T12:05:11.2024631Z Entering 'third_party/NNPACK' 2025-09-07T12:05:11.2074048Z Entering 'third_party/NVTX' 2025-09-07T12:05:11.2123654Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T12:05:11.2172919Z Entering 'third_party/XNNPACK' 2025-09-07T12:05:11.2235268Z Entering 'third_party/aiter' 2025-09-07T12:05:11.2284371Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T12:05:11.2342900Z Entering 'third_party/benchmark' 2025-09-07T12:05:11.2391666Z Entering 'third_party/composable_kernel' 2025-09-07T12:05:11.2449030Z Entering 'third_party/cpp-httplib' 2025-09-07T12:05:11.2501045Z Entering 'third_party/cpuinfo' 2025-09-07T12:05:11.2552836Z Entering 'third_party/cudnn_frontend' 2025-09-07T12:05:11.2601452Z Entering 'third_party/cutlass' 2025-09-07T12:05:11.2659454Z Entering 'third_party/fbgemm' 2025-09-07T12:05:11.2711471Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T12:05:11.2759023Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T12:05:11.2812905Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T12:05:11.2858853Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T12:05:11.2914127Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T12:05:11.2960135Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T12:05:11.3006310Z Entering 'third_party/fbgemm/external/json' 2025-09-07T12:05:11.3056734Z Entering 'third_party/flash-attention' 2025-09-07T12:05:11.3105718Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T12:05:11.3160551Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T12:05:11.3216288Z Entering 'third_party/flatbuffers' 2025-09-07T12:05:11.3267947Z Entering 'third_party/fmt' 2025-09-07T12:05:11.3317485Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T12:05:11.3366880Z Entering 'third_party/gloo' 2025-09-07T12:05:11.3416333Z Entering 'third_party/googletest' 2025-09-07T12:05:11.3465499Z Entering 'third_party/ideep' 2025-09-07T12:05:11.3513887Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T12:05:11.3568443Z Entering 'third_party/ittapi' 2025-09-07T12:05:11.3617861Z Entering 'third_party/kineto' 2025-09-07T12:05:11.3666373Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T12:05:11.3714490Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T12:05:11.3762851Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T12:05:11.3809909Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T12:05:11.3856175Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T12:05:11.3902179Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T12:05:11.3954831Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T12:05:11.4001561Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T12:05:11.4048392Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T12:05:11.4098773Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T12:05:11.4148334Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T12:05:11.4196261Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T12:05:11.4246018Z Entering 'third_party/kleidiai' 2025-09-07T12:05:11.4295851Z Entering 'third_party/mimalloc' 2025-09-07T12:05:11.4345060Z Entering 'third_party/nlohmann' 2025-09-07T12:05:11.4395146Z Entering 'third_party/onnx' 2025-09-07T12:05:11.4458025Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T12:05:11.4511473Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T12:05:11.4561042Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T12:05:11.4609228Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T12:05:11.4655030Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T12:05:11.4700879Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T12:05:11.4748334Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T12:05:11.4795143Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T12:05:11.4840731Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T12:05:11.4886720Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T12:05:11.4935746Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T12:05:11.4985272Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T12:05:11.5051387Z Entering 'third_party/pocketfft' 2025-09-07T12:05:11.5101364Z Entering 'third_party/protobuf' 2025-09-07T12:05:11.5152285Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T12:05:11.5199470Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T12:05:11.5249772Z Entering 'third_party/psimd' 2025-09-07T12:05:11.5299233Z Entering 'third_party/pthreadpool' 2025-09-07T12:05:11.5348214Z Entering 'third_party/pybind11' 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