2025-09-07T07:44:40.2334282Z Current runner version: '2.328.0' 2025-09-07T07:44:40.2340553Z Runner name: 'i-01a21955dc3821a00-1002' 2025-09-07T07:44:40.2341411Z Runner group name: 'default' 2025-09-07T07:44:40.2342320Z Machine name: '19cef9d253c5' 2025-09-07T07:44:40.2345226Z ##[group]GITHUB_TOKEN Permissions 2025-09-07T07:44:40.2347528Z Contents: read 2025-09-07T07:44:40.2348079Z Metadata: read 2025-09-07T07:44:40.2348704Z ##[endgroup] 2025-09-07T07:44:40.2351200Z Secret source: Actions 2025-09-07T07:44:40.2351981Z Prepare workflow directory 2025-09-07T07:44:40.2882539Z Prepare all required actions 2025-09-07T07:44:40.2924064Z Getting action download info 2025-09-07T07:44:40.6945881Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd) 2025-09-07T07:44:43.8424462Z Download action repository 'pytorch/pytorch@main' (SHA:ada43ed39c80b746b4822c92640a1882619e2795) 2025-09-07T07:45:26.5684980Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-09-07T07:45:26.9070827Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-09-07T07:45:27.2405243Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-09-07T07:45:27.5413422Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T07:45:27.9171152Z Getting action download info 2025-09-07T07:45:28.0476806Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-09-07T07:45:28.4314023Z Getting action download info 2025-09-07T07:45:28.5676199Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-09-07T07:45:28.8861661Z Getting action download info 2025-09-07T07:45:29.0298111Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-09-07T07:45:29.3572259Z Getting action download info 2025-09-07T07:45:29.5173923Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634) 2025-09-07T07:45:29.5178026Z ##[group] Inputs 2025-09-07T07:45:29.5178450Z build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T07:45:29.5184933Z test-matrix: {"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]} 2025-09-07T07:45:29.5191850Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:45:29.5192867Z sync-tag: 2025-09-07T07:45:29.5193739Z timeout-minutes: 1440 2025-09-07T07:45:29.5194006Z use-gha: 2025-09-07T07:45:29.5195256Z dashboard-tag: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T07:45:29.5196595Z s3-bucket: gha-artifacts 2025-09-07T07:45:29.5196874Z aws-role-to-assume: 2025-09-07T07:45:29.5197506Z disable-monitor: false 2025-09-07T07:45:29.5197850Z monitor-log-interval: 15 2025-09-07T07:45:29.5198151Z monitor-data-collect-interval: 4 2025-09-07T07:45:29.5198480Z ##[endgroup] 2025-09-07T07:45:29.5198946Z Complete job name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T07:45:29.5699912Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-09-07T07:45:29.5700694Z with: 2025-09-07T07:45:29.5701255Z github-secret: *** 2025-09-07T07:45:29.5702001Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-09-07T07:45:29.5702807Z activate-with-label: false 2025-09-07T07:45:29.5703090Z label: with-ssh 2025-09-07T07:45:29.5703328Z remove-existing-keys: true 2025-09-07T07:45:29.5703604Z fail-silently: true 2025-09-07T07:45:29.5704065Z env: 2025-09-07T07:45:29.5704279Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:29.5704527Z ##[endgroup] 2025-09-07T07:45:29.6856755Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-09-07T07:45:29.6857777Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-09-07T07:45:29.7047400Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-09-07T07:45:29.7047866Z with: 2025-09-07T07:45:29.7048089Z no-sudo: true 2025-09-07T07:45:29.7048315Z submodules: recursive 2025-09-07T07:45:29.7048568Z fetch-depth: 0 2025-09-07T07:45:29.7048792Z env: 2025-09-07T07:45:29.7049003Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:29.7049254Z ##[endgroup] 2025-09-07T07:45:29.7132673Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:29.7133938Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:29.7151491Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:45:29.7151917Z env: 2025-09-07T07:45:29.7152148Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:29.7152405Z ##[endgroup] 2025-09-07T07:45:29.7308986Z ##[group]Run actions/checkout@v4 2025-09-07T07:45:29.7309290Z with: 2025-09-07T07:45:29.7309546Z ref: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:45:29.7309892Z fetch-depth: 0 2025-09-07T07:45:29.7310136Z submodules: recursive 2025-09-07T07:45:29.7310390Z show-progress: false 2025-09-07T07:45:29.7310731Z repository: pytorch/pytorch 2025-09-07T07:45:29.7311159Z token: *** 2025-09-07T07:45:29.7311390Z ssh-strict: true 2025-09-07T07:45:29.7311625Z ssh-user: git 2025-09-07T07:45:29.7311873Z persist-credentials: true 2025-09-07T07:45:29.7312137Z clean: true 2025-09-07T07:45:29.7312388Z sparse-checkout-cone-mode: true 2025-09-07T07:45:29.7312700Z fetch-tags: false 2025-09-07T07:45:29.7312923Z lfs: false 2025-09-07T07:45:29.7313153Z set-safe-directory: true 2025-09-07T07:45:29.7313616Z env: 2025-09-07T07:45:29.7313833Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:29.7314085Z ##[endgroup] 2025-09-07T07:45:29.8425251Z Syncing repository: pytorch/pytorch 2025-09-07T07:45:29.8426683Z ##[group]Getting Git version info 2025-09-07T07:45:29.8427110Z Working directory is '/home/bob/_work/pytorch/pytorch' 2025-09-07T07:45:29.8427713Z [command]/usr/bin/git version 2025-09-07T07:45:29.8428005Z git version 2.51.0 2025-09-07T07:45:29.8444788Z ##[endgroup] 2025-09-07T07:45:29.8456460Z Temporarily overriding HOME='/home/bob/_work/_temp/33e3b6e5-818c-4ce9-8385-c3d3f6c56089' before making global git config changes 2025-09-07T07:45:29.8457378Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T07:45:29.8468394Z [command]/usr/bin/git config --global --add safe.directory /home/bob/_work/pytorch/pytorch 2025-09-07T07:45:29.8497929Z Deleting the contents of '/home/bob/_work/pytorch/pytorch' 2025-09-07T07:45:29.8500879Z ##[group]Initializing the repository 2025-09-07T07:45:29.8503922Z [command]/usr/bin/git init /home/bob/_work/pytorch/pytorch 2025-09-07T07:45:29.8542922Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-09-07T07:45:29.8543596Z hint: is subject to change. To configure the initial branch name to use in all 2025-09-07T07:45:29.8544175Z hint: of your new repositories, which will suppress this warning, call: 2025-09-07T07:45:29.8544716Z hint: 2025-09-07T07:45:29.8545032Z hint: git config --global init.defaultBranch 2025-09-07T07:45:29.8545419Z hint: 2025-09-07T07:45:29.8545753Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-09-07T07:45:29.8546355Z hint: 'development'. The just-created branch can be renamed via this command: 2025-09-07T07:45:29.8546817Z hint: 2025-09-07T07:45:29.8547045Z hint: git branch -m 2025-09-07T07:45:29.8547317Z hint: 2025-09-07T07:45:29.8547678Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-09-07T07:45:29.8548327Z Initialized empty Git repository in /home/bob/_work/pytorch/pytorch/.git/ 2025-09-07T07:45:29.8552455Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-09-07T07:45:29.8585289Z ##[endgroup] 2025-09-07T07:45:29.8586053Z ##[group]Disabling automatic garbage collection 2025-09-07T07:45:29.8589046Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:45:29.8614527Z ##[endgroup] 2025-09-07T07:45:29.8614922Z ##[group]Setting up auth 2025-09-07T07:45:29.8620438Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:45:29.8645382Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :" 2025-09-07T07:45:29.8846980Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T07:45:29.8873521Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :" 2025-09-07T07:45:29.9077578Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:45:29.9109468Z ##[endgroup] 2025-09-07T07:45:29.9109928Z ##[group]Fetching the repository 2025-09-07T07:45:29.9119191Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:46:43.2911225Z From https://github.com/pytorch/pytorch 2025-09-07T07:46:43.2912204Z * [new branch] 160583 -> origin/160583 2025-09-07T07:46:43.2913191Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-09-07T07:46:43.2914365Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-09-07T07:46:43.2915527Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-09-07T07:46:43.2917579Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-09-07T07:46:43.2918783Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-09-07T07:46:43.2920085Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-09-07T07:46:43.2921391Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-09-07T07:46:43.2922450Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-09-07T07:46:43.2923618Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-09-07T07:46:43.2924793Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-09-07T07:46:43.2925882Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-09-07T07:46:43.2926923Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-09-07T07:46:43.2927995Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-09-07T07:46:43.2929073Z * [new branch] VLA_exp -> origin/VLA_exp 2025-09-07T07:46:43.2930203Z * [new branch] actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor 2025-09-07T07:46:43.2931563Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-09-07T07:46:43.2933040Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-09-07T07:46:43.2934186Z * [new branch] add-vllm-nightly-build -> origin/add-vllm-nightly-build 2025-09-07T07:46:43.2935349Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-09-07T07:46:43.2936480Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-09-07T07:46:43.2937518Z * [new branch] addsimde -> origin/addsimde 2025-09-07T07:46:43.2938835Z * [new branch] addvllmtest -> origin/addvllmtest 2025-09-07T07:46:43.2939833Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-09-07T07:46:43.2940827Z * [new branch] adi/test -> origin/adi/test 2025-09-07T07:46:43.2941777Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-09-07T07:46:43.2942841Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-09-07T07:46:43.2943786Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-09-07T07:46:43.2945085Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-09-07T07:46:43.2946179Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-09-07T07:46:43.2947212Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-09-07T07:46:43.2948327Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-09-07T07:46:43.2949730Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-09-07T07:46:43.2950857Z * [new branch] alt-disable -> origin/alt-disable 2025-09-07T07:46:43.2952045Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-09-07T07:46:43.2953248Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-09-07T07:46:43.2954408Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-09-07T07:46:43.2955523Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-09-07T07:46:43.2957205Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-09-07T07:46:43.2958477Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-09-07T07:46:43.2959583Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-09-07T07:46:43.2960734Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-09-07T07:46:43.2961816Z * [new branch] angelayi/fake_cache_empty -> origin/angelayi/fake_cache_empty 2025-09-07T07:46:43.2963047Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-09-07T07:46:43.2964160Z * [new branch] angelayi/item -> origin/angelayi/item 2025-09-07T07:46:43.2965123Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-09-07T07:46:43.2966273Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-09-07T07:46:43.2967412Z * [new branch] angelayi/pattern -> origin/angelayi/pattern 2025-09-07T07:46:43.2968503Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-09-07T07:46:43.2969540Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-09-07T07:46:43.2970641Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-09-07T07:46:43.2971717Z * [new branch] 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2025-09-07T07:46:44.1533689Z * [new branch] xmfan/ca_fix_polyfills -> origin/xmfan/ca_fix_polyfills 2025-09-07T07:46:44.1533989Z * [new branch] xmfan/ca_jan3 -> origin/xmfan/ca_jan3 2025-09-07T07:46:44.1534176Z * [new branch] xmfan/ca_jun18 -> origin/xmfan/ca_jun18 2025-09-07T07:46:44.1534360Z * [new branch] xmfan/ca_jun24 -> origin/xmfan/ca_jun24 2025-09-07T07:46:44.1534566Z * [new branch] xmfan/ca_mem_base -> origin/xmfan/ca_mem_base 2025-09-07T07:46:44.1534758Z * [new branch] xmfan/ca_mem_fix -> origin/xmfan/ca_mem_fix 2025-09-07T07:46:44.1534978Z * [new branch] xmfan/ca_memory_fix -> origin/xmfan/ca_memory_fix 2025-09-07T07:46:44.1535216Z * [new branch] xmfan/ca_memory_fix_rebased -> origin/xmfan/ca_memory_fix_rebased 2025-09-07T07:46:44.1535476Z * [new branch] xmfan/ca_memory_fix_rebased2 -> origin/xmfan/ca_memory_fix_rebased2 2025-09-07T07:46:44.1535685Z * [new branch] xmfan/ca_move_to_cuda -> origin/xmfan/ca_move_to_cuda 2025-09-07T07:46:44.1535883Z * [new branch] xmfan/ca_nested -> origin/xmfan/ca_nested 2025-09-07T07:46:44.1536097Z * [new branch] xmfan/ca_overhead -> origin/xmfan/ca_overhead 2025-09-07T07:46:44.1536350Z * [new branch] xmfan/ca_overhead_0eba7e5451 -> origin/xmfan/ca_overhead_0eba7e5451 2025-09-07T07:46:44.1536556Z * [new branch] xmfan/ca_scalar -> origin/xmfan/ca_scalar 2025-09-07T07:46:44.1536793Z * [new branch] xmfan/ca_subclass_mem_fix -> origin/xmfan/ca_subclass_mem_fix 2025-09-07T07:46:44.1536989Z * [new branch] xmfan/ca_warm_mem -> origin/xmfan/ca_warm_mem 2025-09-07T07:46:44.1537213Z * [new branch] xmfan/ca_warm_mem_base -> origin/xmfan/ca_warm_mem_base 2025-09-07T07:46:44.1537410Z * [new branch] xmfan/cacu_jun18 -> origin/xmfan/cacu_jun18 2025-09-07T07:46:44.1537618Z * [new branch] xmfan/cacu_jun19 -> origin/xmfan/cacu_jun19 2025-09-07T07:46:44.1537807Z * [new branch] xmfan/cacu_jun4 -> origin/xmfan/cacu_jun4 2025-09-07T07:46:44.1538098Z * [new branch] xmfan/cacu_may27 -> origin/xmfan/cacu_may27 2025-09-07T07:46:44.1538337Z * [new branch] xmfan/disable_duck_shape -> origin/xmfan/disable_duck_shape 2025-09-07T07:46:44.1538616Z * [new branch] xmfan/fca_cpp_node_passthrough -> origin/xmfan/fca_cpp_node_passthrough 2025-09-07T07:46:44.1538824Z * [new branch] xmfan/issue_123374 -> origin/xmfan/issue_123374 2025-09-07T07:46:44.1539272Z * [new branch] xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T07:46:44.1539718Z * [new branch] xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T07:46:44.1539936Z * [new branch] xmfan/segfault_test -> origin/xmfan/segfault_test 2025-09-07T07:46:44.1540153Z * [new branch] xmfan/single_step -> origin/xmfan/single_step 2025-09-07T07:46:44.1540343Z * [new branch] xmfan/sth_0829 -> origin/xmfan/sth_0829 2025-09-07T07:46:44.1540520Z * [new branch] xmfan/test -> origin/xmfan/test 2025-09-07T07:46:44.1540774Z * [new branch] yguo/debug-0226-constexpr -> origin/yguo/debug-0226-constexpr 2025-09-07T07:46:44.1540998Z * [new branch] yguo/new_latest_changes -> origin/yguo/new_latest_changes 2025-09-07T07:46:44.1541275Z * [new branch] yguo/patch_constexpr_changes -> origin/yguo/patch_constexpr_changes 2025-09-07T07:46:44.1541484Z * [new branch] yihan_quantization -> origin/yihan_quantization 2025-09-07T07:46:44.1541767Z * [new branch] yiming/add_jit_trace_benchmark -> origin/yiming/add_jit_trace_benchmark 2025-09-07T07:46:44.1542119Z * [new branch] yiming/add_nativert_benchmark -> origin/yiming/add_nativert_benchmark 2025-09-07T07:46:44.1542322Z * [new branch] yiming/bootcamp -> origin/yiming/bootcamp 2025-09-07T07:46:44.1542544Z * [new branch] zainr/canary-test -> origin/zainr/canary-test 2025-09-07T07:46:44.1542792Z * [new branch] zainr/cleanup-gh-runners -> origin/zainr/cleanup-gh-runners 2025-09-07T07:46:44.1543015Z * [new branch] zainr/git-push-v2 -> origin/zainr/git-push-v2 2025-09-07T07:46:44.1543252Z * [new branch] zainr/pull-migration-c -> origin/zainr/pull-migration-c 2025-09-07T07:46:44.1543431Z * [new branch] zainr/test -> origin/zainr/test 2025-09-07T07:46:44.1543624Z * [new branch] zainr/test2 -> origin/zainr/test2 2025-09-07T07:46:44.1543817Z * [new branch] zainr/unstable -> origin/zainr/unstable 2025-09-07T07:46:44.1544050Z * [new branch] zainr/unstable-xla -> origin/zainr/unstable-xla 2025-09-07T07:46:44.1544267Z * [new branch] zasdfgbnm-patch-3 -> origin/zasdfgbnm-patch-3 2025-09-07T07:46:44.1544441Z * [new branch] zb2p -> origin/zb2p 2025-09-07T07:46:44.1544664Z * [new branch] zero_grad_optimization -> origin/zero_grad_optimization 2025-09-07T07:46:44.1544983Z * [new branch] zeros-and-scatter-part2 -> origin/zeros-and-scatter-part2 2025-09-07T07:46:44.1545216Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-09-07T07:46:44.1545441Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-09-07T07:46:44.1545634Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-09-07T07:46:44.1546115Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-09-07T07:46:44.1546288Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-09-07T07:46:44.1546610Z * [new tag] ciflow/binaries/156049 -> ciflow/binaries/156049 2025-09-07T07:46:44.1546796Z * [new tag] ciflow/binaries/156712 -> ciflow/binaries/156712 2025-09-07T07:46:44.1546991Z * [new tag] ciflow/binaries/157432 -> ciflow/binaries/157432 2025-09-07T07:46:44.1547171Z * [new tag] ciflow/binaries/157685 -> ciflow/binaries/157685 2025-09-07T07:46:44.1547366Z * [new tag] ciflow/binaries/157689 -> ciflow/binaries/157689 2025-09-07T07:46:44.1547545Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-09-07T07:46:44.1547727Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-09-07T07:46:44.1547925Z * [new tag] ciflow/binaries/160720 -> ciflow/binaries/160720 2025-09-07T07:46:44.1548106Z * [new tag] ciflow/binaries/162080 -> ciflow/binaries/162080 2025-09-07T07:46:44.1548307Z * [new tag] ciflow/binaries/162329 -> ciflow/binaries/162329 2025-09-07T07:46:44.1548552Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-09-07T07:46:44.1548806Z * [new tag] ciflow/binaries_libtorch/156711 -> ciflow/binaries_libtorch/156711 2025-09-07T07:46:44.1549046Z * [new tag] ciflow/binaries_libtorch/157432 -> ciflow/binaries_libtorch/157432 2025-09-07T07:46:44.1549258Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-09-07T07:46:44.1549484Z * [new tag] ciflow/binaries_wheel/156711 -> ciflow/binaries_wheel/156711 2025-09-07T07:46:44.1549694Z * [new tag] ciflow/binaries_wheel/157432 -> ciflow/binaries_wheel/157432 2025-09-07T07:46:44.1550006Z * [new tag] ciflow/binaries_wheel/162136 -> ciflow/binaries_wheel/162136 2025-09-07T07:46:44.1550217Z * [new tag] ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252 2025-09-07T07:46:44.1550426Z * [new tag] ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325 2025-09-07T07:46:44.1550670Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-09-07T07:46:44.1550872Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-09-07T07:46:44.1551082Z * [new tag] ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984 2025-09-07T07:46:44.1551278Z * [new tag] ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003 2025-09-07T07:46:44.1551489Z * [new tag] ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011 2025-09-07T07:46:44.1551686Z * [new tag] ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026 2025-09-07T07:46:44.1551885Z * [new tag] ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033 2025-09-07T07:46:44.1552097Z * [new tag] ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040 2025-09-07T07:46:44.1552291Z * [new tag] ciflow/h100-symm-mem/162041 -> ciflow/h100-symm-mem/162041 2025-09-07T07:46:44.1552505Z * [new tag] ciflow/h100-symm-mem/162142 -> ciflow/h100-symm-mem/162142 2025-09-07T07:46:44.1552696Z * [new tag] ciflow/h100-symm-mem/162150 -> ciflow/h100-symm-mem/162150 2025-09-07T07:46:44.1552903Z * [new tag] ciflow/h100-symm-mem/162243 -> ciflow/h100-symm-mem/162243 2025-09-07T07:46:44.1553099Z * [new tag] ciflow/h100-symm-mem/162320 -> ciflow/h100-symm-mem/162320 2025-09-07T07:46:44.1553257Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-09-07T07:46:44.1553432Z * [new tag] ciflow/h100/160480 -> ciflow/h100/160480 2025-09-07T07:46:44.1553590Z * [new tag] ciflow/h100/161749 -> ciflow/h100/161749 2025-09-07T07:46:44.1553854Z * [new tag] ciflow/h100/162022 -> ciflow/h100/162022 2025-09-07T07:46:44.1554011Z * [new tag] ciflow/h100/162278 -> ciflow/h100/162278 2025-09-07T07:46:44.1554404Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592 2025-09-07T07:46:44.1554757Z * [new tag] ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592 2025-09-07T07:46:44.1555007Z * [new tag] ciflow/inductor-periodic/162063 -> ciflow/inductor-periodic/162063 2025-09-07T07:46:44.1555270Z * [new tag] ciflow/inductor-periodic/162227 -> ciflow/inductor-periodic/162227 2025-09-07T07:46:44.1555516Z * [new tag] ciflow/inductor-periodic/162323 -> ciflow/inductor-periodic/162323 2025-09-07T07:46:44.1555742Z * [new tag] ciflow/inductor-rocm/154170 -> ciflow/inductor-rocm/154170 2025-09-07T07:46:44.1555952Z * [new tag] ciflow/inductor-rocm/159146 -> ciflow/inductor-rocm/159146 2025-09-07T07:46:44.1556156Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-09-07T07:46:44.1556375Z * [new tag] ciflow/inductor-rocm/161715 -> ciflow/inductor-rocm/161715 2025-09-07T07:46:44.1556577Z * [new tag] ciflow/inductor-rocm/162053 -> ciflow/inductor-rocm/162053 2025-09-07T07:46:44.1556797Z * [new tag] ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056 2025-09-07T07:46:44.1556981Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-09-07T07:46:44.1557169Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-09-07T07:46:44.1557364Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-09-07T07:46:44.1557631Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-09-07T07:46:44.1557828Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-09-07T07:46:44.1558006Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-09-07T07:46:44.1558198Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-09-07T07:46:44.1558376Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-09-07T07:46:44.1558558Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-09-07T07:46:44.1558749Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-09-07T07:46:44.1558928Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-09-07T07:46:44.1559120Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-09-07T07:46:44.1559304Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-09-07T07:46:44.1559501Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-09-07T07:46:44.1559684Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-09-07T07:46:44.1559866Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-09-07T07:46:44.1560059Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-09-07T07:46:44.1560239Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-09-07T07:46:44.1560430Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-09-07T07:46:44.1560609Z * [new tag] ciflow/inductor/158647 -> ciflow/inductor/158647 2025-09-07T07:46:44.1560791Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-09-07T07:46:44.1560986Z * [new tag] ciflow/inductor/159146 -> ciflow/inductor/159146 2025-09-07T07:46:44.1561165Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-09-07T07:46:44.1561440Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-09-07T07:46:44.1561623Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-09-07T07:46:44.1561816Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-09-07T07:46:44.1561996Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-09-07T07:46:44.1562175Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-09-07T07:46:44.1562372Z * [new tag] ciflow/inductor/160161 -> ciflow/inductor/160161 2025-09-07T07:46:44.1562552Z * [new tag] ciflow/inductor/160174 -> ciflow/inductor/160174 2025-09-07T07:46:44.1562751Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-09-07T07:46:44.1562929Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-09-07T07:46:44.1563113Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-09-07T07:46:44.1563303Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-09-07T07:46:44.1563488Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-09-07T07:46:44.1563682Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-09-07T07:46:44.1563862Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-09-07T07:46:44.1564060Z * [new tag] ciflow/inductor/160480 -> ciflow/inductor/160480 2025-09-07T07:46:44.1564238Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-09-07T07:46:44.1564500Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-09-07T07:46:44.1564695Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-09-07T07:46:44.1564881Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-09-07T07:46:44.1565075Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-09-07T07:46:44.1565253Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-09-07T07:46:44.1565433Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-09-07T07:46:44.1565627Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-09-07T07:46:44.1565808Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-09-07T07:46:44.1566008Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-09-07T07:46:44.1566194Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-09-07T07:46:44.1566390Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-09-07T07:46:44.1566577Z * [new tag] ciflow/inductor/160843 -> ciflow/inductor/160843 2025-09-07T07:46:44.1566758Z * [new tag] ciflow/inductor/160869 -> ciflow/inductor/160869 2025-09-07T07:46:44.1566955Z * [new tag] ciflow/inductor/160920 -> ciflow/inductor/160920 2025-09-07T07:46:44.1567133Z * [new tag] ciflow/inductor/160928 -> ciflow/inductor/160928 2025-09-07T07:46:44.1567329Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-09-07T07:46:44.1567507Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-09-07T07:46:44.1567684Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-09-07T07:46:44.1567874Z * [new tag] ciflow/inductor/161109 -> ciflow/inductor/161109 2025-09-07T07:46:44.1568058Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-09-07T07:46:44.1568338Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-09-07T07:46:44.1568521Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-09-07T07:46:44.1568714Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-09-07T07:46:44.1568895Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-09-07T07:46:44.1569075Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-09-07T07:46:44.1569273Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-09-07T07:46:44.1569452Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-09-07T07:46:44.1569643Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-09-07T07:46:44.1569826Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-09-07T07:46:44.1570005Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-09-07T07:46:44.1570196Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-09-07T07:46:44.1570377Z * [new tag] ciflow/inductor/161442 -> ciflow/inductor/161442 2025-09-07T07:46:44.1570570Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-09-07T07:46:44.1570748Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-09-07T07:46:44.1570941Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-09-07T07:46:44.1571118Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-09-07T07:46:44.1571296Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-09-07T07:46:44.1571572Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-09-07T07:46:44.1571755Z * [new tag] ciflow/inductor/161595 -> ciflow/inductor/161595 2025-09-07T07:46:44.1571950Z * [new tag] ciflow/inductor/161596 -> ciflow/inductor/161596 2025-09-07T07:46:44.1572131Z * [new tag] ciflow/inductor/161630 -> ciflow/inductor/161630 2025-09-07T07:46:44.1572314Z * [new tag] ciflow/inductor/161667 -> ciflow/inductor/161667 2025-09-07T07:46:44.1572503Z * [new tag] ciflow/inductor/161670 -> ciflow/inductor/161670 2025-09-07T07:46:44.1572681Z * [new tag] ciflow/inductor/161673 -> ciflow/inductor/161673 2025-09-07T07:46:44.1573065Z * [new tag] ciflow/inductor/161674 -> ciflow/inductor/161674 2025-09-07T07:46:44.1573249Z * [new tag] ciflow/inductor/161675 -> ciflow/inductor/161675 2025-09-07T07:46:44.1573448Z * [new tag] ciflow/inductor/161693 -> ciflow/inductor/161693 2025-09-07T07:46:44.1573626Z * [new tag] ciflow/inductor/161695 -> ciflow/inductor/161695 2025-09-07T07:46:44.1573807Z * [new tag] ciflow/inductor/161715 -> ciflow/inductor/161715 2025-09-07T07:46:44.1574000Z * [new tag] ciflow/inductor/161730 -> ciflow/inductor/161730 2025-09-07T07:46:44.1574182Z * [new tag] ciflow/inductor/161732 -> ciflow/inductor/161732 2025-09-07T07:46:44.1574377Z * [new tag] ciflow/inductor/161744 -> ciflow/inductor/161744 2025-09-07T07:46:44.1574556Z * [new tag] ciflow/inductor/161746 -> ciflow/inductor/161746 2025-09-07T07:46:44.1574737Z * [new tag] ciflow/inductor/161747 -> ciflow/inductor/161747 2025-09-07T07:46:44.1574928Z * [new tag] ciflow/inductor/161819 -> ciflow/inductor/161819 2025-09-07T07:46:44.1575113Z * [new tag] ciflow/inductor/161821 -> ciflow/inductor/161821 2025-09-07T07:46:44.1575307Z * [new tag] ciflow/inductor/161828 -> ciflow/inductor/161828 2025-09-07T07:46:44.1575615Z * [new tag] ciflow/inductor/161879 -> ciflow/inductor/161879 2025-09-07T07:46:44.1575808Z * [new tag] ciflow/inductor/161880 -> ciflow/inductor/161880 2025-09-07T07:46:44.1575993Z * [new tag] ciflow/inductor/161881 -> ciflow/inductor/161881 2025-09-07T07:46:44.1576174Z * [new tag] ciflow/inductor/161907 -> ciflow/inductor/161907 2025-09-07T07:46:44.1576364Z * [new tag] ciflow/inductor/161914 -> ciflow/inductor/161914 2025-09-07T07:46:44.1576542Z * [new tag] ciflow/inductor/161924 -> ciflow/inductor/161924 2025-09-07T07:46:44.1576735Z * [new tag] ciflow/inductor/161936 -> ciflow/inductor/161936 2025-09-07T07:46:44.1576916Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-09-07T07:46:44.1577108Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-09-07T07:46:44.1577290Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-09-07T07:46:44.1577475Z * [new tag] ciflow/inductor/161955 -> ciflow/inductor/161955 2025-09-07T07:46:44.1577671Z * [new tag] ciflow/inductor/161957 -> ciflow/inductor/161957 2025-09-07T07:46:44.1577851Z * [new tag] ciflow/inductor/161975 -> ciflow/inductor/161975 2025-09-07T07:46:44.1578043Z * [new tag] ciflow/inductor/161977 -> ciflow/inductor/161977 2025-09-07T07:46:44.1578220Z * [new tag] ciflow/inductor/161978 -> ciflow/inductor/161978 2025-09-07T07:46:44.1578401Z * [new tag] ciflow/inductor/161979 -> ciflow/inductor/161979 2025-09-07T07:46:44.1578695Z * [new tag] ciflow/inductor/161980 -> ciflow/inductor/161980 2025-09-07T07:46:44.1578878Z * [new tag] ciflow/inductor/161988 -> ciflow/inductor/161988 2025-09-07T07:46:44.1579076Z * [new tag] ciflow/inductor/161994 -> ciflow/inductor/161994 2025-09-07T07:46:44.1579260Z * [new tag] ciflow/inductor/162013 -> ciflow/inductor/162013 2025-09-07T07:46:44.1579451Z * [new tag] ciflow/inductor/162014 -> ciflow/inductor/162014 2025-09-07T07:46:44.1579632Z * [new tag] ciflow/inductor/162017 -> ciflow/inductor/162017 2025-09-07T07:46:44.1579812Z * [new tag] ciflow/inductor/162021 -> ciflow/inductor/162021 2025-09-07T07:46:44.1580006Z * [new tag] ciflow/inductor/162023 -> ciflow/inductor/162023 2025-09-07T07:46:44.1580187Z * [new tag] ciflow/inductor/162027 -> ciflow/inductor/162027 2025-09-07T07:46:44.1580381Z * [new tag] ciflow/inductor/162029 -> ciflow/inductor/162029 2025-09-07T07:46:44.1580563Z * [new tag] ciflow/inductor/162030 -> ciflow/inductor/162030 2025-09-07T07:46:44.1580749Z * [new tag] ciflow/inductor/162031 -> ciflow/inductor/162031 2025-09-07T07:46:44.1580942Z * [new tag] ciflow/inductor/162033 -> ciflow/inductor/162033 2025-09-07T07:46:44.1581121Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-09-07T07:46:44.1581313Z * [new tag] ciflow/inductor/162053 -> ciflow/inductor/162053 2025-09-07T07:46:44.1581490Z * [new tag] ciflow/inductor/162056 -> ciflow/inductor/162056 2025-09-07T07:46:44.1581682Z * [new tag] ciflow/inductor/162063 -> ciflow/inductor/162063 2025-09-07T07:46:44.1581860Z * [new tag] ciflow/inductor/162066 -> ciflow/inductor/162066 2025-09-07T07:46:44.1582041Z * [new tag] ciflow/inductor/162068 -> ciflow/inductor/162068 2025-09-07T07:46:44.1582237Z * [new tag] ciflow/inductor/162081 -> ciflow/inductor/162081 2025-09-07T07:46:44.1582498Z * [new tag] ciflow/inductor/162088 -> ciflow/inductor/162088 2025-09-07T07:46:44.1582695Z * [new tag] ciflow/inductor/162089 -> ciflow/inductor/162089 2025-09-07T07:46:44.1582874Z * [new tag] ciflow/inductor/162094 -> ciflow/inductor/162094 2025-09-07T07:46:44.1583054Z * [new tag] ciflow/inductor/162098 -> ciflow/inductor/162098 2025-09-07T07:46:44.1583248Z * [new tag] ciflow/inductor/162101 -> ciflow/inductor/162101 2025-09-07T07:46:44.1583427Z * [new tag] ciflow/inductor/162102 -> ciflow/inductor/162102 2025-09-07T07:46:44.1583618Z * [new tag] ciflow/inductor/162104 -> ciflow/inductor/162104 2025-09-07T07:46:44.1583796Z * [new tag] ciflow/inductor/162106 -> ciflow/inductor/162106 2025-09-07T07:46:44.1583992Z * [new tag] ciflow/inductor/162108 -> ciflow/inductor/162108 2025-09-07T07:46:44.1584174Z * [new tag] ciflow/inductor/162126 -> ciflow/inductor/162126 2025-09-07T07:46:44.1584355Z * [new tag] ciflow/inductor/162149 -> ciflow/inductor/162149 2025-09-07T07:46:44.1584547Z * [new tag] ciflow/inductor/162164 -> ciflow/inductor/162164 2025-09-07T07:46:44.1584728Z * [new tag] ciflow/inductor/162166 -> ciflow/inductor/162166 2025-09-07T07:46:44.1585007Z * [new tag] ciflow/inductor/162169 -> ciflow/inductor/162169 2025-09-07T07:46:44.1585190Z * [new tag] ciflow/inductor/162170 -> ciflow/inductor/162170 2025-09-07T07:46:44.1585373Z * [new tag] ciflow/inductor/162171 -> ciflow/inductor/162171 2025-09-07T07:46:44.1585568Z * [new tag] ciflow/inductor/162183 -> ciflow/inductor/162183 2025-09-07T07:46:44.1585930Z * [new tag] ciflow/inductor/162189 -> ciflow/inductor/162189 2025-09-07T07:46:44.1586126Z * [new tag] ciflow/inductor/162190 -> ciflow/inductor/162190 2025-09-07T07:46:44.1586310Z * [new tag] ciflow/inductor/162191 -> ciflow/inductor/162191 2025-09-07T07:46:44.1586506Z * [new tag] ciflow/inductor/162194 -> ciflow/inductor/162194 2025-09-07T07:46:44.1586682Z * [new tag] ciflow/inductor/162200 -> ciflow/inductor/162200 2025-09-07T07:46:44.1586865Z * [new tag] ciflow/inductor/162201 -> ciflow/inductor/162201 2025-09-07T07:46:44.1587063Z * [new tag] ciflow/inductor/162208 -> ciflow/inductor/162208 2025-09-07T07:46:44.1587241Z * [new tag] ciflow/inductor/162211 -> ciflow/inductor/162211 2025-09-07T07:46:44.1587438Z * [new tag] ciflow/inductor/162216 -> ciflow/inductor/162216 2025-09-07T07:46:44.1587618Z * [new tag] ciflow/inductor/162220 -> ciflow/inductor/162220 2025-09-07T07:46:44.1587797Z * [new tag] ciflow/inductor/162222 -> ciflow/inductor/162222 2025-09-07T07:46:44.1587990Z * [new tag] ciflow/inductor/162227 -> ciflow/inductor/162227 2025-09-07T07:46:44.1588170Z * [new tag] ciflow/inductor/162238 -> ciflow/inductor/162238 2025-09-07T07:46:44.1588364Z * [new tag] ciflow/inductor/162239 -> ciflow/inductor/162239 2025-09-07T07:46:44.1588547Z * [new tag] ciflow/inductor/162240 -> ciflow/inductor/162240 2025-09-07T07:46:44.1588740Z * [new tag] ciflow/inductor/162244 -> ciflow/inductor/162244 2025-09-07T07:46:44.1588918Z * [new tag] ciflow/inductor/162245 -> ciflow/inductor/162245 2025-09-07T07:46:44.1589095Z * [new tag] ciflow/inductor/162262 -> ciflow/inductor/162262 2025-09-07T07:46:44.1589291Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-09-07T07:46:44.1589470Z * [new tag] ciflow/inductor/162278 -> ciflow/inductor/162278 2025-09-07T07:46:44.1589773Z * [new tag] ciflow/inductor/162284 -> ciflow/inductor/162284 2025-09-07T07:46:44.1589955Z * [new tag] ciflow/inductor/162286 -> ciflow/inductor/162286 2025-09-07T07:46:44.1590135Z * [new tag] ciflow/inductor/162288 -> ciflow/inductor/162288 2025-09-07T07:46:44.1590326Z * [new tag] ciflow/inductor/162293 -> ciflow/inductor/162293 2025-09-07T07:46:44.1590506Z * [new tag] ciflow/inductor/162294 -> ciflow/inductor/162294 2025-09-07T07:46:44.1590700Z * [new tag] ciflow/inductor/162295 -> ciflow/inductor/162295 2025-09-07T07:46:44.1590880Z * [new tag] ciflow/inductor/162296 -> ciflow/inductor/162296 2025-09-07T07:46:44.1591079Z * [new tag] ciflow/inductor/162298 -> ciflow/inductor/162298 2025-09-07T07:46:44.1591259Z * [new tag] ciflow/inductor/162307 -> ciflow/inductor/162307 2025-09-07T07:46:44.1591443Z * [new tag] ciflow/inductor/162309 -> ciflow/inductor/162309 2025-09-07T07:46:44.1591634Z * [new tag] ciflow/inductor/162311 -> ciflow/inductor/162311 2025-09-07T07:46:44.1591814Z * [new tag] ciflow/inductor/162312 -> ciflow/inductor/162312 2025-09-07T07:46:44.1592010Z * [new tag] ciflow/inductor/162315 -> ciflow/inductor/162315 2025-09-07T07:46:44.1592190Z * [new tag] ciflow/inductor/162316 -> ciflow/inductor/162316 2025-09-07T07:46:44.1592370Z * [new tag] ciflow/inductor/162318 -> ciflow/inductor/162318 2025-09-07T07:46:44.1592566Z * [new tag] ciflow/inductor/162323 -> ciflow/inductor/162323 2025-09-07T07:46:44.1592745Z * [new tag] ciflow/inductor/162341 -> ciflow/inductor/162341 2025-09-07T07:46:44.1593030Z * [new tag] ciflow/inductor/162345 -> ciflow/inductor/162345 2025-09-07T07:46:44.1593225Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-09-07T07:46:44.1593428Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-09-07T07:46:44.1593612Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-09-07T07:46:44.1593817Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-09-07T07:46:44.1594027Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-09-07T07:46:44.1594225Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-09-07T07:46:44.1594404Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-09-07T07:46:44.1594567Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-09-07T07:46:44.1594741Z * [new tag] ciflow/mps/161988 -> ciflow/mps/161988 2025-09-07T07:46:44.1594901Z * [new tag] ciflow/mps/162108 -> ciflow/mps/162108 2025-09-07T07:46:44.1595062Z * [new tag] ciflow/mps/162153 -> ciflow/mps/162153 2025-09-07T07:46:44.1595230Z * [new tag] ciflow/mps/162281 -> ciflow/mps/162281 2025-09-07T07:46:44.1595410Z * [new tag] ciflow/nightly/156049 -> ciflow/nightly/156049 2025-09-07T07:46:44.1595599Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-09-07T07:46:44.1595798Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-09-07T07:46:44.1596075Z * [new tag] ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529 2025-09-07T07:46:44.1596359Z * [new tag] ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715 2025-09-07T07:46:44.1596558Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-09-07T07:46:44.1596844Z * [new tag] ciflow/periodic/156703 -> ciflow/periodic/156703 2025-09-07T07:46:44.1597035Z * [new tag] ciflow/periodic/161715 -> ciflow/periodic/161715 2025-09-07T07:46:44.1597234Z * [new tag] ciflow/periodic/162021 -> ciflow/periodic/162021 2025-09-07T07:46:44.1597420Z * [new tag] ciflow/periodic/162323 -> ciflow/periodic/162323 2025-09-07T07:46:44.1597613Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-09-07T07:46:44.1597820Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-09-07T07:46:44.1598000Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-09-07T07:46:44.1598203Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-09-07T07:46:44.1598418Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-09-07T07:46:44.1598654Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-09-07T07:46:44.1598901Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-09-07T07:46:44.1599125Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-09-07T07:46:44.1599361Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-09-07T07:46:44.1599606Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-09-07T07:46:44.1599829Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-09-07T07:46:44.1600017Z * [new tag] ciflow/rocm-mi300/154170 -> ciflow/rocm-mi300/154170 2025-09-07T07:46:44.1600203Z * [new tag] ciflow/rocm-mi300/158747 -> ciflow/rocm-mi300/158747 2025-09-07T07:46:44.1600508Z * [new tag] ciflow/rocm-mi300/159146 -> ciflow/rocm-mi300/159146 2025-09-07T07:46:44.1600698Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-09-07T07:46:44.1600893Z * [new tag] ciflow/rocm-mi300/161715 -> ciflow/rocm-mi300/161715 2025-09-07T07:46:44.1601079Z * [new tag] ciflow/rocm-mi300/161957 -> ciflow/rocm-mi300/161957 2025-09-07T07:46:44.1601263Z * [new tag] ciflow/rocm-mi300/162053 -> ciflow/rocm-mi300/162053 2025-09-07T07:46:44.1601464Z * [new tag] ciflow/rocm-mi300/162056 -> ciflow/rocm-mi300/162056 2025-09-07T07:46:44.1601648Z * [new tag] ciflow/rocm-mi300/162112 -> ciflow/rocm-mi300/162112 2025-09-07T07:46:44.1601844Z * [new tag] ciflow/rocm-mi300/162245 -> ciflow/rocm-mi300/162245 2025-09-07T07:46:44.1602031Z * [new tag] ciflow/rocm-mi300/162278 -> ciflow/rocm-mi300/162278 2025-09-07T07:46:44.1602228Z * [new tag] ciflow/rocm-mi300/162288 -> ciflow/rocm-mi300/162288 2025-09-07T07:46:44.1602422Z * [new tag] ciflow/rocm-mi355/162053 -> ciflow/rocm-mi355/162053 2025-09-07T07:46:44.1602608Z * [new tag] ciflow/rocm-mi355/162056 -> ciflow/rocm-mi355/162056 2025-09-07T07:46:44.1602792Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-09-07T07:46:44.1602957Z * [new tag] ciflow/rocm/154170 -> ciflow/rocm/154170 2025-09-07T07:46:44.1603138Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-09-07T07:46:44.1603302Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-09-07T07:46:44.1603467Z * [new tag] ciflow/rocm/158747 -> ciflow/rocm/158747 2025-09-07T07:46:44.1603642Z * [new tag] ciflow/rocm/159146 -> ciflow/rocm/159146 2025-09-07T07:46:44.1603805Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-09-07T07:46:44.1604063Z * [new tag] ciflow/rocm/161715 -> ciflow/rocm/161715 2025-09-07T07:46:44.1604228Z * [new tag] ciflow/rocm/161972 -> ciflow/rocm/161972 2025-09-07T07:46:44.1604403Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-09-07T07:46:44.1604564Z * [new tag] ciflow/rocm/162053 -> ciflow/rocm/162053 2025-09-07T07:46:44.1604729Z * [new tag] ciflow/rocm/162056 -> ciflow/rocm/162056 2025-09-07T07:46:44.1604904Z * [new tag] ciflow/rocm/162112 -> ciflow/rocm/162112 2025-09-07T07:46:44.1605065Z * [new tag] ciflow/rocm/162278 -> ciflow/rocm/162278 2025-09-07T07:46:44.1605241Z * [new tag] ciflow/rocm/162288 -> ciflow/rocm/162288 2025-09-07T07:46:44.1605406Z * [new tag] ciflow/rocm/162305 -> ciflow/rocm/162305 2025-09-07T07:46:44.1605576Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-09-07T07:46:44.1605759Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-09-07T07:46:44.1606291Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-09-07T07:46:44.1606470Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-09-07T07:46:44.1606631Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-09-07T07:46:44.1606810Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-09-07T07:46:44.1606980Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-09-07T07:46:44.1607149Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-09-07T07:46:44.1607415Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-09-07T07:46:44.1607584Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-09-07T07:46:44.1607771Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-09-07T07:46:44.1607939Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-09-07T07:46:44.1608105Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-09-07T07:46:44.1608605Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-09-07T07:46:44.1608772Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-09-07T07:46:44.1608953Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-09-07T07:46:44.1609123Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-09-07T07:46:44.1609306Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-09-07T07:46:44.1609476Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-09-07T07:46:44.1609986Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-09-07T07:46:44.1610229Z * [new tag] ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329 2025-09-07T07:46:44.1610396Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-09-07T07:46:44.1610578Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-09-07T07:46:44.1610742Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-09-07T07:46:44.1610925Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-09-07T07:46:44.1611096Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-09-07T07:46:44.1611263Z * [new tag] ciflow/trunk/148919 -> ciflow/trunk/148919 2025-09-07T07:46:44.1611525Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-09-07T07:46:44.1611692Z * [new tag] ciflow/trunk/154170 -> ciflow/trunk/154170 2025-09-07T07:46:44.1611872Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-09-07T07:46:44.1612039Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-09-07T07:46:44.1612207Z * [new tag] ciflow/trunk/156703 -> ciflow/trunk/156703 2025-09-07T07:46:44.1612387Z * [new tag] ciflow/trunk/156711 -> ciflow/trunk/156711 2025-09-07T07:46:44.1612555Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-09-07T07:46:44.1612736Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-09-07T07:46:44.1613100Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-09-07T07:46:44.1613287Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-09-07T07:46:44.1613454Z * [new tag] ciflow/trunk/157813 -> ciflow/trunk/157813 2025-09-07T07:46:44.1613620Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-09-07T07:46:44.1613804Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-09-07T07:46:44.1613970Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-09-07T07:46:44.1614152Z * [new tag] ciflow/trunk/158404 -> ciflow/trunk/158404 2025-09-07T07:46:44.1614321Z * [new tag] ciflow/trunk/158647 -> ciflow/trunk/158647 2025-09-07T07:46:44.1614489Z * [new tag] ciflow/trunk/158846 -> ciflow/trunk/158846 2025-09-07T07:46:44.1614804Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-09-07T07:46:44.1614971Z * [new tag] ciflow/trunk/159682 -> ciflow/trunk/159682 2025-09-07T07:46:44.1615159Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-09-07T07:46:44.1615326Z * [new tag] ciflow/trunk/160161 -> ciflow/trunk/160161 2025-09-07T07:46:44.1615510Z * [new tag] ciflow/trunk/160236 -> ciflow/trunk/160236 2025-09-07T07:46:44.1615677Z * [new tag] ciflow/trunk/160329 -> ciflow/trunk/160329 2025-09-07T07:46:44.1615845Z * [new tag] ciflow/trunk/160480 -> ciflow/trunk/160480 2025-09-07T07:46:44.1616032Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-09-07T07:46:44.1616201Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-09-07T07:46:44.1616382Z * [new tag] ciflow/trunk/160843 -> ciflow/trunk/160843 2025-09-07T07:46:44.1616554Z * [new tag] ciflow/trunk/160869 -> ciflow/trunk/160869 2025-09-07T07:46:44.1616724Z * [new tag] ciflow/trunk/160928 -> ciflow/trunk/160928 2025-09-07T07:46:44.1616908Z * [new tag] ciflow/trunk/160940 -> ciflow/trunk/160940 2025-09-07T07:46:44.1617075Z * [new tag] ciflow/trunk/160943 -> ciflow/trunk/160943 2025-09-07T07:46:44.1617253Z * [new tag] ciflow/trunk/160953 -> ciflow/trunk/160953 2025-09-07T07:46:44.1617417Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-09-07T07:46:44.1617596Z * [new tag] ciflow/trunk/161178 -> ciflow/trunk/161178 2025-09-07T07:46:44.1617763Z * [new tag] ciflow/trunk/161349 -> ciflow/trunk/161349 2025-09-07T07:46:44.1617931Z * [new tag] ciflow/trunk/161350 -> ciflow/trunk/161350 2025-09-07T07:46:44.1618111Z * [new tag] ciflow/trunk/161351 -> ciflow/trunk/161351 2025-09-07T07:46:44.1618277Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-09-07T07:46:44.1618550Z * [new tag] ciflow/trunk/161405 -> ciflow/trunk/161405 2025-09-07T07:46:44.1618716Z * [new tag] ciflow/trunk/161406 -> ciflow/trunk/161406 2025-09-07T07:46:44.1618881Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-09-07T07:46:44.1619059Z * [new tag] ciflow/trunk/161468 -> ciflow/trunk/161468 2025-09-07T07:46:44.1619223Z * [new tag] ciflow/trunk/161499 -> ciflow/trunk/161499 2025-09-07T07:46:44.1619404Z * [new tag] ciflow/trunk/161527 -> ciflow/trunk/161527 2025-09-07T07:46:44.1619570Z * [new tag] ciflow/trunk/161534 -> ciflow/trunk/161534 2025-09-07T07:46:44.1619751Z * [new tag] ciflow/trunk/161591 -> ciflow/trunk/161591 2025-09-07T07:46:44.1619920Z * [new tag] ciflow/trunk/161595 -> ciflow/trunk/161595 2025-09-07T07:46:44.1620092Z * [new tag] ciflow/trunk/161596 -> ciflow/trunk/161596 2025-09-07T07:46:44.1620274Z * [new tag] ciflow/trunk/161633 -> ciflow/trunk/161633 2025-09-07T07:46:44.1620443Z * [new tag] ciflow/trunk/161634 -> ciflow/trunk/161634 2025-09-07T07:46:44.1620622Z * [new tag] ciflow/trunk/161635 -> ciflow/trunk/161635 2025-09-07T07:46:44.1620788Z * [new tag] ciflow/trunk/161667 -> ciflow/trunk/161667 2025-09-07T07:46:44.1620959Z * [new tag] ciflow/trunk/161670 -> ciflow/trunk/161670 2025-09-07T07:46:44.1621136Z * [new tag] ciflow/trunk/161692 -> ciflow/trunk/161692 2025-09-07T07:46:44.1621299Z * [new tag] ciflow/trunk/161693 -> ciflow/trunk/161693 2025-09-07T07:46:44.1621561Z * [new tag] ciflow/trunk/161695 -> ciflow/trunk/161695 2025-09-07T07:46:44.1621729Z * [new tag] ciflow/trunk/161730 -> ciflow/trunk/161730 2025-09-07T07:46:44.1621897Z * [new tag] ciflow/trunk/161744 -> ciflow/trunk/161744 2025-09-07T07:46:44.1622074Z * [new tag] ciflow/trunk/161749 -> ciflow/trunk/161749 2025-09-07T07:46:44.1622239Z * [new tag] ciflow/trunk/161881 -> ciflow/trunk/161881 2025-09-07T07:46:44.1622415Z * [new tag] ciflow/trunk/161924 -> ciflow/trunk/161924 2025-09-07T07:46:44.1622580Z * [new tag] ciflow/trunk/161926 -> ciflow/trunk/161926 2025-09-07T07:46:44.1622757Z * [new tag] ciflow/trunk/161936 -> ciflow/trunk/161936 2025-09-07T07:46:44.1622922Z * [new tag] ciflow/trunk/161952 -> ciflow/trunk/161952 2025-09-07T07:46:44.1623091Z * [new tag] ciflow/trunk/161955 -> ciflow/trunk/161955 2025-09-07T07:46:44.1623270Z * [new tag] ciflow/trunk/161957 -> ciflow/trunk/161957 2025-09-07T07:46:44.1623440Z * [new tag] ciflow/trunk/161959 -> ciflow/trunk/161959 2025-09-07T07:46:44.1623620Z * [new tag] ciflow/trunk/161977 -> ciflow/trunk/161977 2025-09-07T07:46:44.1623789Z * [new tag] ciflow/trunk/161988 -> ciflow/trunk/161988 2025-09-07T07:46:44.1623957Z * [new tag] ciflow/trunk/161994 -> ciflow/trunk/161994 2025-09-07T07:46:44.1624134Z * [new tag] ciflow/trunk/162007 -> ciflow/trunk/162007 2025-09-07T07:46:44.1624301Z * [new tag] ciflow/trunk/162013 -> ciflow/trunk/162013 2025-09-07T07:46:44.1624478Z * [new tag] ciflow/trunk/162017 -> ciflow/trunk/162017 2025-09-07T07:46:44.1624644Z * [new tag] ciflow/trunk/162021 -> ciflow/trunk/162021 2025-09-07T07:46:44.1624910Z * [new tag] ciflow/trunk/162022 -> ciflow/trunk/162022 2025-09-07T07:46:44.1625189Z * [new tag] ciflow/trunk/162040 -> ciflow/trunk/162040 2025-09-07T07:46:44.1625356Z * [new tag] ciflow/trunk/162041 -> ciflow/trunk/162041 2025-09-07T07:46:44.1625536Z * [new tag] ciflow/trunk/162062 -> ciflow/trunk/162062 2025-09-07T07:46:44.1625708Z * [new tag] ciflow/trunk/162066 -> ciflow/trunk/162066 2025-09-07T07:46:44.1625886Z * [new tag] ciflow/trunk/162089 -> ciflow/trunk/162089 2025-09-07T07:46:44.1626050Z * [new tag] ciflow/trunk/162099 -> ciflow/trunk/162099 2025-09-07T07:46:44.1626220Z * [new tag] ciflow/trunk/162104 -> ciflow/trunk/162104 2025-09-07T07:46:44.1626403Z * [new tag] ciflow/trunk/162106 -> ciflow/trunk/162106 2025-09-07T07:46:44.1626571Z * [new tag] ciflow/trunk/162112 -> ciflow/trunk/162112 2025-09-07T07:46:44.1626752Z * [new tag] ciflow/trunk/162119 -> ciflow/trunk/162119 2025-09-07T07:46:44.1626926Z * [new tag] ciflow/trunk/162142 -> ciflow/trunk/162142 2025-09-07T07:46:44.1627108Z * [new tag] ciflow/trunk/162169 -> ciflow/trunk/162169 2025-09-07T07:46:44.1627272Z * [new tag] ciflow/trunk/162183 -> ciflow/trunk/162183 2025-09-07T07:46:44.1627441Z * [new tag] ciflow/trunk/162190 -> ciflow/trunk/162190 2025-09-07T07:46:44.1627621Z * [new tag] ciflow/trunk/162194 -> ciflow/trunk/162194 2025-09-07T07:46:44.1627790Z * [new tag] ciflow/trunk/162200 -> ciflow/trunk/162200 2025-09-07T07:46:44.1627967Z * [new tag] ciflow/trunk/162206 -> ciflow/trunk/162206 2025-09-07T07:46:44.1628243Z * [new tag] ciflow/trunk/162208 -> ciflow/trunk/162208 2025-09-07T07:46:44.1628411Z * [new tag] ciflow/trunk/162222 -> ciflow/trunk/162222 2025-09-07T07:46:44.1628593Z * [new tag] ciflow/trunk/162238 -> ciflow/trunk/162238 2025-09-07T07:46:44.1628760Z * [new tag] ciflow/trunk/162244 -> ciflow/trunk/162244 2025-09-07T07:46:44.1628942Z * [new tag] ciflow/trunk/162267 -> ciflow/trunk/162267 2025-09-07T07:46:44.1629109Z * [new tag] ciflow/trunk/162269 -> ciflow/trunk/162269 2025-09-07T07:46:44.1629288Z * [new tag] ciflow/trunk/162278 -> ciflow/trunk/162278 2025-09-07T07:46:44.1629454Z * [new tag] ciflow/trunk/162286 -> ciflow/trunk/162286 2025-09-07T07:46:44.1629619Z * [new tag] ciflow/trunk/162288 -> ciflow/trunk/162288 2025-09-07T07:46:44.1629799Z * [new tag] ciflow/trunk/162293 -> ciflow/trunk/162293 2025-09-07T07:46:44.1629973Z * [new tag] ciflow/trunk/162310 -> ciflow/trunk/162310 2025-09-07T07:46:44.1630158Z * [new tag] ciflow/trunk/162311 -> ciflow/trunk/162311 2025-09-07T07:46:44.1630327Z * [new tag] ciflow/trunk/162315 -> ciflow/trunk/162315 2025-09-07T07:46:44.1630495Z * [new tag] ciflow/trunk/162325 -> ciflow/trunk/162325 2025-09-07T07:46:44.1630676Z * [new tag] ciflow/trunk/162328 -> ciflow/trunk/162328 2025-09-07T07:46:44.1630842Z * [new tag] ciflow/trunk/162329 -> ciflow/trunk/162329 2025-09-07T07:46:44.1631025Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-09-07T07:46:44.1631191Z * [new tag] ciflow/vllm/162292 -> ciflow/vllm/162292 2025-09-07T07:46:44.1631392Z * [new tag] ciflow/win-arm64/156049 -> ciflow/win-arm64/156049 2025-09-07T07:46:44.1631577Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-09-07T07:46:44.1631743Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-09-07T07:46:44.1632005Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-09-07T07:46:44.1632171Z * [new tag] ciflow/xpu/159459 -> ciflow/xpu/159459 2025-09-07T07:46:44.1632343Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-09-07T07:46:44.1632504Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-09-07T07:46:44.1632669Z * [new tag] ciflow/xpu/160867 -> ciflow/xpu/160867 2025-09-07T07:46:44.1632841Z * [new tag] ciflow/xpu/160938 -> ciflow/xpu/160938 2025-09-07T07:46:44.1633005Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-09-07T07:46:44.1633183Z * [new tag] ciflow/xpu/160953 -> ciflow/xpu/160953 2025-09-07T07:46:44.1633351Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-09-07T07:46:44.1633530Z * [new tag] ciflow/xpu/161058 -> ciflow/xpu/161058 2025-09-07T07:46:44.1633692Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-09-07T07:46:44.1633854Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-09-07T07:46:44.1634028Z * [new tag] ciflow/xpu/161485 -> ciflow/xpu/161485 2025-09-07T07:46:44.1634190Z * [new tag] ciflow/xpu/161988 -> ciflow/xpu/161988 2025-09-07T07:46:44.1634364Z * [new tag] ciflow/xpu/162062 -> ciflow/xpu/162062 2025-09-07T07:46:44.1634512Z * [new tag] cslpull75 -> cslpull75 2025-09-07T07:46:44.1634658Z * [new tag] cslpull76 -> cslpull76 2025-09-07T07:46:44.1634895Z * [new tag] cslpull77 -> cslpull77 2025-09-07T07:46:44.1635039Z * [new tag] cslpull78 -> cslpull78 2025-09-07T07:46:44.1635197Z * [new tag] cslpull79 -> cslpull79 2025-09-07T07:46:44.1635340Z * [new tag] cslpull80 -> cslpull80 2025-09-07T07:46:44.1635483Z * [new tag] cslpull81 -> cslpull81 2025-09-07T07:46:44.1635634Z * [new tag] cslpull82 -> cslpull82 2025-09-07T07:46:44.1635776Z * [new tag] cslpull83 -> cslpull83 2025-09-07T07:46:44.1635926Z * [new tag] cslpull84 -> cslpull84 2025-09-07T07:46:44.1636069Z * [new tag] cslpull85 -> cslpull85 2025-09-07T07:46:44.1636225Z * [new tag] cslpull86 -> cslpull86 2025-09-07T07:46:44.1636366Z * [new tag] cslpull87 -> cslpull87 2025-09-07T07:46:44.1636512Z * [new tag] cslpull88 -> cslpull88 2025-09-07T07:46:44.1636665Z * [new tag] cslpull89 -> cslpull89 2025-09-07T07:46:44.1636811Z * [new tag] cslpull90 -> cslpull90 2025-09-07T07:46:44.1636965Z * [new tag] cslpull91 -> cslpull91 2025-09-07T07:46:44.1637107Z * [new tag] cslpull92 -> cslpull92 2025-09-07T07:46:44.1637251Z * [new tag] flight_5 -> flight_5 2025-09-07T07:46:44.1637410Z * [new tag] flight_5.1 -> flight_5.1 2025-09-07T07:46:44.1637553Z * [new tag] flight_5.2 -> flight_5.2 2025-09-07T07:46:44.1637706Z * [new tag] flight_5.3 -> flight_5.3 2025-09-07T07:46:44.1637848Z * [new tag] forpull1 -> forpull1 2025-09-07T07:46:44.1638023Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-09-07T07:46:44.1638202Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-09-07T07:46:44.1638459Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-09-07T07:46:44.1638636Z * [new tag] nightly-binary -> nightly-binary 2025-09-07T07:46:44.1638812Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-09-07T07:46:44.1638986Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-09-07T07:46:44.1639364Z * [new tag] trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608 2025-09-07T07:46:44.1639756Z * [new tag] trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 2025-09-07T07:46:44.1640152Z * [new tag] trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544 2025-09-07T07:46:44.1640562Z * [new tag] trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b 2025-09-07T07:46:44.1640960Z * [new tag] trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388 2025-09-07T07:46:44.1641348Z * [new tag] trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 2025-09-07T07:46:44.1641729Z * [new tag] trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4 2025-09-07T07:46:44.1642118Z * [new tag] trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 2025-09-07T07:46:44.1642498Z * [new tag] trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23 2025-09-07T07:46:44.1642979Z * [new tag] trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 2025-09-07T07:46:44.1643369Z * [new tag] trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 2025-09-07T07:46:44.1643759Z * [new tag] trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 2025-09-07T07:46:44.1644150Z * [new tag] trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 2025-09-07T07:46:44.1644546Z * [new tag] trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 2025-09-07T07:46:44.1644936Z * [new tag] trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 2025-09-07T07:46:44.1645340Z * [new tag] trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c 2025-09-07T07:46:44.1645736Z * [new tag] trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 2025-09-07T07:46:44.1646120Z * [new tag] trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e 2025-09-07T07:46:44.1646513Z * [new tag] trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 2025-09-07T07:46:44.1646915Z * [new tag] trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f 2025-09-07T07:46:44.1647310Z * [new tag] trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f 2025-09-07T07:46:44.1647690Z * [new tag] trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0 2025-09-07T07:46:44.1648091Z * [new tag] trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c 2025-09-07T07:46:44.1648565Z * [new tag] trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 2025-09-07T07:46:44.1648972Z * [new tag] trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 2025-09-07T07:46:44.1649352Z * [new tag] trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb 2025-09-07T07:46:44.1649745Z * [new tag] trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 2025-09-07T07:46:44.1650146Z * [new tag] trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 2025-09-07T07:46:44.1650527Z * [new tag] trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c 2025-09-07T07:46:44.1650934Z * [new tag] trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 2025-09-07T07:46:44.1651324Z * [new tag] trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 2025-09-07T07:46:44.1651721Z * [new tag] trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 2025-09-07T07:46:44.1652108Z * [new tag] trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a 2025-09-07T07:46:44.1652506Z * [new tag] trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 2025-09-07T07:46:44.1653554Z * [new tag] trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 2025-09-07T07:46:44.1653939Z * [new tag] trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a 2025-09-07T07:46:44.1654456Z * [new tag] trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b 2025-09-07T07:46:44.1654836Z * [new tag] trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc 2025-09-07T07:46:44.1655230Z * [new tag] trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05 2025-09-07T07:46:44.1655620Z * [new tag] trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 2025-09-07T07:46:44.1656021Z * [new tag] trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd 2025-09-07T07:46:44.1656410Z * [new tag] trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 2025-09-07T07:46:44.1656804Z * [new tag] trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f 2025-09-07T07:46:44.1657210Z * [new tag] trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23 2025-09-07T07:46:44.1657591Z * [new tag] trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 2025-09-07T07:46:44.1657985Z * [new tag] trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f 2025-09-07T07:46:44.1658379Z * [new tag] trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 2025-09-07T07:46:44.1658763Z * [new tag] trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9 2025-09-07T07:46:44.1659149Z * [new tag] trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 2025-09-07T07:46:44.1659539Z * [new tag] trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef 2025-09-07T07:46:44.1660044Z * [new tag] trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c 2025-09-07T07:46:44.1660422Z * [new tag] trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6 2025-09-07T07:46:44.1660826Z * [new tag] trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 2025-09-07T07:46:44.1661210Z * [new tag] trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a 2025-09-07T07:46:44.1661611Z * [new tag] trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 2025-09-07T07:46:44.1661997Z * [new tag] trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 2025-09-07T07:46:44.1662407Z * [new tag] trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 2025-09-07T07:46:44.1662793Z * [new tag] trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 2025-09-07T07:46:44.1663166Z * [new tag] trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176 2025-09-07T07:46:44.1663565Z * [new tag] trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 2025-09-07T07:46:44.1663958Z * [new tag] trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b 2025-09-07T07:46:44.1664361Z * [new tag] trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 2025-09-07T07:46:44.1664926Z * [new tag] trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287 2025-09-07T07:46:44.1665326Z * [new tag] trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f 2025-09-07T07:46:44.1665716Z * [new tag] trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 2025-09-07T07:46:44.1666125Z * [new tag] trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 2025-09-07T07:46:44.1666517Z * [new tag] trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f 2025-09-07T07:46:44.1666907Z * [new tag] trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf 2025-09-07T07:46:44.1667311Z * [new tag] trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 2025-09-07T07:46:44.1667700Z * [new tag] trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d 2025-09-07T07:46:44.1668104Z * [new tag] trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa 2025-09-07T07:46:44.1668489Z * [new tag] trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 2025-09-07T07:46:44.1668883Z * [new tag] trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336 2025-09-07T07:46:44.1669260Z * [new tag] trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63 2025-09-07T07:46:44.1669651Z * [new tag] trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3 2025-09-07T07:46:44.1670045Z * [new tag] trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c 2025-09-07T07:46:44.1670548Z * [new tag] trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 2025-09-07T07:46:44.1670949Z * [new tag] trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf 2025-09-07T07:46:44.1671351Z * [new tag] trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e 2025-09-07T07:46:44.1671758Z * [new tag] trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 2025-09-07T07:46:44.1672146Z * [new tag] trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215 2025-09-07T07:46:44.1672547Z * [new tag] trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d 2025-09-07T07:46:44.1672931Z * [new tag] trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 2025-09-07T07:46:44.1673321Z * [new tag] trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c 2025-09-07T07:46:44.1673727Z * [new tag] trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 2025-09-07T07:46:44.1674101Z * [new tag] trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b 2025-09-07T07:46:44.1674493Z * [new tag] trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 2025-09-07T07:46:44.1674869Z * [new tag] trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503 2025-09-07T07:46:44.1675275Z * [new tag] trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 2025-09-07T07:46:44.1675766Z * [new tag] trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 2025-09-07T07:46:44.1676162Z * [new tag] trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 2025-09-07T07:46:44.1676555Z * [new tag] trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 2025-09-07T07:46:44.1676937Z * [new tag] trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a 2025-09-07T07:46:44.1677327Z * [new tag] trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 2025-09-07T07:46:44.1677724Z * [new tag] trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 2025-09-07T07:46:44.1678127Z * [new tag] trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c 2025-09-07T07:46:44.1678518Z * [new tag] trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 2025-09-07T07:46:44.1678915Z * [new tag] trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806 2025-09-07T07:46:44.1679306Z * [new tag] trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 2025-09-07T07:46:44.1679696Z * [new tag] trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 2025-09-07T07:46:44.1680102Z * [new tag] trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 2025-09-07T07:46:44.1680480Z * [new tag] trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251 2025-09-07T07:46:44.1680875Z * [new tag] trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 2025-09-07T07:46:44.1681340Z * [new tag] trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c 2025-09-07T07:46:44.1681741Z * [new tag] trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a 2025-09-07T07:46:44.1682127Z * [new tag] trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db 2025-09-07T07:46:44.1682516Z * [new tag] trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536 2025-09-07T07:46:44.1682894Z * [new tag] trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f 2025-09-07T07:46:44.1683278Z * [new tag] trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 2025-09-07T07:46:44.1683676Z * [new tag] trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b 2025-09-07T07:46:44.1684057Z * [new tag] trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda 2025-09-07T07:46:44.1684451Z * [new tag] trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b 2025-09-07T07:46:44.1684841Z * [new tag] trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 2025-09-07T07:46:44.1685233Z * [new tag] trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8 2025-09-07T07:46:44.1685624Z * [new tag] trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b 2025-09-07T07:46:44.1686091Z * [new tag] trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab 2025-09-07T07:46:44.1686488Z * [new tag] trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 2025-09-07T07:46:44.1686868Z * [new tag] trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe 2025-09-07T07:46:44.1687272Z * [new tag] trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 2025-09-07T07:46:44.1687660Z * [new tag] trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 2025-09-07T07:46:44.1688054Z * [new tag] trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 2025-09-07T07:46:44.1688434Z * [new tag] trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c 2025-09-07T07:46:44.1688832Z * [new tag] trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d 2025-09-07T07:46:44.1689201Z * [new tag] trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429 2025-09-07T07:46:44.1689593Z * [new tag] trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 2025-09-07T07:46:44.1689988Z * [new tag] trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c 2025-09-07T07:46:44.1690381Z * [new tag] trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895 2025-09-07T07:46:44.1690784Z * [new tag] trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 2025-09-07T07:46:44.1691176Z * [new tag] trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435 2025-09-07T07:46:44.1691652Z * [new tag] trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965 2025-09-07T07:46:44.1692047Z * [new tag] trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 2025-09-07T07:46:44.1692441Z * [new tag] trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 2025-09-07T07:46:44.1692995Z * [new tag] trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 2025-09-07T07:46:44.1693388Z * [new tag] trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 2025-09-07T07:46:44.1693791Z * [new tag] trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 2025-09-07T07:46:44.1694179Z * [new tag] trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f 2025-09-07T07:46:44.1694587Z * [new tag] trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 2025-09-07T07:46:44.1694975Z * [new tag] trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610 2025-09-07T07:46:44.1695378Z * [new tag] trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 2025-09-07T07:46:44.1695769Z * [new tag] trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af 2025-09-07T07:46:44.1696161Z * [new tag] trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 2025-09-07T07:46:44.1696675Z * [new tag] trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d 2025-09-07T07:46:44.1697055Z * [new tag] trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 2025-09-07T07:46:44.1697462Z * [new tag] trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 2025-09-07T07:46:44.1697842Z * [new tag] trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab 2025-09-07T07:46:44.1698243Z * [new tag] trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d 2025-09-07T07:46:44.1698631Z * [new tag] trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:44.1699039Z * [new tag] trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c 2025-09-07T07:46:44.1699435Z * [new tag] trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e 2025-09-07T07:46:44.1699825Z * [new tag] trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 2025-09-07T07:46:44.1700220Z * [new tag] trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1 2025-09-07T07:46:44.1700612Z * [new tag] trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 2025-09-07T07:46:44.1701013Z * [new tag] trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a 2025-09-07T07:46:44.1701405Z * [new tag] trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500 2025-09-07T07:46:44.1701820Z * [new tag] trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 2025-09-07T07:46:44.1702318Z * [new tag] trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6 2025-09-07T07:46:44.1702710Z * [new tag] trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 2025-09-07T07:46:44.1703114Z * [new tag] trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd 2025-09-07T07:46:44.1703500Z * [new tag] trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57 2025-09-07T07:46:44.1703893Z * [new tag] trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4 2025-09-07T07:46:44.1704294Z * [new tag] trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e 2025-09-07T07:46:44.1704703Z * [new tag] trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839 2025-09-07T07:46:44.1705182Z * [new tag] trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60 2025-09-07T07:46:44.1705582Z * [new tag] trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 2025-09-07T07:46:44.1705975Z * [new tag] trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 2025-09-07T07:46:44.1706372Z * [new tag] trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 2025-09-07T07:46:44.1706776Z * [new tag] trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 2025-09-07T07:46:44.1707155Z * [new tag] trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d 2025-09-07T07:46:44.1707662Z * [new tag] trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 2025-09-07T07:46:44.1708049Z * [new tag] trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92 2025-09-07T07:46:44.1708447Z * [new tag] trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098 2025-09-07T07:46:44.1708831Z * [new tag] trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356 2025-09-07T07:46:44.1709214Z * [new tag] trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae 2025-09-07T07:46:44.1709625Z * [new tag] trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 2025-09-07T07:46:44.1710018Z * [new tag] trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e 2025-09-07T07:46:44.1710429Z * [new tag] trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 2025-09-07T07:46:44.1710819Z * [new tag] trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 2025-09-07T07:46:44.1711225Z * [new tag] trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c 2025-09-07T07:46:44.1711619Z * [new tag] trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 2025-09-07T07:46:44.1712034Z * [new tag] trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d 2025-09-07T07:46:44.1712418Z * [new tag] trunk/ada43ed39c80b746b4822c92640a1882619e2795 -> trunk/ada43ed39c80b746b4822c92640a1882619e2795 2025-09-07T07:46:44.1712816Z * [new tag] trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa 2025-09-07T07:46:44.1713323Z * [new tag] trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c 2025-09-07T07:46:44.1713712Z * [new tag] trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d 2025-09-07T07:46:44.1714104Z * [new tag] trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 2025-09-07T07:46:44.1714497Z * [new tag] trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f 2025-09-07T07:46:44.1714903Z * [new tag] trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 2025-09-07T07:46:44.1715288Z * [new tag] trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 2025-09-07T07:46:44.1715702Z * [new tag] trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de 2025-09-07T07:46:44.1716083Z * [new tag] trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b 2025-09-07T07:46:44.1716483Z * [new tag] trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 2025-09-07T07:46:44.1716887Z * [new tag] trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 2025-09-07T07:46:44.1717267Z * [new tag] trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b 2025-09-07T07:46:44.1717668Z * [new tag] trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde 2025-09-07T07:46:44.1718156Z * [new tag] trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c 2025-09-07T07:46:44.1718568Z * [new tag] trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 2025-09-07T07:46:44.1718953Z * [new tag] trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052 2025-09-07T07:46:44.1719338Z * [new tag] trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e 2025-09-07T07:46:44.1719740Z * [new tag] trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 2025-09-07T07:46:44.1720136Z * [new tag] trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 2025-09-07T07:46:44.1720529Z * [new tag] trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85 2025-09-07T07:46:44.1720926Z * [new tag] trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d 2025-09-07T07:46:44.1721339Z * [new tag] trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 2025-09-07T07:46:44.1721718Z * [new tag] trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865 2025-09-07T07:46:44.1722127Z * [new tag] trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 2025-09-07T07:46:44.1722524Z * [new tag] trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 2025-09-07T07:46:44.1722920Z * [new tag] trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 2025-09-07T07:46:44.1723335Z * [new tag] trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf 2025-09-07T07:46:44.1723891Z * [new tag] trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 2025-09-07T07:46:44.1724298Z * [new tag] trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad 2025-09-07T07:46:44.1724691Z * [new tag] trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 2025-09-07T07:46:44.1725085Z * [new tag] trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 2025-09-07T07:46:44.1725463Z * [new tag] trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76 2025-09-07T07:46:44.1725844Z * [new tag] trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5 2025-09-07T07:46:44.1726252Z * [new tag] trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 2025-09-07T07:46:44.1726649Z * [new tag] trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd 2025-09-07T07:46:44.1727047Z * [new tag] trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741 2025-09-07T07:46:44.1727437Z * [new tag] trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b 2025-09-07T07:46:44.1727839Z * [new tag] trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 2025-09-07T07:46:44.1728249Z * [new tag] trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 2025-09-07T07:46:44.1728653Z * [new tag] trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b 2025-09-07T07:46:44.1729130Z * [new tag] trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8 2025-09-07T07:46:44.1729521Z * [new tag] trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 2025-09-07T07:46:44.1729927Z * [new tag] trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7 2025-09-07T07:46:44.1730311Z * [new tag] trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87 2025-09-07T07:46:44.1730713Z * [new tag] trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e 2025-09-07T07:46:44.1731093Z * [new tag] trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e 2025-09-07T07:46:44.1731510Z * [new tag] trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d 2025-09-07T07:46:44.1731903Z * [new tag] trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 2025-09-07T07:46:44.1732309Z * [new tag] trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e 2025-09-07T07:46:44.1732696Z * [new tag] trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 2025-09-07T07:46:44.1733217Z * [new tag] trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 2025-09-07T07:46:44.1733613Z * [new tag] trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 2025-09-07T07:46:44.1733996Z * [new tag] trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462 2025-09-07T07:46:44.1734399Z * [new tag] trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 2025-09-07T07:46:44.1734910Z * [new tag] trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285 2025-09-07T07:46:44.1735303Z * [new tag] trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643 2025-09-07T07:46:44.1735694Z * [new tag] trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 2025-09-07T07:46:44.1736084Z * [new tag] trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661 2025-09-07T07:46:44.1736492Z * [new tag] trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab 2025-09-07T07:46:44.1736893Z * [new tag] trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 2025-09-07T07:46:44.1737310Z * [new tag] trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 2025-09-07T07:46:44.1737703Z * [new tag] trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061 2025-09-07T07:46:44.1738102Z * [new tag] trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a 2025-09-07T07:46:44.1738489Z * [new tag] trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 2025-09-07T07:46:44.1738904Z * [new tag] trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d 2025-09-07T07:46:44.1739287Z * [new tag] trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717 2025-09-07T07:46:44.1739791Z * [new tag] trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 2025-09-07T07:46:44.1740195Z * [new tag] trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 2025-09-07T07:46:44.1740582Z * [new tag] trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439 2025-09-07T07:46:44.1740980Z * [new tag] trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 2025-09-07T07:46:44.1741369Z * [new tag] trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 2025-09-07T07:46:44.1741780Z * [new tag] trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 2025-09-07T07:46:44.1742157Z * [new tag] trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b 2025-09-07T07:46:44.1742537Z * [new tag] trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090 2025-09-07T07:46:44.1742945Z * [new tag] trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087 2025-09-07T07:46:44.1743352Z * [new tag] trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 2025-09-07T07:46:44.1743757Z * [new tag] trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de 2025-09-07T07:46:44.1744152Z * [new tag] trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 2025-09-07T07:46:44.1744563Z * [new tag] trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 2025-09-07T07:46:44.1745028Z * [new tag] trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b 2025-09-07T07:46:44.1745514Z * [new tag] trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37 2025-09-07T07:46:44.1745897Z * [new tag] trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 2025-09-07T07:46:44.1746278Z * [new tag] trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd 2025-09-07T07:46:44.1746688Z * [new tag] trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb 2025-09-07T07:46:44.1747082Z * [new tag] trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c 2025-09-07T07:46:44.1747478Z * [new tag] trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8 2025-09-07T07:46:44.1747873Z * [new tag] trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c 2025-09-07T07:46:44.1748275Z * [new tag] trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c 2025-09-07T07:46:44.1748659Z * [new tag] trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 2025-09-07T07:46:44.1749074Z * [new tag] trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 2025-09-07T07:46:44.1749465Z * [new tag] trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa 2025-09-07T07:46:44.1749858Z * [new tag] trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab 2025-09-07T07:46:44.1750254Z * [new tag] trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd 2025-09-07T07:46:44.1750480Z * [new tag] v0.1.1 -> v0.1.1 2025-09-07T07:46:44.1750636Z * [new tag] v0.1.10 -> v0.1.10 2025-09-07T07:46:44.1750771Z * [new tag] v0.1.11 -> v0.1.11 2025-09-07T07:46:44.1750903Z * [new tag] v0.1.12 -> v0.1.12 2025-09-07T07:46:44.1751052Z * [new tag] v0.1.2 -> v0.1.2 2025-09-07T07:46:44.1751215Z * [new tag] v0.1.3 -> v0.1.3 2025-09-07T07:46:44.1751361Z * [new tag] v0.1.4 -> v0.1.4 2025-09-07T07:46:44.1751494Z * [new tag] v0.1.5 -> v0.1.5 2025-09-07T07:46:44.1751638Z * [new tag] v0.1.6 -> v0.1.6 2025-09-07T07:46:44.1751770Z * [new tag] v0.1.7 -> v0.1.7 2025-09-07T07:46:44.1751907Z * [new tag] v0.1.8 -> v0.1.8 2025-09-07T07:46:44.1752055Z * [new tag] v0.1.9 -> v0.1.9 2025-09-07T07:46:44.1752185Z * [new tag] v0.2.0 -> v0.2.0 2025-09-07T07:46:44.1752326Z * [new tag] v0.3.0 -> v0.3.0 2025-09-07T07:46:44.1752459Z * [new tag] v0.3.1 -> v0.3.1 2025-09-07T07:46:44.1752588Z * [new tag] v0.4.0 -> v0.4.0 2025-09-07T07:46:44.1752732Z * [new tag] v0.4.1 -> v0.4.1 2025-09-07T07:46:44.1752864Z * [new tag] v1.0.0 -> v1.0.0 2025-09-07T07:46:44.1753019Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-09-07T07:46:44.1753150Z * [new tag] v1.0.1 -> v1.0.1 2025-09-07T07:46:44.1753290Z * [new tag] v1.0rc0 -> v1.0rc0 2025-09-07T07:46:44.1753437Z * [new tag] v1.0rc1 -> v1.0rc1 2025-09-07T07:46:44.1753656Z * [new tag] v1.1.0 -> v1.1.0 2025-09-07T07:46:44.1753810Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-09-07T07:46:44.1753943Z * [new tag] v1.10.0 -> v1.10.0 2025-09-07T07:46:44.1754089Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-09-07T07:46:44.1754245Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-09-07T07:46:44.1754388Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-09-07T07:46:44.1754533Z * [new tag] v1.10.1 -> v1.10.1 2025-09-07T07:46:44.1754674Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-09-07T07:46:44.1754825Z * [new tag] v1.10.2 -> v1.10.2 2025-09-07T07:46:44.1754972Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-09-07T07:46:44.1755109Z * [new tag] v1.11.0 -> v1.11.0 2025-09-07T07:46:44.1755272Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-09-07T07:46:44.1755415Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-09-07T07:46:44.1755570Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-09-07T07:46:44.1755714Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-09-07T07:46:44.1755855Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-09-07T07:46:44.1756011Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-09-07T07:46:44.1756152Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-09-07T07:46:44.1756299Z * [new tag] v1.12.0 -> v1.12.0 2025-09-07T07:46:44.1756521Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-09-07T07:46:44.1756663Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-09-07T07:46:44.1756820Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-09-07T07:46:44.1756963Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-09-07T07:46:44.1757114Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-09-07T07:46:44.1757257Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-09-07T07:46:44.1757414Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-09-07T07:46:44.1757555Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-09-07T07:46:44.1757691Z * [new tag] v1.12.1 -> v1.12.1 2025-09-07T07:46:44.1757846Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-09-07T07:46:44.1757992Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-09-07T07:46:44.1758149Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-09-07T07:46:44.1758296Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-09-07T07:46:44.1758438Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-09-07T07:46:44.1758589Z * [new tag] v1.13.0 -> v1.13.0 2025-09-07T07:46:44.1758730Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-09-07T07:46:44.1758884Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-09-07T07:46:44.1759027Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-09-07T07:46:44.1759171Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-09-07T07:46:44.1759326Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-09-07T07:46:44.1759474Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-09-07T07:46:44.1759624Z * [new tag] v1.13.1 -> v1.13.1 2025-09-07T07:46:44.1759848Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-09-07T07:46:44.1759997Z * [new tag] v1.2.0 -> v1.2.0 2025-09-07T07:46:44.1760134Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-09-07T07:46:44.1760270Z * [new tag] v1.3.0 -> v1.3.0 2025-09-07T07:46:44.1760419Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-09-07T07:46:44.1760555Z * [new tag] v1.3.1 -> v1.3.1 2025-09-07T07:46:44.1760699Z * [new tag] v1.4.0 -> v1.4.0 2025-09-07T07:46:44.1760834Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-09-07T07:46:44.1760968Z * [new tag] v1.4.1 -> v1.4.1 2025-09-07T07:46:44.1761119Z * [new tag] v1.5.0 -> v1.5.0 2025-09-07T07:46:44.1761265Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-09-07T07:46:44.1761426Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-09-07T07:46:44.1761569Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-09-07T07:46:44.1761708Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-09-07T07:46:44.1761863Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-09-07T07:46:44.1761998Z * [new tag] v1.5.1 -> v1.5.1 2025-09-07T07:46:44.1762153Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-09-07T07:46:44.1762285Z * [new tag] v1.6.0 -> v1.6.0 2025-09-07T07:46:44.1762438Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-09-07T07:46:44.1762658Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-09-07T07:46:44.1762800Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-09-07T07:46:44.1762955Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-09-07T07:46:44.1763094Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-09-07T07:46:44.1763245Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-09-07T07:46:44.1763384Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-09-07T07:46:44.1763518Z * [new tag] v1.7.0 -> v1.7.0 2025-09-07T07:46:44.1763672Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-09-07T07:46:44.1763812Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-09-07T07:46:44.1763967Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-09-07T07:46:44.1764109Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-09-07T07:46:44.1764241Z * [new tag] v1.7.1 -> v1.7.1 2025-09-07T07:46:44.1764400Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-09-07T07:46:44.1764539Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-09-07T07:46:44.1764692Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-09-07T07:46:44.1764825Z * [new tag] v1.8.0 -> v1.8.0 2025-09-07T07:46:44.1764977Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-09-07T07:46:44.1765120Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-09-07T07:46:44.1765261Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-09-07T07:46:44.1765413Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-09-07T07:46:44.1765553Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-09-07T07:46:44.1765707Z * [new tag] v1.8.1 -> v1.8.1 2025-09-07T07:46:44.1765951Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-09-07T07:46:44.1766093Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-09-07T07:46:44.1766244Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-09-07T07:46:44.1766377Z * [new tag] v1.8.2 -> v1.8.2 2025-09-07T07:46:44.1766532Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-09-07T07:46:44.1766667Z * [new tag] v1.9.0 -> v1.9.0 2025-09-07T07:46:44.1766808Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-09-07T07:46:44.1766961Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-09-07T07:46:44.1767102Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-09-07T07:46:44.1767258Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-09-07T07:46:44.1767395Z * [new tag] v1.9.1 -> v1.9.1 2025-09-07T07:46:44.1767537Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-09-07T07:46:44.1767690Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-09-07T07:46:44.1767825Z * [new tag] v2.0.0 -> v2.0.0 2025-09-07T07:46:44.1767975Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-09-07T07:46:44.1768114Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-09-07T07:46:44.1768267Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-09-07T07:46:44.1768407Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-09-07T07:46:44.1768549Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-09-07T07:46:44.1768818Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-09-07T07:46:44.1768954Z * [new tag] v2.0.1 -> v2.0.1 2025-09-07T07:46:44.1769118Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-09-07T07:46:44.1769260Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-09-07T07:46:44.1769401Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-09-07T07:46:44.1769557Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-09-07T07:46:44.1769691Z * [new tag] v2.1.0 -> v2.1.0 2025-09-07T07:46:44.1769846Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-09-07T07:46:44.1769987Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-09-07T07:46:44.1770130Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-09-07T07:46:44.1770285Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-09-07T07:46:44.1770430Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-09-07T07:46:44.1770590Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-09-07T07:46:44.1770724Z * [new tag] v2.1.1 -> v2.1.1 2025-09-07T07:46:44.1770877Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-09-07T07:46:44.1771016Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-09-07T07:46:44.1771155Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-09-07T07:46:44.1771307Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-09-07T07:46:44.1771446Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-09-07T07:46:44.1771600Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-09-07T07:46:44.1771733Z * [new tag] v2.1.2 -> v2.1.2 2025-09-07T07:46:44.1771874Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-09-07T07:46:44.1772027Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-09-07T07:46:44.1772267Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-09-07T07:46:44.1772416Z * [new tag] v2.2.0 -> v2.2.0 2025-09-07T07:46:44.1772555Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-09-07T07:46:44.1772694Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-09-07T07:46:44.1772984Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-09-07T07:46:44.1773128Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-09-07T07:46:44.1773284Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-09-07T07:46:44.1773425Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-09-07T07:46:44.1773582Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-09-07T07:46:44.1773722Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-09-07T07:46:44.1773862Z * [new tag] v2.2.1 -> v2.2.1 2025-09-07T07:46:44.1774014Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-09-07T07:46:44.1774154Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-09-07T07:46:44.1774307Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-09-07T07:46:44.1774439Z * [new tag] v2.2.2 -> v2.2.2 2025-09-07T07:46:44.1774578Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-09-07T07:46:44.1774729Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-09-07T07:46:44.1774868Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-09-07T07:46:44.1775013Z * [new tag] v2.3.0 -> v2.3.0 2025-09-07T07:46:44.1775271Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-09-07T07:46:44.1775422Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-09-07T07:46:44.1775583Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-09-07T07:46:44.1775726Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-09-07T07:46:44.1775881Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-09-07T07:46:44.1776022Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-09-07T07:46:44.1776175Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-09-07T07:46:44.1776314Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-09-07T07:46:44.1776453Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-09-07T07:46:44.1776604Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-09-07T07:46:44.1776746Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-09-07T07:46:44.1776898Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-09-07T07:46:44.1777036Z * [new tag] v2.3.1 -> v2.3.1 2025-09-07T07:46:44.1777174Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-09-07T07:46:44.1777329Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-09-07T07:46:44.1777468Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-09-07T07:46:44.1777614Z * [new tag] v2.4.0 -> v2.4.0 2025-09-07T07:46:44.1777757Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-09-07T07:46:44.1777899Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-09-07T07:46:44.1778052Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-09-07T07:46:44.1778195Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-09-07T07:46:44.1778348Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-09-07T07:46:44.1778596Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-09-07T07:46:44.1778755Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-09-07T07:46:44.1778896Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-09-07T07:46:44.1779036Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-09-07T07:46:44.1779185Z * [new tag] v2.4.1 -> v2.4.1 2025-09-07T07:46:44.1779323Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-09-07T07:46:44.1779475Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-09-07T07:46:44.1779616Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-09-07T07:46:44.1779753Z * [new tag] v2.5.0 -> v2.5.0 2025-09-07T07:46:44.1779904Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-09-07T07:46:44.1780051Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-09-07T07:46:44.1780202Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-09-07T07:46:44.1780342Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-09-07T07:46:44.1780482Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-09-07T07:46:44.1780637Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-09-07T07:46:44.1780776Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-09-07T07:46:44.1780927Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-09-07T07:46:44.1781066Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-09-07T07:46:44.1781217Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-09-07T07:46:44.1781439Z * [new tag] v2.5.1 -> v2.5.1 2025-09-07T07:46:44.1781580Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-09-07T07:46:44.1781727Z * [new tag] v2.6.0 -> v2.6.0 2025-09-07T07:46:44.1781866Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-09-07T07:46:44.1782025Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-09-07T07:46:44.1782166Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-09-07T07:46:44.1782304Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-09-07T07:46:44.1782454Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-09-07T07:46:44.1782600Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-09-07T07:46:44.1782752Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-09-07T07:46:44.1782898Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-09-07T07:46:44.1783037Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-09-07T07:46:44.1783189Z * [new tag] v2.7.0 -> v2.7.0 2025-09-07T07:46:44.1783330Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-09-07T07:46:44.1783485Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-09-07T07:46:44.1783628Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-09-07T07:46:44.1783778Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-09-07T07:46:44.1783916Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-09-07T07:46:44.1784054Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-09-07T07:46:44.1784209Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-09-07T07:46:44.1784353Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-09-07T07:46:44.1784503Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-09-07T07:46:44.1784759Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-09-07T07:46:44.1784994Z * [new tag] v2.7.1 -> v2.7.1 2025-09-07T07:46:44.1785150Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-09-07T07:46:44.1785292Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-09-07T07:46:44.1785447Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-09-07T07:46:44.1785588Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-09-07T07:46:44.1785728Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-09-07T07:46:44.1785875Z * [new tag] v2.8.0 -> v2.8.0 2025-09-07T07:46:44.1786012Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-09-07T07:46:44.1786171Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-09-07T07:46:44.1786316Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-09-07T07:46:44.1786471Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-09-07T07:46:44.1786613Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-09-07T07:46:44.1786754Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-09-07T07:46:44.1786907Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-09-07T07:46:44.1787045Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-09-07T07:46:44.1787209Z * [new tag] whc_flight_1 -> whc_flight_1 2025-09-07T07:46:44.1787360Z * [new tag] whc_flight_2 -> whc_flight_2 2025-09-07T07:46:44.1787509Z * [new tag] whc_flight_4 -> whc_flight_4 2025-09-07T07:46:47.2207200Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:46:47.2237728Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:47.2242718Z ##[endgroup] 2025-09-07T07:46:47.2243231Z ##[group]Determining the checkout info 2025-09-07T07:46:47.2243747Z ##[endgroup] 2025-09-07T07:46:47.2247563Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:46:47.2331044Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:46:47.2367378Z ##[group]Checking out the ref 2025-09-07T07:46:47.2367900Z [command]/usr/bin/git checkout --progress 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You can look around, make experimental 2025-09-07T07:46:50.4370034Z changes and commit them, and you can discard any commits you make in this 2025-09-07T07:46:50.4370877Z state without impacting any branches by switching back to a branch. 2025-09-07T07:46:50.4371223Z 2025-09-07T07:46:50.4371434Z If you want to create a new branch to retain commits you create, you may 2025-09-07T07:46:50.4371954Z do so (now or later) by using -c with the switch command. Example: 2025-09-07T07:46:50.4372252Z 2025-09-07T07:46:50.4372381Z git switch -c 2025-09-07T07:46:50.4372581Z 2025-09-07T07:46:50.4372700Z Or undo this operation with: 2025-09-07T07:46:50.4373008Z 2025-09-07T07:46:50.4373098Z git switch - 2025-09-07T07:46:50.4373247Z 2025-09-07T07:46:50.4373486Z Turn off this advice by setting config variable advice.detachedHead to false 2025-09-07T07:46:50.4373855Z 2025-09-07T07:46:50.4374036Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:46:50.4478859Z ##[endgroup] 2025-09-07T07:46:50.4479331Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:46:50.4484535Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:46:50.4527640Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:46:50.4553827Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:46:50.4580493Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:46:50.4611011Z ##[endgroup] 2025-09-07T07:46:50.4611398Z ##[group]Fetching submodules 2025-09-07T07:46:50.4614814Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:46:50.4853941Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:46:50.5089817Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-09-07T07:46:50.5099593Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-09-07T07:46:50.5110831Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-09-07T07:46:50.5121855Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-09-07T07:46:50.5132391Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-09-07T07:46:50.5144310Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-09-07T07:46:50.5154793Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-09-07T07:46:50.5165953Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-09-07T07:46:50.5177488Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-09-07T07:46:50.5188430Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-09-07T07:46:50.5199908Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-09-07T07:46:50.5211504Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-09-07T07:46:50.5222872Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-09-07T07:46:50.5233906Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-09-07T07:46:50.5245151Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-09-07T07:46:50.5256911Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-09-07T07:46:50.5268399Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-09-07T07:46:50.5279878Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-09-07T07:46:50.5291153Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:46:50.5302361Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-09-07T07:46:50.5313921Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-09-07T07:46:50.5325154Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-09-07T07:46:50.5336786Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-09-07T07:46:50.5348406Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-09-07T07:46:50.5360171Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-09-07T07:46:50.5371642Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-09-07T07:46:50.5383326Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-09-07T07:46:50.5395246Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-09-07T07:46:50.5407417Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-09-07T07:46:50.5418763Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-09-07T07:46:50.5430877Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-09-07T07:46:50.5442944Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-09-07T07:46:50.5454746Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-09-07T07:46:50.5466299Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-09-07T07:46:50.5478582Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-09-07T07:46:50.5490545Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-09-07T07:46:50.5502975Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-09-07T07:46:50.5531473Z Cloning into '/home/bob/_work/pytorch/pytorch/android/libs/fbjni'... 2025-09-07T07:46:51.3560319Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/FP16'... 2025-09-07T07:46:51.6767880Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/FXdiv'... 2025-09-07T07:46:51.9692758Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/NNPACK'... 2025-09-07T07:46:52.3436242Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/NVTX'... 2025-09-07T07:46:52.8613368Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-09-07T07:46:54.2427462Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-09-07T07:47:13.9496779Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/aiter'... 2025-09-07T07:47:22.1064727Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/benchmark'... 2025-09-07T07:47:23.0259634Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-09-07T07:47:29.0417178Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-09-07T07:47:30.1221627Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-09-07T07:47:31.9636236Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-09-07T07:47:33.2285046Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/cutlass'... 2025-09-07T07:47:35.5004609Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm'... 2025-09-07T07:47:37.6652283Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/flash-attention'... 2025-09-07T07:47:38.3462418Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-09-07T07:47:39.7609001Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fmt'... 2025-09-07T07:47:40.9686266Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-09-07T07:47:41.4989417Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/gloo'... 2025-09-07T07:47:41.9956493Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/googletest'... 2025-09-07T07:47:43.0704660Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/ideep'... 2025-09-07T07:47:43.5548665Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/ittapi'... 2025-09-07T07:47:45.0264303Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto'... 2025-09-07T07:47:46.4411048Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kleidiai'... 2025-09-07T07:47:47.0160325Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/mimalloc'... 2025-09-07T07:47:48.2578102Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/nlohmann'... 2025-09-07T07:47:58.9607805Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/onnx'... 2025-09-07T07:48:02.1917400Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-09-07T07:48:12.7039984Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/pocketfft'... 2025-09-07T07:48:13.0798320Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/protobuf'... 2025-09-07T07:48:26.4265309Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/psimd'... 2025-09-07T07:48:27.0348616Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-09-07T07:48:27.3864294Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/pybind11'... 2025-09-07T07:48:28.3766528Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-09-07T07:48:28.8518955Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/sleef'... 2025-09-07T07:48:29.7742536Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-09-07T07:48:30.3318977Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:48:30.3445211Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:48:30.3539167Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:48:30.3787091Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:48:30.4582469Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:48:30.5165565Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:48:31.3002141Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:48:31.4612514Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:48:31.4646396Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:48:31.4673137Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-09-07T07:48:35.2252005Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:48:35.2557758Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:48:35.6087492Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:48:35.6593894Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:48:35.7635112Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:48:35.8086073Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:48:36.4878501Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:48:36.6321825Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:48:36.6354649Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-09-07T07:48:36.6363653Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:48:36.6373365Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:48:36.6383451Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-09-07T07:48:36.6393128Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-09-07T07:48:36.6403117Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:48:36.6413004Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-09-07T07:48:36.6440634Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-09-07T07:48:37.9866222Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-09-07T07:48:40.3210992Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-09-07T07:48:42.7847528Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-09-07T07:48:45.5114924Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-09-07T07:48:46.6365917Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-09-07T07:48:47.1016180Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-09-07T07:49:03.5992893Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:49:04.1786193Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:49:04.3114423Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:49:05.2184845Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:49:05.2844214Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:49:05.3136413Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:49:05.4276423Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:49:05.5218603Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:49:05.5632487Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:49:05.5986787Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:49:05.6014838Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-09-07T07:49:12.6440261Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-09-07T07:49:18.9696388Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:49:20.1282033Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:49:20.4257642Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:49:20.4756029Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:49:20.5396395Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:49:20.5835694Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:49:20.6571209Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:49:20.6876488Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:49:20.7053174Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-09-07T07:49:20.7077014Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-09-07T07:49:42.7904487Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:49:42.8223405Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:49:42.9430778Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:49:42.9611206Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:49:42.9938667Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:49:43.0108232Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:49:43.0135963Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-09-07T07:49:44.6384126Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-09-07T07:49:47.5566976Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-09-07T07:49:50.9449537Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:49:50.9982194Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:49:51.0245912Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:49:51.0740180Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:49:51.0990181Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:49:51.1422914Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:49:51.1711082Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:49:51.2078973Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:49:51.2460723Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:49:51.2490149Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-09-07T07:49:54.4794708Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-09-07T07:49:55.5938183Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-09-07T07:49:58.6939449Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-09-07T07:49:59.4833687Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-09-07T07:50:00.5142959Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-09-07T07:50:02.7891181Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-09-07T07:50:21.0583591Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-09-07T07:50:23.0657890Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:50:23.1082880Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:50:23.1704662Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:50:23.2018003Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:50:23.2251993Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:23.2282504Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-09-07T07:50:24.3496628Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:50:24.4236059Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:50:24.6029568Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:50:24.7236892Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:50:24.7664681Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:50:24.8328952Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:50:24.9148948Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:50:24.9798742Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:50:25.0290212Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:50:25.3125568Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:50:26.6593542Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:50:26.6823487Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:26.6850377Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'... 2025-09-07T07:50:28.7123079Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:50:28.7954691Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:50:28.8165143Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:28.8397245Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:28.8596419Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:28.8820559Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:28.9052295Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:28.9328723Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:28.9569728Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:28.9813591Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:28.9842149Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-09-07T07:50:30.0636755Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-09-07T07:50:32.6070263Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-09-07T07:50:34.1367973Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-09-07T07:50:50.2731397Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-09-07T07:50:51.1671574Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-09-07T07:50:52.5996185Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-09-07T07:50:53.6363916Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-09-07T07:51:04.9558707Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:51:05.0159137Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:51:05.0566564Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:51:05.3114325Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:51:05.3364288Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:51:05.3760868Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:51:05.4062352Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:51:05.4455062Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:05.4764011Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:05.4789936Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'... 2025-09-07T07:51:09.0182005Z Cloning into '/home/bob/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'... 2025-09-07T07:51:11.7962536Z Submodule path 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'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:25.5989285Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:25.6031700Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:25.6074390Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:25.6115267Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:25.6173362Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url" 2025-09-07T07:51:25.6411196Z Entering 'android/libs/fbjni' 2025-09-07T07:51:25.6453575Z file:/home/bob/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:51:25.6472232Z Entering 'third_party/FP16' 2025-09-07T07:51:25.6510436Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:51:25.6529173Z Entering 'third_party/FXdiv' 2025-09-07T07:51:25.6567994Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:51:25.6586628Z Entering 'third_party/NNPACK' 2025-09-07T07:51:25.6624911Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:51:25.6644263Z Entering 'third_party/NVTX' 2025-09-07T07:51:25.6681696Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:51:25.6701918Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:25.6740592Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:51:25.6758857Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:25.6797324Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:51:25.6832338Z Entering 'third_party/aiter' 2025-09-07T07:51:25.6871119Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:51:25.6890941Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:25.6928822Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:51:25.6957207Z Entering 'third_party/benchmark' 2025-09-07T07:51:25.7002128Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:25.7021870Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:25.7061947Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T07:51:25.7090376Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:25.7129546Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T07:51:25.7148134Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:25.7186169Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T07:51:25.7206411Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:25.7243149Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T07:51:25.7262371Z Entering 'third_party/cutlass' 2025-09-07T07:51:25.7303720Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config remote.origin.url 2025-09-07T07:51:25.7333874Z Entering 'third_party/fbgemm' 2025-09-07T07:51:25.7372271Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T07:51:25.7392931Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:25.7430861Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T07:51:25.7448975Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:25.7488486Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T07:51:25.7515653Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:25.7557198Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T07:51:25.7576258Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:25.7613679Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T07:51:25.7641934Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:25.7683766Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T07:51:25.7702180Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:25.7741835Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T07:51:25.7758971Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:25.7799205Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T07:51:25.7821035Z Entering 'third_party/flash-attention' 2025-09-07T07:51:25.7862480Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:51:25.7881403Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:25.7931796Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:51:25.7955784Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:25.7994192Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:51:25.8024326Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:25.8062971Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:51:25.8084153Z Entering 'third_party/fmt' 2025-09-07T07:51:25.8121842Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:51:25.8142292Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:25.8182506Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T07:51:25.8201054Z Entering 'third_party/gloo' 2025-09-07T07:51:25.8238496Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T07:51:25.8257935Z Entering 'third_party/googletest' 2025-09-07T07:51:25.8297209Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:25.8316463Z Entering 'third_party/ideep' 2025-09-07T07:51:25.8354452Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T07:51:25.8372215Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:25.8411831Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T07:51:25.8438001Z Entering 'third_party/ittapi' 2025-09-07T07:51:25.8480399Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:51:25.8500099Z Entering 'third_party/kineto' 2025-09-07T07:51:25.8537928Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:51:25.8555718Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:25.8596469Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:51:25.8614093Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:25.8654530Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:51:25.8673874Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:25.8711401Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T07:51:25.8729759Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:25.8770786Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:51:25.8788622Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:25.8830270Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T07:51:25.8847129Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:25.8889368Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T07:51:25.8908400Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:25.9224707Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T07:51:25.9243255Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:25.9283024Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:25.9303408Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:25.9350963Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T07:51:25.9370891Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:25.9418303Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:51:25.9438707Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:25.9484410Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:51:25.9504070Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:25.9544272Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:51:25.9564160Z Entering 'third_party/kleidiai' 2025-09-07T07:51:25.9602981Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:51:25.9622773Z Entering 'third_party/mimalloc' 2025-09-07T07:51:25.9663596Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:51:25.9681861Z Entering 'third_party/nlohmann' 2025-09-07T07:51:25.9721661Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:51:25.9742534Z Entering 'third_party/onnx' 2025-09-07T07:51:25.9784393Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:51:25.9822888Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:25.9863404Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:51:25.9884085Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:25.9926371Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T07:51:25.9947610Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:25.9987162Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:26.0005207Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:26.0042852Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:26.0060844Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:26.0098431Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config remote.origin.url 2025-09-07T07:51:26.0116053Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:26.0157490Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config remote.origin.url 2025-09-07T07:51:26.0176871Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:26.0214181Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config remote.origin.url 2025-09-07T07:51:26.0231064Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:26.0273497Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config remote.origin.url 2025-09-07T07:51:26.0291917Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:26.0330628Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config remote.origin.url 2025-09-07T07:51:26.0347449Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:26.0387845Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config remote.origin.url 2025-09-07T07:51:26.0407195Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:26.0446155Z 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http.https://github.com/.extraheader 2025-09-07T07:51:28.4048774Z Entering 'third_party/kineto' 2025-09-07T07:51:28.4074941Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4107716Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:28.4132046Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4166214Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:28.4191292Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4725092Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:28.4750136Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4785513Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:28.4810102Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4842340Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:28.4866906Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4903280Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:28.4927466Z http.https://github.com/.extraheader 2025-09-07T07:51:28.4961473Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:28.4985634Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5019851Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:28.5044592Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5079359Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:28.5104169Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5140506Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:28.5164858Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5200176Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:28.5225284Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5258778Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:28.5282698Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5317790Z Entering 'third_party/kleidiai' 2025-09-07T07:51:28.5342454Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5376284Z Entering 'third_party/mimalloc' 2025-09-07T07:51:28.5401048Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5432432Z Entering 'third_party/nlohmann' 2025-09-07T07:51:28.5457775Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5495367Z Entering 'third_party/onnx' 2025-09-07T07:51:28.5520851Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5574094Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:28.5598489Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5634680Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:28.5661112Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5695258Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:28.5718712Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5754417Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:28.5778033Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5810783Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:28.5834879Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5868688Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:28.5893662Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5929340Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:28.5958722Z http.https://github.com/.extraheader 2025-09-07T07:51:28.5996838Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:28.6022182Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6054010Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:28.6078026Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6110766Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:28.6135144Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6172224Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:28.6196001Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6233219Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:28.6258562Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6311439Z Entering 'third_party/pocketfft' 2025-09-07T07:51:28.6337585Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6368612Z Entering 'third_party/protobuf' 2025-09-07T07:51:28.6394252Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6430274Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:28.6453523Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6488731Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:28.6512849Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6547516Z Entering 'third_party/psimd' 2025-09-07T07:51:28.6571834Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6602820Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:28.6626921Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6658079Z Entering 'third_party/pybind11' 2025-09-07T07:51:28.6682387Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6713831Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:28.6738973Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6773728Z Entering 'third_party/sleef' 2025-09-07T07:51:28.6798114Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6831528Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:28.6857629Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6888691Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:28.6912230Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6942804Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:28.6966247Z http.https://github.com/.extraheader 2025-09-07T07:51:28.6996460Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:28.7021478Z http.https://github.com/.extraheader 2025-09-07T07:51:28.7051623Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:28.7075021Z http.https://github.com/.extraheader 2025-09-07T07:51:28.7104077Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:28.7127537Z http.https://github.com/.extraheader 2025-09-07T07:51:28.7179260Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:51:28.7218088Z ##[endgroup] 2025-09-07T07:51:28.7218511Z ##[group]Fetching the repository 2025-09-07T07:51:28.7225488Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:51:29.3045493Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:51:29.3069174Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:29.3073761Z ##[endgroup] 2025-09-07T07:51:29.3074174Z ##[group]Determining the checkout info 2025-09-07T07:51:29.3075123Z ##[endgroup] 2025-09-07T07:51:29.3078760Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:51:29.3287984Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:51:29.3317254Z ##[group]Checking out the ref 2025-09-07T07:51:29.3321944Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:29.3843012Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:51:29.3854416Z ##[endgroup] 2025-09-07T07:51:29.3854856Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:51:29.3859681Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:51:29.3896637Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:51:29.3921390Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:51:29.3952474Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:51:29.3975614Z ##[endgroup] 2025-09-07T07:51:29.3976364Z ##[group]Fetching submodules 2025-09-07T07:51:29.3979287Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:51:29.4237521Z Synchronizing submodule url for 'android/libs/fbjni' 2025-09-07T07:51:29.4259105Z Synchronizing submodule url for 'third_party/FP16' 2025-09-07T07:51:29.4282070Z Synchronizing submodule url for 'third_party/FXdiv' 2025-09-07T07:51:29.4305849Z Synchronizing submodule url for 'third_party/NNPACK' 2025-09-07T07:51:29.4329143Z Synchronizing submodule url for 'third_party/NVTX' 2025-09-07T07:51:29.4351751Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:29.4374552Z Synchronizing submodule url for 'third_party/XNNPACK' 2025-09-07T07:51:29.4412762Z Synchronizing submodule url for 'third_party/aiter' 2025-09-07T07:51:29.4437591Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:29.4469611Z Synchronizing submodule url for 'third_party/benchmark' 2025-09-07T07:51:29.4492614Z Synchronizing submodule url for 'third_party/composable_kernel' 2025-09-07T07:51:29.4524656Z Synchronizing submodule url for 'third_party/cpp-httplib' 2025-09-07T07:51:29.4547251Z Synchronizing submodule url for 'third_party/cpuinfo' 2025-09-07T07:51:29.4570246Z Synchronizing submodule url for 'third_party/cudnn_frontend' 2025-09-07T07:51:29.4593562Z Synchronizing submodule url for 'third_party/cutlass' 2025-09-07T07:51:29.4625794Z Synchronizing submodule url for 'third_party/fbgemm' 2025-09-07T07:51:29.4649971Z Synchronizing submodule url for 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:29.4669892Z Synchronizing submodule url for 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:29.4699051Z Synchronizing submodule url for 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:29.4720820Z Synchronizing submodule url for 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:29.4757038Z Synchronizing submodule url for 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:29.4770439Z Synchronizing submodule url for 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:29.4791302Z Synchronizing submodule url for 'third_party/fbgemm/external/json' 2025-09-07T07:51:29.4816316Z Synchronizing submodule url for 'third_party/flash-attention' 2025-09-07T07:51:29.4840293Z Synchronizing submodule url for 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:29.4868053Z Synchronizing submodule url for 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:29.4900810Z Synchronizing submodule url for 'third_party/flatbuffers' 2025-09-07T07:51:29.4925756Z Synchronizing submodule url for 'third_party/fmt' 2025-09-07T07:51:29.4948761Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:29.4970941Z Synchronizing submodule url for 'third_party/gloo' 2025-09-07T07:51:29.4994525Z Synchronizing submodule url for 'third_party/googletest' 2025-09-07T07:51:29.5017989Z Synchronizing submodule url for 'third_party/ideep' 2025-09-07T07:51:29.5039858Z Synchronizing submodule url for 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:29.5070200Z Synchronizing submodule url for 'third_party/ittapi' 2025-09-07T07:51:29.5096162Z Synchronizing submodule url for 'third_party/kineto' 2025-09-07T07:51:29.5118205Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:29.5142100Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:29.5163803Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:29.5186261Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:29.5207277Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:29.5227246Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:29.5248837Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:29.5270576Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:29.5290727Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:29.5313271Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:29.5335124Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:29.5355694Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:29.5379800Z Synchronizing submodule url for 'third_party/kleidiai' 2025-09-07T07:51:29.5402942Z Synchronizing submodule url for 'third_party/mimalloc' 2025-09-07T07:51:29.5427875Z Synchronizing submodule url for 'third_party/nlohmann' 2025-09-07T07:51:29.5451192Z Synchronizing submodule url for 'third_party/onnx' 2025-09-07T07:51:29.5495314Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:29.5520135Z Synchronizing submodule url for 'third_party/opentelemetry-cpp' 2025-09-07T07:51:29.5545039Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:29.5565101Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:29.5586538Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:29.5606591Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:29.5629003Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:29.5649294Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:29.5670026Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:29.5691529Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:29.5713095Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:29.5736266Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:29.5779922Z Synchronizing submodule url for 'third_party/pocketfft' 2025-09-07T07:51:29.5802366Z Synchronizing submodule url for 'third_party/protobuf' 2025-09-07T07:51:29.5831806Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:29.5851263Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:29.5876022Z Synchronizing submodule url for 'third_party/psimd' 2025-09-07T07:51:29.5899130Z Synchronizing submodule url for 'third_party/pthreadpool' 2025-09-07T07:51:29.5921462Z Synchronizing submodule url for 'third_party/pybind11' 2025-09-07T07:51:29.5945342Z Synchronizing submodule url for 'third_party/python-peachpy' 2025-09-07T07:51:29.5968056Z Synchronizing submodule url for 'third_party/sleef' 2025-09-07T07:51:29.5991769Z Synchronizing submodule url for 'third_party/tensorpipe' 2025-09-07T07:51:29.6015405Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:29.6034843Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:29.6055357Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:29.6074972Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:29.6096926Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:29.6129062Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:51:29.6507118Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:51:29.6630961Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:51:29.6722493Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:51:29.6963845Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:51:29.8063938Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:51:29.8452233Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:51:30.5790662Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:51:30.8231337Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:51:31.0625731Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 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'979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:51:34.0437233Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:51:34.2068128Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:51:34.4825728Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:51:34.5147353Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:51:34.5592591Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:51:34.5819971Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:51:34.6214313Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:51:34.6356181Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:51:35.6169951Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:51:35.6392599Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:51:35.7439092Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:51:35.9192980Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:51:36.0148715Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:51:36.0312495Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:51:36.0655465Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:51:36.0799226Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:51:36.0897137Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:51:36.1062065Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:51:36.1448718Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:51:36.2446856Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:51:36.2614741Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:51:36.2928808Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:51:36.3760788Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:51:36.4251674Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:51:36.4667296Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:51:36.5970707Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:51:36.8114673Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:51:36.8476567Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:51:36.9167239Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:51:36.9352454Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:51:36.9767366Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:51:36.9899438Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:51:37.1095439Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:51:37.1256553Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:51:37.1408703Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:51:37.1600376Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:51:37.4973883Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T07:51:37.5372014Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T07:51:38.0247709Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T07:51:38.0380529Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 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2025-09-07T07:51:38.9186437Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:38.9229960Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:38.9273225Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:38.9309418Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:38.9348407Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:38.9387211Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:38.9429618Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:38.9468451Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:38.9508610Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:38.9553822Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:38.9596182Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:38.9660214Z Entering 'third_party/pocketfft' 2025-09-07T07:51:38.9701927Z Entering 'third_party/protobuf' 2025-09-07T07:51:38.9750179Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:38.9788114Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:38.9829191Z Entering 'third_party/psimd' 2025-09-07T07:51:38.9875276Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:38.9916090Z Entering 'third_party/pybind11' 2025-09-07T07:51:38.9959390Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:39.0004142Z Entering 'third_party/sleef' 2025-09-07T07:51:39.0045048Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:39.0088904Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:39.0130194Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:39.0170124Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:39.0212150Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:39.0252527Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:39.0304068Z ##[endgroup] 2025-09-07T07:51:39.0304528Z ##[group]Persisting credentials for submodules 2025-09-07T07:51:39.0310809Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'url\.https\:\/\/github\.com\/\.insteadOf' && git config --local --unset-all 'url.https://github.com/.insteadOf' || :" 2025-09-07T07:51:39.0555382Z Entering 'android/libs/fbjni' 2025-09-07T07:51:39.0580777Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0581190Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0613814Z Entering 'third_party/FP16' 2025-09-07T07:51:39.0640048Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0640427Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0673060Z Entering 'third_party/FXdiv' 2025-09-07T07:51:39.0702759Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0703096Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0742568Z Entering 'third_party/NNPACK' 2025-09-07T07:51:39.0768795Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0769147Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0806407Z Entering 'third_party/NVTX' 2025-09-07T07:51:39.0831580Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0831964Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0869427Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:39.0896244Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0896613Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0928746Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:39.0955449Z url.https://github.com/.insteadof 2025-09-07T07:51:39.0955820Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1009771Z Entering 'third_party/aiter' 2025-09-07T07:51:39.1037312Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1037664Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1073114Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:39.1097983Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1098334Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1141031Z Entering 'third_party/benchmark' 2025-09-07T07:51:39.1167570Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1167922Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1201950Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:39.1229408Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1229769Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1272112Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:39.1298813Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1299288Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1331675Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:39.1358509Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1359092Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1391149Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:39.1417292Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1417636Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1455227Z Entering 'third_party/cutlass' 2025-09-07T07:51:39.1480383Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1480726Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1524516Z Entering 'third_party/fbgemm' 2025-09-07T07:51:39.1551009Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1551411Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1587468Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:39.1610897Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1611244Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1649667Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:39.1674737Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1675107Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1718883Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:39.1745600Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1745957Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1781872Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:39.1806302Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1806659Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1848306Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:39.1872616Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1872983Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1911212Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:39.1937641Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1938000Z url.https://github.com/.insteadof 2025-09-07T07:51:39.1975591Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:39.2001074Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2001412Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2038391Z Entering 'third_party/flash-attention' 2025-09-07T07:51:39.2066093Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2066457Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2100800Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:39.2125488Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2125830Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2165234Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:39.2190129Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2190488Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2234898Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:39.2261499Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2261852Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2302094Z Entering 'third_party/fmt' 2025-09-07T07:51:39.2327486Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2327836Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2359669Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:39.2385508Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2385915Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2424418Z Entering 'third_party/gloo' 2025-09-07T07:51:39.2451618Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2452000Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2485913Z Entering 'third_party/googletest' 2025-09-07T07:51:39.2512105Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2512455Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2546220Z Entering 'third_party/ideep' 2025-09-07T07:51:39.2572450Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2572967Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2604278Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:39.2629776Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2630148Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2670639Z Entering 'third_party/ittapi' 2025-09-07T07:51:39.2699033Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2699405Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2731781Z Entering 'third_party/kineto' 2025-09-07T07:51:39.2758021Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2758397Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2790319Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:39.2815747Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2816093Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2847836Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:39.2872644Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2872967Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2912456Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:39.2939793Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2940370Z url.https://github.com/.insteadof 2025-09-07T07:51:39.2976045Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:39.3001264Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3001627Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3033319Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:39.3059095Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3059433Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3090785Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:39.3116179Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3116558Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3150780Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:39.3177057Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3177457Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3210546Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:39.3236926Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3237325Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3269739Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:39.3294615Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3294988Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3329451Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:39.3353762Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3354106Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3389215Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:39.3414891Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3449496Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3449941Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:39.3474771Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3475146Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3510243Z Entering 'third_party/kleidiai' 2025-09-07T07:51:39.3537524Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3537889Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3576326Z Entering 'third_party/mimalloc' 2025-09-07T07:51:39.3601157Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3601507Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3637494Z Entering 'third_party/nlohmann' 2025-09-07T07:51:39.3663857Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3664208Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3698873Z Entering 'third_party/onnx' 2025-09-07T07:51:39.3724992Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3725344Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3778423Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:39.3803464Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3803841Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3839490Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:39.3866782Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3867178Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3902033Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:39.3927246Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3927643Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3964479Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:39.3989875Z url.https://github.com/.insteadof 2025-09-07T07:51:39.3990245Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4026606Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:39.4052057Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4052439Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4084137Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:39.4109984Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4110592Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4143386Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:39.4168864Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4169232Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4200644Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:39.4226413Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4226795Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4259146Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:39.4284114Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4284465Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4316730Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:39.4341387Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4341740Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4375929Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:39.4401786Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4402174Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4436903Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:39.4462354Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4462717Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4517407Z Entering 'third_party/pocketfft' 2025-09-07T07:51:39.4545115Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4545453Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4578092Z Entering 'third_party/protobuf' 2025-09-07T07:51:39.4604602Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4604962Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4640742Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:39.4666450Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4666802Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4701269Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:39.4726849Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4727446Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4767196Z Entering 'third_party/psimd' 2025-09-07T07:51:39.4792917Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4793268Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4830016Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:39.4856547Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4856951Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4889096Z Entering 'third_party/pybind11' 2025-09-07T07:51:39.4915739Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4916132Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4947755Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:39.4972974Z url.https://github.com/.insteadof 2025-09-07T07:51:39.4973317Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5010557Z Entering 'third_party/sleef' 2025-09-07T07:51:39.5036075Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5036428Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5070127Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:39.5095989Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5096336Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5128361Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:39.5154019Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5154372Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5190720Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:39.5216407Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5216777Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5247776Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:39.5272943Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5273289Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5307736Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:39.5334666Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5335021Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5366041Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:39.5390584Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5390954Z url.https://github.com/.insteadof 2025-09-07T07:51:39.5443538Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url" 2025-09-07T07:51:39.5688516Z Entering 'android/libs/fbjni' 2025-09-07T07:51:39.5727403Z file:/home/bob/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:51:39.5747095Z Entering 'third_party/FP16' 2025-09-07T07:51:39.5786176Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:51:39.5805640Z Entering 'third_party/FXdiv' 2025-09-07T07:51:39.5844842Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:51:39.5863089Z Entering 'third_party/NNPACK' 2025-09-07T07:51:39.5902821Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:51:39.5922750Z Entering 'third_party/NVTX' 2025-09-07T07:51:39.5962227Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:51:39.5982419Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:39.6026444Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:51:39.6045624Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:39.6091390Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:51:39.6127853Z Entering 'third_party/aiter' 2025-09-07T07:51:39.6167413Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:51:39.6187308Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:39.6234171Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:51:39.6263319Z Entering 'third_party/benchmark' 2025-09-07T07:51:39.6302874Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:39.6322157Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:39.6360890Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T07:51:39.6388690Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:39.6429085Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T07:51:39.6447098Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:39.6494085Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T07:51:39.6513480Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:39.6553957Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T07:51:39.6573215Z Entering 'third_party/cutlass' 2025-09-07T07:51:39.6612376Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config remote.origin.url 2025-09-07T07:51:39.6641618Z Entering 'third_party/fbgemm' 2025-09-07T07:51:39.6680900Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T07:51:39.6704096Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:39.6747465Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T07:51:39.6765354Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:39.6806389Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T07:51:39.6833056Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:39.6873518Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T07:51:39.6893486Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:39.6938747Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T07:51:39.6967241Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:39.7007379Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T07:51:39.7024755Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:39.7067138Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T07:51:39.7084996Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:39.7127519Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T07:51:39.7150997Z Entering 'third_party/flash-attention' 2025-09-07T07:51:39.7195237Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:51:39.7215157Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:39.7254493Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:51:39.7280254Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:39.7318288Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:51:39.7349672Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:39.7390697Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:51:39.7413531Z Entering 'third_party/fmt' 2025-09-07T07:51:39.7453470Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:51:39.7473016Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:39.7513200Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T07:51:39.7532499Z Entering 'third_party/gloo' 2025-09-07T07:51:39.7573188Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T07:51:39.7592397Z Entering 'third_party/googletest' 2025-09-07T07:51:39.7638247Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:39.7658473Z Entering 'third_party/ideep' 2025-09-07T07:51:39.7698157Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T07:51:39.7715502Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:39.7753936Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T07:51:39.7786449Z Entering 'third_party/ittapi' 2025-09-07T07:51:39.7828470Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:51:39.7848317Z Entering 'third_party/kineto' 2025-09-07T07:51:39.8274796Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:51:39.8295066Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:39.8336472Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:51:39.8354597Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:39.8395681Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:51:39.8414938Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:39.8454752Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T07:51:39.8472700Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:39.8510897Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:51:39.8529174Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:39.8568913Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T07:51:39.8586124Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:39.8625870Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T07:51:39.8646120Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:39.8685906Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T07:51:39.8704391Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:39.8746568Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:39.8765087Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:39.8803919Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T07:51:39.8823163Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:39.8862378Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:51:39.8882044Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:39.8926635Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:51:39.8945456Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:39.8989880Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:51:39.9009904Z Entering 'third_party/kleidiai' 2025-09-07T07:51:39.9050083Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:51:39.9069561Z Entering 'third_party/mimalloc' 2025-09-07T07:51:39.9109533Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:51:39.9127849Z Entering 'third_party/nlohmann' 2025-09-07T07:51:39.9166613Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:51:39.9186906Z Entering 'third_party/onnx' 2025-09-07T07:51:39.9225959Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:51:39.9264245Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:39.9303803Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:51:39.9325723Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:39.9366990Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T07:51:39.9387581Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:39.9425590Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:39.9442889Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:39.9480405Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:39.9499854Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:39.9541731Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config remote.origin.url 2025-09-07T07:51:39.9560072Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:39.9599168Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config remote.origin.url 2025-09-07T07:51:39.9620284Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:39.9658122Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config remote.origin.url 2025-09-07T07:51:39.9675676Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:39.9714340Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config remote.origin.url 2025-09-07T07:51:39.9731601Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:39.9769323Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config remote.origin.url 2025-09-07T07:51:39.9786728Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:39.9825308Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config remote.origin.url 2025-09-07T07:51:39.9844651Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:39.9887050Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/googletest/config remote.origin.url 2025-09-07T07:51:39.9907402Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:40.0023718Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/tools/vcpkg/config remote.origin.url 2025-09-07T07:51:40.0070063Z Entering 'third_party/pocketfft' 2025-09-07T07:51:40.0110055Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/pocketfft/config remote.origin.url 2025-09-07T07:51:40.0129777Z Entering 'third_party/protobuf' 2025-09-07T07:51:40.0172471Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/protobuf/config remote.origin.url 2025-09-07T07:51:40.0194204Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:40.0233865Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:40.0251517Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:40.0289859Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:40.0309479Z Entering 'third_party/psimd' 2025-09-07T07:51:40.0349672Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/psimd/config remote.origin.url 2025-09-07T07:51:40.0368161Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:40.0406675Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/pthreadpool/config remote.origin.url 2025-09-07T07:51:40.0425434Z Entering 'third_party/pybind11' 2025-09-07T07:51:40.0463651Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:51:40.0482549Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:40.0525683Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/python-peachpy/config remote.origin.url 2025-09-07T07:51:40.0543923Z Entering 'third_party/sleef' 2025-09-07T07:51:40.0582870Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/sleef/config remote.origin.url 2025-09-07T07:51:40.0601809Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:40.0644823Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/config remote.origin.url 2025-09-07T07:51:40.0663316Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:40.0701121Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:40.0718674Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:40.0757827Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libnop/config remote.origin.url 2025-09-07T07:51:40.0776365Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:40.0816339Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libuv/config remote.origin.url 2025-09-07T07:51:40.0834119Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:40.0871291Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:51:40.0887648Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:40.0927855Z file:/home/bob/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/modules/tools/clang/config remote.origin.url 2025-09-07T07:51:40.1152515Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'git@github.com:' 2025-09-07T07:51:40.1396526Z Entering 'android/libs/fbjni' 2025-09-07T07:51:40.1435796Z Entering 'third_party/FP16' 2025-09-07T07:51:40.1475168Z Entering 'third_party/FXdiv' 2025-09-07T07:51:40.1514317Z Entering 'third_party/NNPACK' 2025-09-07T07:51:40.1553337Z Entering 'third_party/NVTX' 2025-09-07T07:51:40.1593482Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:40.1632669Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:40.1689003Z Entering 'third_party/aiter' 2025-09-07T07:51:40.1727708Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:40.1775652Z Entering 'third_party/benchmark' 2025-09-07T07:51:40.1816198Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:40.1864644Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:40.1903758Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:40.1942186Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:40.1982117Z Entering 'third_party/cutlass' 2025-09-07T07:51:40.2033309Z Entering 'third_party/fbgemm' 2025-09-07T07:51:40.2075845Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:40.2113424Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:40.2159994Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:40.2197689Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:40.2244377Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:40.2282730Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:40.2322450Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:40.2368767Z Entering 'third_party/flash-attention' 2025-09-07T07:51:40.2409549Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:40.2455911Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:40.2503811Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:40.2546516Z Entering 'third_party/fmt' 2025-09-07T07:51:40.2586777Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:40.2627424Z Entering 'third_party/gloo' 2025-09-07T07:51:40.2667032Z Entering 'third_party/googletest' 2025-09-07T07:51:40.2707817Z Entering 'third_party/ideep' 2025-09-07T07:51:40.2745243Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:40.2792842Z Entering 'third_party/ittapi' 2025-09-07T07:51:40.2832313Z Entering 'third_party/kineto' 2025-09-07T07:51:40.2871636Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:40.2908428Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:40.2948670Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:40.2987656Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:40.3024962Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:40.3061049Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:40.3101894Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:40.3140827Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:40.3178833Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:40.3217762Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:40.3257770Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:40.3294804Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:40.3335367Z Entering 'third_party/kleidiai' 2025-09-07T07:51:40.3375465Z Entering 'third_party/mimalloc' 2025-09-07T07:51:40.3414493Z Entering 'third_party/nlohmann' 2025-09-07T07:51:40.3454366Z Entering 'third_party/onnx' 2025-09-07T07:51:40.3513918Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:40.3555251Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:40.3600361Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:40.3637359Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:40.3672698Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:40.3710131Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:40.3750510Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:40.3786785Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:40.3822304Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:40.3860128Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:40.3900520Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:40.3940397Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:40.4001607Z Entering 'third_party/pocketfft' 2025-09-07T07:51:40.4040126Z Entering 'third_party/protobuf' 2025-09-07T07:51:40.4083195Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:40.4119640Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:40.4160322Z Entering 'third_party/psimd' 2025-09-07T07:51:40.4199415Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:40.4238020Z Entering 'third_party/pybind11' 2025-09-07T07:51:40.4277554Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:40.4317120Z Entering 'third_party/sleef' 2025-09-07T07:51:40.4356342Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:40.4395146Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:40.4433182Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:40.4470583Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:40.4508764Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:40.4546334Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:40.4603009Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-09-07T07:51:40.4846359Z Entering 'android/libs/fbjni' 2025-09-07T07:51:40.4886299Z Entering 'third_party/FP16' 2025-09-07T07:51:40.4924690Z Entering 'third_party/FXdiv' 2025-09-07T07:51:40.4964261Z Entering 'third_party/NNPACK' 2025-09-07T07:51:40.5003428Z Entering 'third_party/NVTX' 2025-09-07T07:51:40.5043616Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:40.5083991Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:40.5140125Z Entering 'third_party/aiter' 2025-09-07T07:51:40.5180632Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:40.5229458Z Entering 'third_party/benchmark' 2025-09-07T07:51:40.5270310Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:40.5319823Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:40.5360443Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:40.5399266Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:40.5440832Z Entering 'third_party/cutlass' 2025-09-07T07:51:40.5491662Z Entering 'third_party/fbgemm' 2025-09-07T07:51:40.5538973Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:40.5577839Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:40.5624312Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:40.5669086Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:40.5711995Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:40.5751275Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:40.5788555Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:40.5832382Z Entering 'third_party/flash-attention' 2025-09-07T07:51:40.5874614Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:40.5919712Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:40.5968227Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:40.6012443Z Entering 'third_party/fmt' 2025-09-07T07:51:40.6051129Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:40.6089263Z Entering 'third_party/gloo' 2025-09-07T07:51:40.6128374Z Entering 'third_party/googletest' 2025-09-07T07:51:40.6168188Z Entering 'third_party/ideep' 2025-09-07T07:51:40.6206585Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:40.6252604Z Entering 'third_party/ittapi' 2025-09-07T07:51:40.6291180Z Entering 'third_party/kineto' 2025-09-07T07:51:40.6330023Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:40.6366501Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:40.6406170Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:40.6443840Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:40.6483732Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:40.6520793Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:40.6560097Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:40.6598530Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:40.6636344Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:40.6675387Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:40.6715054Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:40.6752861Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:40.6791613Z Entering 'third_party/kleidiai' 2025-09-07T07:51:40.6833002Z Entering 'third_party/mimalloc' 2025-09-07T07:51:40.6873113Z Entering 'third_party/nlohmann' 2025-09-07T07:51:40.6914546Z Entering 'third_party/onnx' 2025-09-07T07:51:40.6976282Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:40.7018717Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:40.7061340Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:40.7100429Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:40.7137780Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:40.7177697Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:40.7215841Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:40.7254511Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:40.7291324Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:40.7329436Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:40.7369267Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:40.7408868Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:40.7471930Z Entering 'third_party/pocketfft' 2025-09-07T07:51:40.7510585Z Entering 'third_party/protobuf' 2025-09-07T07:51:40.7553281Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:40.7590100Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:40.7630608Z Entering 'third_party/psimd' 2025-09-07T07:51:40.7669668Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:40.7708843Z Entering 'third_party/pybind11' 2025-09-07T07:51:40.7748371Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:40.7787956Z Entering 'third_party/sleef' 2025-09-07T07:51:40.7827399Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:40.7866553Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:40.7905370Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:40.7943084Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:40.7982100Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:40.8017663Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:40.8070404Z ##[endgroup] 2025-09-07T07:51:40.8113445Z [command]/usr/bin/git log -1 --format=%H 2025-09-07T07:51:40.8140297Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:40.8329392Z Prepare all required actions 2025-09-07T07:51:40.8329931Z Getting action download info 2025-09-07T07:51:41.1822816Z ##[group]Run ./.github/actions/setup-linux 2025-09-07T07:51:41.1823418Z env: 2025-09-07T07:51:41.1823803Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.1824241Z ##[endgroup] 2025-09-07T07:51:41.1885400Z ##[group]Run set -euo pipefail 2025-09-07T07:51:41.1885947Z set -euo pipefail 2025-09-07T07:51:41.1886405Z function get_ec2_metadata() { 2025-09-07T07:51:41.1887038Z  # Pulled from instance metadata endpoint for EC2 2025-09-07T07:51:41.1888150Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-09-07T07:51:41.1889131Z  category=$1 2025-09-07T07:51:41.1889805Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-09-07T07:51:41.1890619Z  runner_name_str=i-01a21955dc3821a00-1002 2025-09-07T07:51:41.1891338Z  if [[ -f /.inarc ]]; then 2025-09-07T07:51:41.1891916Z  echo "ARC Runner, no info on ec2 metadata" 2025-09-07T07:51:41.1892558Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-09-07T07:51:41.1893586Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-09-07T07:51:41.1894346Z  else 2025-09-07T07:51:41.1895957Z  curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}" 2025-09-07T07:51:41.1897580Z  fi 2025-09-07T07:51:41.1897945Z } 2025-09-07T07:51:41.1898403Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-09-07T07:51:41.1899090Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-09-07T07:51:41.1899914Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-09-07T07:51:41.1900656Z echo "system info $(uname -a)" 2025-09-07T07:51:41.1920917Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:41.1921588Z env: 2025-09-07T07:51:41.1921974Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.1922442Z ##[endgroup] 2025-09-07T07:51:41.1969941Z ami-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:41.1975551Z instance-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:41.1980113Z instance-type: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:41.1990301Z system info Linux 19cef9d253c5 6.5.0-1024-aws #24~22.04.1-Ubuntu SMP Thu Jul 18 10:43:12 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux 2025-09-07T07:51:41.2009437Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:51:41.2010415Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:51:41.2023284Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:41.2023686Z env: 2025-09-07T07:51:41.2023892Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.2024153Z ##[endgroup] 2025-09-07T07:51:41.2128066Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T07:51:41.2128633Z with: 2025-09-07T07:51:41.2128977Z shell: bash 2025-09-07T07:51:41.2129373Z timeout_minutes: 5 2025-09-07T07:51:41.2129808Z max_attempts: 3 2025-09-07T07:51:41.2130234Z retry_wait_seconds: 30 2025-09-07T07:51:41.2135301Z command: AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\") aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" # For LF Runners we need to make sure we also login to Meta's ECR docker registry too. META_AWS_ACCOUNT_ID=308535385114 if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" fi 2025-09-07T07:51:41.2139599Z polling_interval_seconds: 1 2025-09-07T07:51:41.2140146Z warning_on_retry: true 2025-09-07T07:51:41.2140622Z continue_on_error: false 2025-09-07T07:51:41.2141034Z env: 2025-09-07T07:51:41.2141427Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.2141880Z AWS_RETRY_MODE: standard 2025-09-07T07:51:41.2142341Z AWS_MAX_ATTEMPTS: 5 2025-09-07T07:51:41.2142766Z AWS_DEFAULT_REGION: us-east-1 2025-09-07T07:51:41.2143236Z ##[endgroup] 2025-09-07T07:51:42.9345216Z 2025-09-07T07:51:42.9345848Z WARNING! Your credentials are stored unencrypted in '/home/bob/.docker/config.json'. 2025-09-07T07:51:42.9346498Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:42.9346967Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:42.9347218Z 2025-09-07T07:51:42.9347325Z Login Succeeded 2025-09-07T07:51:43.2964873Z Command completed after 1 attempt(s). 2025-09-07T07:51:43.3060377Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:43.3060931Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:43.3061409Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:43.3074560Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:43.3074961Z env: 2025-09-07T07:51:43.3075184Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:43.3075451Z ##[endgroup] 2025-09-07T07:51:43.3255089Z ##[group]Run set +e 2025-09-07T07:51:43.3255404Z set +e 2025-09-07T07:51:43.3255635Z set -x 2025-09-07T07:51:43.3255860Z  2025-09-07T07:51:43.3256090Z PT_DOMAIN=download.pytorch.org 2025-09-07T07:51:43.3256695Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-09-07T07:51:43.3257480Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-09-07T07:51:43.3258255Z # one is returned at random 2025-09-07T07:51:43.3258661Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-09-07T07:51:43.3259036Z  2025-09-07T07:51:43.3259267Z if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:51:43.3259712Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-09-07T07:51:43.3260250Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-09-07T07:51:43.3260639Z  2025-09-07T07:51:43.3260875Z  if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:51:43.3261268Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-09-07T07:51:43.3261641Z  exit 1 2025-09-07T07:51:43.3261873Z  fi 2025-09-07T07:51:43.3262074Z fi 2025-09-07T07:51:43.3262278Z  2025-09-07T07:51:43.3262540Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-09-07T07:51:43.3262918Z  # Clean up any old records first 2025-09-07T07:51:43.3263286Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-09-07T07:51:43.3263620Z fi 2025-09-07T07:51:43.3263828Z  2025-09-07T07:51:43.3264138Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-09-07T07:51:43.3264669Z cat /etc/hosts 2025-09-07T07:51:43.3277337Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:43.3277757Z env: 2025-09-07T07:51:43.3277978Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:43.3278249Z ##[endgroup] 2025-09-07T07:51:43.3373585Z + PT_DOMAIN=download.pytorch.org 2025-09-07T07:51:43.3379472Z ++ dig -4 +short download.pytorch.org 2025-09-07T07:51:43.3380765Z ++ tail -n1 2025-09-07T07:51:43.3578198Z + RESOLVED_IP=3.170.131.53 2025-09-07T07:51:43.3578496Z + '[' -z 3.170.131.53 ']' 2025-09-07T07:51:43.3578787Z + grep -r download.pytorch.org /etc/hosts 2025-09-07T07:51:43.3591601Z + echo '3.170.131.53 download.pytorch.org' 2025-09-07T07:51:43.3593019Z + sudo tee -a /etc/hosts 2025-09-07T07:51:43.3651997Z 3.170.131.53 download.pytorch.org 2025-09-07T07:51:43.3664341Z + cat /etc/hosts 2025-09-07T07:51:43.3671879Z 127.0.0.1 localhost 2025-09-07T07:51:43.3676893Z ::1 localhost ip6-localhost ip6-loopback 2025-09-07T07:51:43.3677268Z fe00:: ip6-localnet 2025-09-07T07:51:43.3677520Z ff00:: ip6-mcastprefix 2025-09-07T07:51:43.3677780Z ff02::1 ip6-allnodes 2025-09-07T07:51:43.3678015Z ff02::2 ip6-allrouters 2025-09-07T07:51:43.3678263Z 172.17.0.2 19cef9d253c5 2025-09-07T07:51:43.3678528Z 3.170.131.53 download.pytorch.org 2025-09-07T07:51:43.3748200Z ##[group]Run set +x 2025-09-07T07:51:43.3748492Z set +x 2025-09-07T07:51:43.3748720Z  2025-09-07T07:51:43.3748935Z max_attempts=30 2025-09-07T07:51:43.3749204Z delay=10 2025-09-07T07:51:43.3749443Z attempt=1 2025-09-07T07:51:43.3749685Z  2025-09-07T07:51:43.3749933Z for attempt in $(seq 1 $max_attempts); do 2025-09-07T07:51:43.3750486Z  echo "Attempt $attempt of $max_attempts: Checking if Docker daemon is running..." 2025-09-07T07:51:43.3751029Z  if docker info > /dev/null 2>&1; then 2025-09-07T07:51:43.3765591Z  echo "Docker is running. Proceeding with the next steps" 2025-09-07T07:51:43.3766026Z  exit 0 2025-09-07T07:51:43.3766258Z  else 2025-09-07T07:51:43.3766528Z  echo "Docker is not running yet." 2025-09-07T07:51:43.3766904Z  echo "Retrying in $delay seconds..." 2025-09-07T07:51:43.3767252Z  sleep $delay 2025-09-07T07:51:43.3767499Z  fi 2025-09-07T07:51:43.3767715Z done 2025-09-07T07:51:43.3768069Z echo "Reached maximum attempts to connect to Docker. Exiting." 2025-09-07T07:51:43.3768503Z exit 1 2025-09-07T07:51:43.3781478Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:43.3781856Z env: 2025-09-07T07:51:43.3782083Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:43.3782354Z ##[endgroup] 2025-09-07T07:51:43.3873443Z Attempt 1 of 30: Checking if Docker daemon is running... 2025-09-07T07:51:43.4267406Z Docker is running. Proceeding with the next steps 2025-09-07T07:51:43.4537204Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-09-07T07:51:43.4537700Z with: 2025-09-07T07:51:43.4538645Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.4539699Z use-custom-docker-registry: true 2025-09-07T07:51:43.4540004Z docker-build-dir: .ci/docker 2025-09-07T07:51:43.4540300Z docker-build-script: ./build.sh 2025-09-07T07:51:43.4540601Z working-directory: . 2025-09-07T07:51:43.4540953Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:43.4541361Z force-push: false 2025-09-07T07:51:43.4541576Z env: 2025-09-07T07:51:43.4541787Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:43.4542061Z ##[endgroup] 2025-09-07T07:51:43.4909129Z ##[group]Run set -ex 2025-09-07T07:51:43.4909490Z set -ex 2025-09-07T07:51:43.4909721Z  2025-09-07T07:51:43.4910190Z # If the docker build directory or the build script doesn't exist, the action will 2025-09-07T07:51:43.4910884Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-09-07T07:51:43.4911463Z # job could then download the pre-built image as usual 2025-09-07T07:51:43.4912181Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-09-07T07:51:43.4912844Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4913185Z else 2025-09-07T07:51:43.4913451Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4913892Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4914319Z  2025-09-07T07:51:43.4914897Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-09-07T07:51:43.4915548Z  exit 0 2025-09-07T07:51:43.4915759Z fi 2025-09-07T07:51:43.4915966Z  2025-09-07T07:51:43.4916308Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-09-07T07:51:43.4916929Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-09-07T07:51:43.4917481Z  # use it as it is, but first let's extract the tag 2025-09-07T07:51:43.4917966Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-09-07T07:51:43.4918489Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4918993Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4919408Z else 2025-09-07T07:51:43.4919679Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-09-07T07:51:43.4920056Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-09-07T07:51:43.4920463Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-09-07T07:51:43.4920808Z  fi 2025-09-07T07:51:43.4921271Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-09-07T07:51:43.4921890Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4922554Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4923283Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.4923726Z fi 2025-09-07T07:51:43.4937040Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:43.4937444Z env: 2025-09-07T07:51:43.4937652Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:43.4938158Z REPO_NAME: pytorch 2025-09-07T07:51:43.4939367Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.4940397Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:51:43.4940683Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-09-07T07:51:43.4941071Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:43.4941483Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-09-07T07:51:43.4941784Z CUSTOM_TAG_PREFIX: 2025-09-07T07:51:43.4942052Z ##[endgroup] 2025-09-07T07:51:43.4981405Z + [[ -d .ci/docker ]] 2025-09-07T07:51:43.4981704Z + [[ -f .ci/docker/./build.sh ]] 2025-09-07T07:51:43.4982002Z + [[ true == \t\r\u\e ]] 2025-09-07T07:51:43.4982260Z + echo skip=false 2025-09-07T07:51:43.4983483Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 == *\3\0\8\5\3\5\3\8\5\1\1\4\.\d\k\r\.\e\c\r\.\u\s\-\e\a\s\t\-\1\.\a\m\a\z\o\n\a\w\s\.\c\o\m\/\p\y\t\o\r\c\h* ]] 2025-09-07T07:51:43.4989331Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.4990322Z ++ awk -F '[:,]' '{print $2}' 2025-09-07T07:51:43.5001720Z + DOCKER_TAG=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.5002884Z + echo docker-tag=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.5004487Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.5175599Z ##[group]Run set +e 2025-09-07T07:51:43.5175951Z set +e 2025-09-07T07:51:43.5176209Z set -x 2025-09-07T07:51:43.5176435Z  2025-09-07T07:51:43.5176631Z login() { 2025-09-07T07:51:43.5177130Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:51:43.5177662Z } 2025-09-07T07:51:43.5177870Z  2025-09-07T07:51:43.5178065Z retry () { 2025-09-07T07:51:43.5178342Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:51:43.5178660Z } 2025-09-07T07:51:43.5178866Z  2025-09-07T07:51:43.5179084Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:51:43.5179395Z  2025-09-07T07:51:43.5179617Z START_TIME=$(date +%s) 2025-09-07T07:51:43.5179913Z # Wait up to 120 minutes 2025-09-07T07:51:43.5180273Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-09-07T07:51:43.5180826Z  # Check if image already exists, if it does then skip building it 2025-09-07T07:51:43.5181364Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-09-07T07:51:43.5181737Z  exit 0 2025-09-07T07:51:43.5182010Z  fi 2025-09-07T07:51:43.5182255Z  2025-09-07T07:51:43.5182685Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-09-07T07:51:43.5183429Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-09-07T07:51:43.5184146Z  # latter, it will wait for the Docker images to become available before continuing 2025-09-07T07:51:43.5184828Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-09-07T07:51:43.5185261Z  # It's a Docker build job, let's build the image 2025-09-07T07:51:43.5185604Z  break 2025-09-07T07:51:43.5185843Z  else 2025-09-07T07:51:43.5186195Z  # It's a regular build job, wait for the image to become available 2025-09-07T07:51:43.5186666Z  sleep 300 2025-09-07T07:51:43.5187146Z  fi 2025-09-07T07:51:43.5187370Z done 2025-09-07T07:51:43.5187587Z  2025-09-07T07:51:43.5188109Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-09-07T07:51:43.5188705Z # be empty. The default action would be to continue rebuild the image 2025-09-07T07:51:43.5189225Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-09-07T07:51:43.5189699Z  # if we're on the base branch then use the parent commit 2025-09-07T07:51:43.5190114Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-09-07T07:51:43.5190441Z else 2025-09-07T07:51:43.5190762Z  # otherwise we're on a PR, so use the most recent base commit 2025-09-07T07:51:43.5191252Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-09-07T07:51:43.5191621Z fi 2025-09-07T07:51:43.5191832Z  2025-09-07T07:51:43.5192049Z if [[ -z "${MERGE_BASE}" ]]; then 2025-09-07T07:51:43.5192415Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.5192747Z  2025-09-07T07:51:43.5193227Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-09-07T07:51:43.5193792Z  exit 0 2025-09-07T07:51:43.5194002Z fi 2025-09-07T07:51:43.5194203Z  2025-09-07T07:51:43.5194508Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-09-07T07:51:43.5195217Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-09-07T07:51:43.5195807Z  exit 1 2025-09-07T07:51:43.5196032Z fi 2025-09-07T07:51:43.5196242Z  2025-09-07T07:51:43.5196611Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-09-07T07:51:43.5197285Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-09-07T07:51:43.5197916Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-09-07T07:51:43.5198620Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-09-07T07:51:43.5199419Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-09-07T07:51:43.5199889Z fi 2025-09-07T07:51:43.5200085Z  2025-09-07T07:51:43.5200344Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:43.5213314Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:43.5213710Z env: 2025-09-07T07:51:43.5213936Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:43.5214204Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:51:43.5214550Z BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:43.5215622Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.5217057Z DOCKER_TAG: pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.5217885Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:43.5218271Z DOCKER_PUSH: 2025-09-07T07:51:43.5218503Z ##[endgroup] 2025-09-07T07:51:43.5269982Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:43.5270432Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:43.5273012Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:51:43.5274622Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:44.4256109Z 2025-09-07T07:51:44.4256768Z WARNING! Your credentials are stored unencrypted in '/home/bob/.docker/config.json'. 2025-09-07T07:51:44.4257413Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:44.4258294Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:44.4258722Z Login Succeeded 2025-09-07T07:51:44.4277600Z 2025-09-07T07:51:44.4277887Z ++ date +%s 2025-09-07T07:51:44.4287204Z + START_TIME=1757231504 2025-09-07T07:51:44.4290587Z ++ date +%s 2025-09-07T07:51:44.4299405Z + [[ 1757224304 -lt 1757231504 ]] 2025-09-07T07:51:44.4300493Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:44.8204235Z { 2025-09-07T07:51:44.8204529Z "schemaVersion": 2, 2025-09-07T07:51:44.8204971Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-09-07T07:51:44.8205432Z "config": { 2025-09-07T07:51:44.8205782Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-09-07T07:51:44.8206200Z "size": 31375, 2025-09-07T07:51:44.8206623Z "digest": "sha256:29d1d8a31b215537637bab7c99e18c255840b899cf7023e4e3cb5efa3270aef8" 2025-09-07T07:51:44.8207133Z }, 2025-09-07T07:51:44.8207334Z "layers": [ 2025-09-07T07:51:44.8207546Z { 2025-09-07T07:51:44.8207884Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8208312Z "size": 30448359, 2025-09-07T07:51:44.8208745Z "digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46" 2025-09-07T07:51:44.8209235Z }, 2025-09-07T07:51:44.8209429Z { 2025-09-07T07:51:44.8209750Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8210172Z "size": 1554, 2025-09-07T07:51:44.8210587Z "digest": "sha256:171dcef20c49de4bc9268f60e02f111b72c638b0f24c3c5636c5013029db6d30" 2025-09-07T07:51:44.8211068Z }, 2025-09-07T07:51:44.8211247Z { 2025-09-07T07:51:44.8211575Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8211997Z "size": 313297922, 2025-09-07T07:51:44.8212432Z "digest": "sha256:4c92b3f72f1df31fe9f487fc1c27fcf1ba475ffb43abd69056306d1247786e40" 2025-09-07T07:51:44.8213145Z }, 2025-09-07T07:51:44.8213336Z { 2025-09-07T07:51:44.8213668Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8214090Z "size": 792, 2025-09-07T07:51:44.8214490Z "digest": "sha256:744f9ba90a6582eb601b3c20409bb10d6dad635dd118c3975f79721f4c82747c" 2025-09-07T07:51:44.8214972Z }, 2025-09-07T07:51:44.8215165Z { 2025-09-07T07:51:44.8215490Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8215897Z "size": 106, 2025-09-07T07:51:44.8216297Z "digest": "sha256:d3c08322a3326e45849dd80264a047c4f42ba4a2419d35c919542e2890e23934" 2025-09-07T07:51:44.8216767Z }, 2025-09-07T07:51:44.8216956Z { 2025-09-07T07:51:44.8217266Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8217680Z "size": 704, 2025-09-07T07:51:44.8218095Z "digest": "sha256:ffd43b71f3ccf3ba563606231cb1d191eb9dd0052f422d54835e6af350525170" 2025-09-07T07:51:44.8218579Z }, 2025-09-07T07:51:44.8218754Z { 2025-09-07T07:51:44.8219082Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8219506Z "size": 1215, 2025-09-07T07:51:44.8219915Z "digest": "sha256:830692b57f6e2758398ec80c3b67a20441d12696b54ed14f2ecebf926198f7d6" 2025-09-07T07:51:44.8220374Z }, 2025-09-07T07:51:44.8220566Z { 2025-09-07T07:51:44.8220892Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8221312Z "size": 482, 2025-09-07T07:51:44.8221702Z "digest": "sha256:5bad36d184686719399be50830a98939d7dbda2313fb407df5915217483fc6a3" 2025-09-07T07:51:44.8222172Z }, 2025-09-07T07:51:44.8222362Z { 2025-09-07T07:51:44.8222683Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8223095Z "size": 110343614, 2025-09-07T07:51:44.8223534Z "digest": "sha256:0e34fdd9ac5c39eb0a9d2c2d258b26f42bb79d7dc0a22014bf201daa2e033eb4" 2025-09-07T07:51:44.8224021Z }, 2025-09-07T07:51:44.8964241Z + exit 0 2025-09-07T07:51:44.8964439Z { 2025-09-07T07:51:44.8964804Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8965411Z "size": 4786, 2025-09-07T07:51:44.8965851Z "digest": "sha256:3c868a62868ef54f82ac11be8dabe1b4365d000bacfe4c104e08022fc96dd767" 2025-09-07T07:51:44.8966338Z }, 2025-09-07T07:51:44.8966532Z { 2025-09-07T07:51:44.8966864Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8967284Z "size": 1710, 2025-09-07T07:51:44.8967690Z "digest": "sha256:62170a22dd571d55ffccac64c0be17f4006d2498cfbf7c6289325f0899cba005" 2025-09-07T07:51:44.8968174Z }, 2025-09-07T07:51:44.8968367Z { 2025-09-07T07:51:44.8968696Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:44.8969104Z "size": 724, 2025-09-07T07:51:44.8969524Z "digest": 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"sha256:bc127046d33a7a98563698411b54ece8a167d520922879d7b69e8ca73a12d034" 2025-09-07T07:51:45.2597762Z }, 2025-09-07T07:51:45.2597942Z { 2025-09-07T07:51:45.2598271Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2598693Z "size": 32, 2025-09-07T07:51:45.2599117Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:45.2599643Z }, 2025-09-07T07:51:45.2599832Z { 2025-09-07T07:51:45.2600163Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2600587Z "size": 104, 2025-09-07T07:51:45.2600981Z "digest": "sha256:951e8ce838415c4257680a9d60d216f3750cbb18d243d9a21e2008cce7e589cf" 2025-09-07T07:51:45.2601462Z }, 2025-09-07T07:51:45.2601656Z { 2025-09-07T07:51:45.2601988Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2602401Z "size": 408, 2025-09-07T07:51:45.2602820Z "digest": "sha256:32340b97ae50ba7b2918ab40d6f4a8db875afee69318f484e4deb0a1e2ec4beb" 2025-09-07T07:51:45.2603301Z }, 2025-09-07T07:51:45.2603492Z { 2025-09-07T07:51:45.2603802Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2604219Z "size": 32, 2025-09-07T07:51:45.2604630Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:45.2605111Z }, 2025-09-07T07:51:45.2605284Z { 2025-09-07T07:51:45.2605608Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2606027Z "size": 109, 2025-09-07T07:51:45.2606453Z "digest": "sha256:5bbb04cd6b57ae13d7cf05ab9e9b4ed9752833ee2dba4eeaac47bde6022c4725" 2025-09-07T07:51:45.2606935Z }, 2025-09-07T07:51:45.2607122Z { 2025-09-07T07:51:45.2607455Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2607894Z "size": 1897, 2025-09-07T07:51:45.2608314Z "digest": "sha256:d8c4b845cfc7ca7cc0604f472bf6da8b1f1d4e98dff3c76e1985a7013a5b9e3f" 2025-09-07T07:51:45.2608807Z }, 2025-09-07T07:51:45.2608992Z { 2025-09-07T07:51:45.2620874Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2621344Z "size": 243440375, 2025-09-07T07:51:45.2621795Z "digest": "sha256:b35c180f4d8ddc2396eac4a6b893f438481a8163ceb0b88f203488bc5f2a8ba4" 2025-09-07T07:51:45.2622405Z }, 2025-09-07T07:51:45.2622588Z { 2025-09-07T07:51:45.2622928Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2623358Z "size": 106, 2025-09-07T07:51:45.2623778Z "digest": "sha256:5f967b3c303a99e609441551f7c8988cca4fd464c0c3127506bff8509583091b" 2025-09-07T07:51:45.2624241Z }, 2025-09-07T07:51:45.2624430Z { 2025-09-07T07:51:45.2624855Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2625291Z "size": 166, 2025-09-07T07:51:45.2625691Z "digest": "sha256:04770904f012e5584f1c19a0bc92d9863baaebf08bf75b4a9981f2b7795c8953" 2025-09-07T07:51:45.2626175Z }, 2025-09-07T07:51:45.2626363Z { 2025-09-07T07:51:45.2626687Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2627095Z "size": 7943, 2025-09-07T07:51:45.2627510Z "digest": "sha256:73373941fb321b4cb4a171b1423a68a4c7fedada3a1498868d7efe93cb03170e" 2025-09-07T07:51:45.2627991Z }, 2025-09-07T07:51:45.2628184Z { 2025-09-07T07:51:45.2628495Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2628912Z "size": 8072, 2025-09-07T07:51:45.2629324Z "digest": "sha256:9572e6cd907bfa4888456dbccc6e22146a0044374585f3fa0a8ced19b831ed62" 2025-09-07T07:51:45.2629806Z }, 2025-09-07T07:51:45.2629980Z { 2025-09-07T07:51:45.2630304Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2630717Z "size": 304, 2025-09-07T07:51:45.2631398Z "digest": "sha256:64a544aba233551e38898f138dd6ba3161ccdb9554e0ffb5b9d8f0f7fe4a7fa8" 2025-09-07T07:51:45.2631877Z }, 2025-09-07T07:51:45.2632048Z { 2025-09-07T07:51:45.2632556Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2632979Z "size": 13362696, 2025-09-07T07:51:45.2633376Z "digest": "sha256:7e35418a24997de5428763c93826679486760a1a9563209ae64de66ba45f99c1" 2025-09-07T07:51:45.2633842Z }, 2025-09-07T07:51:45.2634030Z { 2025-09-07T07:51:45.2634345Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2634763Z "size": 108, 2025-09-07T07:51:45.2635158Z "digest": "sha256:2ed8e82748d4a1131f41d9e41322f47a6ffef67a5a2b7bf5392237db5c035c61" 2025-09-07T07:51:45.2635638Z }, 2025-09-07T07:51:45.2635826Z { 2025-09-07T07:51:45.2636136Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2636551Z "size": 54145663, 2025-09-07T07:51:45.2636977Z "digest": "sha256:c988fbcccd708fb158a81c429d32e1060a7e40924fc3c987c629fa69d9484717" 2025-09-07T07:51:45.2637456Z }, 2025-09-07T07:51:45.2637640Z { 2025-09-07T07:51:45.2637953Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:45.2638369Z "size": 32, 2025-09-07T07:51:45.2638774Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:45.2639256Z } 2025-09-07T07:51:45.2639428Z ] 2025-09-07T07:51:45.2639608Z } 2025-09-07T07:51:45.2983777Z ##[group]Run set -eux 2025-09-07T07:51:45.2984081Z set -eux 2025-09-07T07:51:45.2984518Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-09-07T07:51:45.2985842Z aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token | jq --raw-output '.SecretString' | jq -r .docker_hub_readonly_token | docker login --username pytorchbot --password-stdin || true 2025-09-07T07:51:45.3000712Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:45.3001121Z env: 2025-09-07T07:51:45.3001350Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:45.3001617Z ##[endgroup] 2025-09-07T07:51:45.3077924Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-09-07T07:51:45.3078767Z + jq --raw-output .SecretString 2025-09-07T07:51:45.3080128Z + jq -r .docker_hub_readonly_token 2025-09-07T07:51:45.3081745Z + docker login --username pytorchbot --password-stdin 2025-09-07T07:51:45.9861411Z 2025-09-07T07:51:45.9863347Z An error occurred (AccessDeniedException) when calling the GetSecretValue operation: User: arn:aws:sts::308535385114:assumed-role/gh-ci-github-action-runners-runner-role/i-01a21955dc3821a00 is not authorized to perform: secretsmanager:GetSecretValue on resource: docker_hub_readonly_token because no identity-based policy allows the secretsmanager:GetSecretValue action 2025-09-07T07:51:46.1088032Z Error: Cannot perform an interactive login from a non TTY device 2025-09-07T07:51:46.1103158Z + true 2025-09-07T07:51:46.1395624Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:51:46.1396028Z tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:51:46.1396430Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-09-07T07:51:46.1409547Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:46.1409950Z env: 2025-09-07T07:51:46.1410207Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:46.1411205Z ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:46.1412213Z ##[endgroup] 2025-09-07T07:51:46.1548130Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:46.1738811Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-09-07T07:51:46.1739352Z with: 2025-09-07T07:51:46.1740282Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:46.1741636Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:46.1742063Z env: 2025-09-07T07:51:46.1742278Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:46.1742544Z ##[endgroup] 2025-09-07T07:51:46.1874636Z ##[group]Run set -x 2025-09-07T07:51:46.1874933Z set -x 2025-09-07T07:51:46.1875170Z set +e 2025-09-07T07:51:46.1875392Z  2025-09-07T07:51:46.1875589Z login() { 2025-09-07T07:51:46.1876090Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:51:46.1876632Z } 2025-09-07T07:51:46.1876844Z  2025-09-07T07:51:46.1877111Z retry () { 2025-09-07T07:51:46.1877395Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:51:46.1877711Z } 2025-09-07T07:51:46.1877935Z  2025-09-07T07:51:46.1878167Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:51:46.1878485Z  2025-09-07T07:51:46.1878974Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-09-07T07:51:46.1879661Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-09-07T07:51:46.1880047Z  2025-09-07T07:51:46.1880248Z set -e 2025-09-07T07:51:46.1880586Z # ignore output since only exit code is used for conditional 2025-09-07T07:51:46.1881089Z # only pull docker image if it's not available locally 2025-09-07T07:51:46.1881645Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-09-07T07:51:46.1882168Z  retry docker pull "${DOCKER_IMAGE}" 2025-09-07T07:51:46.1882493Z fi 2025-09-07T07:51:46.1895766Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:46.1896180Z env: 2025-09-07T07:51:46.1896436Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:46.1897416Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:46.1898522Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:46.1898932Z ##[endgroup] 2025-09-07T07:51:46.2622058Z + set +e 2025-09-07T07:51:46.2622407Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:46.2622869Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:46.2625996Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:51:46.2627722Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:47.2386668Z 2025-09-07T07:51:47.2387372Z WARNING! Your credentials are stored unencrypted in '/home/bob/.docker/config.json'. 2025-09-07T07:51:47.2388011Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:47.2388472Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:47.2388734Z 2025-09-07T07:51:47.2388829Z Login Succeeded 2025-09-07T07:51:47.2411817Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:47.2413244Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-09-07T07:51:47.6078941Z + IMAGE_SIZE=36183.606596946716 2025-09-07T07:51:47.6079385Z + echo 'Compressed size of image in MB: 36183.606596946716' 2025-09-07T07:51:47.6079765Z + set -e 2025-09-07T07:51:47.6087618Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:47.6089012Z Compressed size of image in MB: 36183.606596946716 2025-09-07T07:51:47.6207959Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:47.6209707Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:48.6521768Z pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image 2025-09-07T07:51:48.6523146Z e6fdc8487bfe: Pulling fs layer 2025-09-07T07:51:48.6523655Z 171dcef20c49: Pulling fs layer 2025-09-07T07:51:48.6524111Z 4c92b3f72f1d: Pulling fs layer 2025-09-07T07:51:48.6524617Z 744f9ba90a65: Pulling fs layer 2025-09-07T07:51:48.6525188Z d3c08322a332: Pulling fs layer 2025-09-07T07:51:48.6525721Z ffd43b71f3cc: Pulling fs layer 2025-09-07T07:51:48.6526258Z 830692b57f6e: Pulling fs layer 2025-09-07T07:51:48.6526768Z 5bad36d18468: Pulling fs layer 2025-09-07T07:51:48.6527318Z d3c08322a332: Waiting 2025-09-07T07:51:48.6527763Z 744f9ba90a65: Waiting 2025-09-07T07:51:48.6528137Z ffd43b71f3cc: Waiting 2025-09-07T07:51:48.6528538Z 0e34fdd9ac5c: Pulling fs layer 2025-09-07T07:51:48.6529032Z 830692b57f6e: Waiting 2025-09-07T07:51:48.6529454Z 5bad36d18468: Waiting 2025-09-07T07:51:48.6529902Z 3c868a62868e: Pulling fs layer 2025-09-07T07:51:48.6530367Z 0e34fdd9ac5c: Waiting 2025-09-07T07:51:48.6530827Z 62170a22dd57: Pulling fs layer 2025-09-07T07:51:48.6531301Z 3c868a62868e: Waiting 2025-09-07T07:51:48.6531664Z 553c1d23b6c4: Pulling fs layer 2025-09-07T07:51:48.6532153Z 62170a22dd57: Waiting 2025-09-07T07:51:48.6532547Z 9408d557a804: Pulling fs layer 2025-09-07T07:51:48.6533190Z df607cfc7c07: Pulling fs layer 2025-09-07T07:51:48.6533470Z 4f4fb700ef54: Pulling fs layer 2025-09-07T07:51:48.6533776Z 553c1d23b6c4: Waiting 2025-09-07T07:51:48.6534014Z 9408d557a804: Waiting 2025-09-07T07:51:48.6534264Z 40a8e39faeda: Pulling fs layer 2025-09-07T07:51:48.6534540Z df607cfc7c07: Waiting 2025-09-07T07:51:48.6534792Z d895771c9fac: Pulling fs layer 2025-09-07T07:51:48.6535063Z 4f4fb700ef54: Waiting 2025-09-07T07:51:48.6535306Z 40a8e39faeda: Waiting 2025-09-07T07:51:48.6535550Z c4ee04f39d49: Pulling fs layer 2025-09-07T07:51:48.6535825Z d895771c9fac: Waiting 2025-09-07T07:51:48.6536124Z 3690c9826e48: Pulling fs layer 2025-09-07T07:51:48.6536400Z c4ee04f39d49: Waiting 2025-09-07T07:51:48.6536649Z 57cbc5013733: Pulling fs layer 2025-09-07T07:51:48.6536907Z 3690c9826e48: Waiting 2025-09-07T07:51:48.6537159Z f5f4b06b58bb: Pulling fs layer 2025-09-07T07:51:48.6537434Z 57cbc5013733: Waiting 2025-09-07T07:51:48.6537684Z f59713ce4bf4: Pulling fs layer 2025-09-07T07:51:48.6537944Z f5f4b06b58bb: Waiting 2025-09-07T07:51:48.6538191Z fe0486521517: Pulling fs layer 2025-09-07T07:51:48.6538482Z 8c21cc3715a2: Pulling fs layer 2025-09-07T07:51:48.6538757Z fe0486521517: Waiting 2025-09-07T07:51:48.6538980Z f59713ce4bf4: Waiting 2025-09-07T07:51:48.6539234Z d37c58456a6a: Pulling fs layer 2025-09-07T07:51:48.6539525Z d042f63abc13: Pulling fs layer 2025-09-07T07:51:48.6539801Z d37c58456a6a: Waiting 2025-09-07T07:51:48.6540029Z 8c21cc3715a2: Waiting 2025-09-07T07:51:48.6540277Z 621284a9c05a: Pulling fs layer 2025-09-07T07:51:48.6540564Z 85f605d2dd3a: Pulling fs layer 2025-09-07T07:51:48.6540840Z d042f63abc13: Waiting 2025-09-07T07:51:48.6541075Z 381b5539e598: Pulling fs layer 2025-09-07T07:51:48.6541355Z a487c0c80029: Pulling fs layer 2025-09-07T07:51:48.6541715Z 381b5539e598: Waiting 2025-09-07T07:51:48.6542083Z 85f605d2dd3a: Waiting 2025-09-07T07:51:48.6542503Z 48bcb81e2566: Pulling fs layer 2025-09-07T07:51:48.6542993Z a487c0c80029: Waiting 2025-09-07T07:51:48.6543400Z 48bcb81e2566: Waiting 2025-09-07T07:51:48.6543833Z e261928c0043: Pulling fs layer 2025-09-07T07:51:48.6544332Z 0fea55428091: Pulling fs layer 2025-09-07T07:51:48.6545470Z e261928c0043: Waiting 2025-09-07T07:51:48.6545747Z b4291bccbb84: Pulling fs layer 2025-09-07T07:51:48.6546036Z 0fea55428091: Waiting 2025-09-07T07:51:48.6546469Z ddc91b09189a: Pulling fs layer 2025-09-07T07:51:48.6546747Z b4291bccbb84: Waiting 2025-09-07T07:51:48.6547002Z 7540c7428627: Pulling fs layer 2025-09-07T07:51:48.6547262Z ddc91b09189a: Waiting 2025-09-07T07:51:48.6547500Z 7540c7428627: Waiting 2025-09-07T07:51:48.6547752Z 003c4e2598fb: Pulling fs layer 2025-09-07T07:51:48.6548037Z 5687149362ae: Pulling fs layer 2025-09-07T07:51:48.6548297Z 003c4e2598fb: Waiting 2025-09-07T07:51:48.6548554Z cdd2cf54eb2a: Pulling fs layer 2025-09-07T07:51:48.6548827Z 5687149362ae: Waiting 2025-09-07T07:51:48.6549065Z cdd2cf54eb2a: Waiting 2025-09-07T07:51:48.6549368Z d3ad4df1ba3a: Pulling fs layer 2025-09-07T07:51:48.6549756Z 3c9055753b4c: Pulling fs layer 2025-09-07T07:51:48.6550136Z d3ad4df1ba3a: Waiting 2025-09-07T07:51:48.6550491Z 31cf8d0bd21c: Pulling fs layer 2025-09-07T07:51:48.6550827Z 3c9055753b4c: Waiting 2025-09-07T07:51:48.6551106Z 6623ea814971: Pulling fs layer 2025-09-07T07:51:48.6551486Z 11696c3aa380: Pulling fs layer 2025-09-07T07:51:48.6551770Z 6623ea814971: Waiting 2025-09-07T07:51:48.6552024Z 31cf8d0bd21c: Waiting 2025-09-07T07:51:48.6552438Z 11696c3aa380: Waiting 2025-09-07T07:51:48.6552917Z ef4d544e35ca: Pulling fs layer 2025-09-07T07:51:48.6553279Z ef4d544e35ca: Waiting 2025-09-07T07:51:48.6553521Z 5c5108865e5e: Pulling fs layer 2025-09-07T07:51:48.6553864Z 5c5108865e5e: Waiting 2025-09-07T07:51:48.6554227Z 9e97578e9edf: Pulling fs layer 2025-09-07T07:51:48.6554552Z da5a91b54cb5: Pulling fs layer 2025-09-07T07:51:48.6554870Z 9e97578e9edf: Waiting 2025-09-07T07:51:48.6555112Z da5a91b54cb5: Waiting 2025-09-07T07:51:48.6555369Z 1e93be219e89: Pulling fs layer 2025-09-07T07:51:48.6555659Z 136825afebb5: Pulling fs layer 2025-09-07T07:51:48.6556042Z 22b39805302d: Pulling fs layer 2025-09-07T07:51:48.6556317Z 22b39805302d: Waiting 2025-09-07T07:51:48.6556554Z 1e93be219e89: Waiting 2025-09-07T07:51:48.6556888Z d12add675e35: Pulling fs layer 2025-09-07T07:51:48.6557334Z 136825afebb5: Waiting 2025-09-07T07:51:48.6557753Z d12add675e35: Waiting 2025-09-07T07:51:48.6558029Z bc127046d33a: Pulling fs layer 2025-09-07T07:51:48.6558318Z 951e8ce83841: Pulling fs layer 2025-09-07T07:51:48.6558580Z bc127046d33a: Waiting 2025-09-07T07:51:48.6558858Z 32340b97ae50: Pulling fs layer 2025-09-07T07:51:48.6559147Z 5bbb04cd6b57: Pulling fs layer 2025-09-07T07:51:48.6559498Z 951e8ce83841: Waiting 2025-09-07T07:51:48.6559855Z d8c4b845cfc7: Pulling fs layer 2025-09-07T07:51:48.6560211Z 5bbb04cd6b57: Waiting 2025-09-07T07:51:48.6560525Z b35c180f4d8d: Pulling fs layer 2025-09-07T07:51:48.6560817Z 5f967b3c303a: Pulling fs layer 2025-09-07T07:51:48.6561128Z d8c4b845cfc7: Waiting 2025-09-07T07:51:48.6561542Z b35c180f4d8d: Waiting 2025-09-07T07:51:48.6561986Z 04770904f012: Pulling fs layer 2025-09-07T07:51:48.6562340Z 5f967b3c303a: Waiting 2025-09-07T07:51:48.6562640Z 73373941fb32: Pulling fs layer 2025-09-07T07:51:48.6562914Z 04770904f012: Waiting 2025-09-07T07:51:48.6563189Z 73373941fb32: Waiting 2025-09-07T07:51:48.6563449Z 9572e6cd907b: Pulling fs layer 2025-09-07T07:51:48.6563724Z 64a544aba233: Pulling fs layer 2025-09-07T07:51:48.6564119Z 7e35418a2499: Pulling fs layer 2025-09-07T07:51:48.6564416Z 64a544aba233: Waiting 2025-09-07T07:51:48.6564732Z 7e35418a2499: Waiting 2025-09-07T07:51:48.6564969Z 2ed8e82748d4: Pulling fs layer 2025-09-07T07:51:48.6565305Z c988fbcccd70: Pulling fs layer 2025-09-07T07:51:48.6565659Z 2ed8e82748d4: Waiting 2025-09-07T07:51:48.6565998Z c988fbcccd70: Waiting 2025-09-07T07:51:48.8040596Z 171dcef20c49: Verifying Checksum 2025-09-07T07:51:48.8041016Z 171dcef20c49: Download complete 2025-09-07T07:51:49.1299589Z 744f9ba90a65: Verifying Checksum 2025-09-07T07:51:49.1299999Z 744f9ba90a65: Download complete 2025-09-07T07:51:49.3120289Z d3c08322a332: Download complete 2025-09-07T07:51:49.3898004Z e6fdc8487bfe: Verifying Checksum 2025-09-07T07:51:49.3898457Z e6fdc8487bfe: Download complete 2025-09-07T07:51:49.4665563Z ffd43b71f3cc: Download complete 2025-09-07T07:51:49.5450723Z 830692b57f6e: Download complete 2025-09-07T07:51:49.6749585Z 5bad36d18468: Verifying Checksum 2025-09-07T07:51:49.6750286Z 5bad36d18468: Download complete 2025-09-07T07:51:49.8342712Z 3c868a62868e: Verifying Checksum 2025-09-07T07:51:49.8343351Z 3c868a62868e: Download complete 2025-09-07T07:51:50.0469244Z 62170a22dd57: Verifying Checksum 2025-09-07T07:51:50.0469620Z 62170a22dd57: Download complete 2025-09-07T07:51:50.2921001Z 553c1d23b6c4: Verifying Checksum 2025-09-07T07:51:50.2921564Z 553c1d23b6c4: Download complete 2025-09-07T07:51:50.5466700Z 9408d557a804: Verifying Checksum 2025-09-07T07:51:50.5467079Z 9408d557a804: Download complete 2025-09-07T07:51:52.2559845Z 0e34fdd9ac5c: Verifying Checksum 2025-09-07T07:51:52.2560521Z 0e34fdd9ac5c: Download complete 2025-09-07T07:51:52.3640616Z 4f4fb700ef54: Verifying Checksum 2025-09-07T07:51:52.3641035Z 4f4fb700ef54: Download complete 2025-09-07T07:51:52.5141114Z 40a8e39faeda: Verifying Checksum 2025-09-07T07:51:52.5141612Z 40a8e39faeda: Download complete 2025-09-07T07:51:53.6008159Z d895771c9fac: Verifying Checksum 2025-09-07T07:51:53.6008580Z d895771c9fac: Download complete 2025-09-07T07:51:53.9108216Z c4ee04f39d49: Verifying Checksum 2025-09-07T07:51:53.9108589Z c4ee04f39d49: Download complete 2025-09-07T07:51:54.1798458Z e6fdc8487bfe: Pull complete 2025-09-07T07:51:54.2232145Z 3690c9826e48: Verifying Checksum 2025-09-07T07:51:54.2232588Z 3690c9826e48: Download complete 2025-09-07T07:51:54.4178043Z 57cbc5013733: Verifying Checksum 2025-09-07T07:51:54.4178386Z 57cbc5013733: Download complete 2025-09-07T07:51:54.6100978Z f5f4b06b58bb: Verifying Checksum 2025-09-07T07:51:54.6101365Z f5f4b06b58bb: Download complete 2025-09-07T07:51:54.7518336Z 4c92b3f72f1d: Verifying Checksum 2025-09-07T07:51:54.7518707Z 4c92b3f72f1d: Download complete 2025-09-07T07:51:54.7734288Z f59713ce4bf4: Verifying Checksum 2025-09-07T07:51:54.7734684Z f59713ce4bf4: Download complete 2025-09-07T07:51:54.9346326Z fe0486521517: Verifying Checksum 2025-09-07T07:51:54.9346685Z fe0486521517: Download complete 2025-09-07T07:51:55.1627921Z d37c58456a6a: Verifying Checksum 2025-09-07T07:51:55.1628457Z d37c58456a6a: Download complete 2025-09-07T07:51:55.7776007Z 171dcef20c49: Pull complete 2025-09-07T07:51:55.9622990Z d042f63abc13: Verifying Checksum 2025-09-07T07:51:55.9623392Z d042f63abc13: Download complete 2025-09-07T07:51:56.1774901Z 621284a9c05a: Verifying Checksum 2025-09-07T07:51:56.1775279Z 621284a9c05a: Download complete 2025-09-07T07:51:56.4307012Z 85f605d2dd3a: Verifying Checksum 2025-09-07T07:51:56.4307414Z 85f605d2dd3a: Download complete 2025-09-07T07:52:07.2354176Z 381b5539e598: Verifying Checksum 2025-09-07T07:52:07.2354575Z 381b5539e598: Download complete 2025-09-07T07:52:07.4135279Z a487c0c80029: Verifying Checksum 2025-09-07T07:52:07.4135853Z a487c0c80029: Download complete 2025-09-07T07:52:07.5487617Z 48bcb81e2566: Verifying Checksum 2025-09-07T07:52:07.5488198Z 48bcb81e2566: Download complete 2025-09-07T07:52:07.7154853Z e261928c0043: Verifying Checksum 2025-09-07T07:52:07.9857002Z 0fea55428091: Verifying Checksum 2025-09-07T07:52:07.9857421Z 0fea55428091: Download complete 2025-09-07T07:52:08.4734510Z b4291bccbb84: Verifying Checksum 2025-09-07T07:52:08.4738039Z b4291bccbb84: Download complete 2025-09-07T07:52:08.6223003Z ddc91b09189a: Verifying Checksum 2025-09-07T07:52:08.6223635Z ddc91b09189a: Download complete 2025-09-07T07:52:08.7850600Z 7540c7428627: Verifying Checksum 2025-09-07T07:52:08.7851239Z 7540c7428627: Download complete 2025-09-07T07:52:08.9738378Z 003c4e2598fb: Verifying Checksum 2025-09-07T07:52:08.9738758Z 003c4e2598fb: Download complete 2025-09-07T07:52:09.1349922Z 5687149362ae: Download complete 2025-09-07T07:52:09.2884986Z cdd2cf54eb2a: Verifying Checksum 2025-09-07T07:52:09.2885378Z cdd2cf54eb2a: Download complete 2025-09-07T07:52:38.8686724Z 4c92b3f72f1d: Pull complete 2025-09-07T07:52:40.2636178Z 744f9ba90a65: Pull complete 2025-09-07T07:52:42.0839785Z d3c08322a332: Pull complete 2025-09-07T07:52:44.0980347Z ffd43b71f3cc: Pull complete 2025-09-07T07:52:45.1535724Z 830692b57f6e: Pull complete 2025-09-07T07:52:46.5398438Z 5bad36d18468: Pull complete 2025-09-07T07:52:54.9562634Z 0e34fdd9ac5c: Pull complete 2025-09-07T07:52:55.7249604Z 3c868a62868e: Pull complete 2025-09-07T07:52:56.3285295Z 62170a22dd57: Pull complete 2025-09-07T07:52:56.5848246Z df607cfc7c07: Verifying Checksum 2025-09-07T07:52:56.5848696Z df607cfc7c07: Download complete 2025-09-07T07:52:56.7462670Z 3c9055753b4c: Download complete 2025-09-07T07:52:57.0842139Z 553c1d23b6c4: Pull complete 2025-09-07T07:52:57.9707002Z 9408d557a804: Pull complete 2025-09-07T07:53:01.5001121Z 31cf8d0bd21c: Download complete 2025-09-07T08:02:15.1664887Z 6623ea814971: Verifying Checksum 2025-09-07T08:02:15.1665292Z 6623ea814971: Download complete 2025-09-07T08:02:15.5144940Z 11696c3aa380: Verifying Checksum 2025-09-07T08:02:15.5145345Z 11696c3aa380: Download complete 2025-09-07T08:02:15.6860158Z ef4d544e35ca: Download complete 2025-09-07T08:02:15.8456278Z 5c5108865e5e: Download complete 2025-09-07T08:02:16.0021371Z 9e97578e9edf: Verifying Checksum 2025-09-07T08:02:16.0021754Z 9e97578e9edf: Download complete 2025-09-07T08:02:16.1684009Z da5a91b54cb5: Verifying Checksum 2025-09-07T08:02:16.1684384Z da5a91b54cb5: Download complete 2025-09-07T08:02:16.3406778Z 1e93be219e89: Verifying Checksum 2025-09-07T08:02:16.3407173Z 1e93be219e89: Download complete 2025-09-07T08:02:16.4807072Z 136825afebb5: Verifying Checksum 2025-09-07T08:02:16.4807442Z 136825afebb5: Download complete 2025-09-07T08:02:16.6374926Z 22b39805302d: Verifying Checksum 2025-09-07T08:02:16.6375288Z 22b39805302d: Download complete 2025-09-07T08:02:16.7761709Z d12add675e35: Verifying Checksum 2025-09-07T08:02:16.7762095Z d12add675e35: Download complete 2025-09-07T08:02:16.9420250Z bc127046d33a: Verifying Checksum 2025-09-07T08:02:16.9420746Z bc127046d33a: Download complete 2025-09-07T08:02:17.1076602Z 951e8ce83841: Verifying Checksum 2025-09-07T08:02:17.1076982Z 951e8ce83841: Download complete 2025-09-07T08:02:17.2694417Z 32340b97ae50: Verifying Checksum 2025-09-07T08:02:17.2694797Z 32340b97ae50: Download complete 2025-09-07T08:02:17.4113305Z 5bbb04cd6b57: Verifying Checksum 2025-09-07T08:02:17.4113698Z 5bbb04cd6b57: Download complete 2025-09-07T08:02:17.5544833Z d8c4b845cfc7: Verifying Checksum 2025-09-07T08:02:17.5545213Z d8c4b845cfc7: Download complete 2025-09-07T08:02:55.0388794Z b35c180f4d8d: Verifying Checksum 2025-09-07T08:02:55.0389179Z b35c180f4d8d: Download complete 2025-09-07T08:02:55.2057010Z 5f967b3c303a: Verifying Checksum 2025-09-07T08:02:55.2057395Z 5f967b3c303a: Download complete 2025-09-07T08:02:55.3667054Z 04770904f012: Verifying Checksum 2025-09-07T08:02:55.3667438Z 04770904f012: Download complete 2025-09-07T08:02:55.5332497Z 73373941fb32: Download complete 2025-09-07T08:02:55.6901339Z 9572e6cd907b: Download complete 2025-09-07T08:02:55.8506498Z 64a544aba233: Verifying Checksum 2025-09-07T08:02:55.8506876Z 64a544aba233: Download complete 2025-09-07T08:02:58.3057848Z 7e35418a2499: Verifying Checksum 2025-09-07T08:02:58.3058231Z 7e35418a2499: Download complete 2025-09-07T08:02:58.4407905Z 2ed8e82748d4: Verifying Checksum 2025-09-07T08:02:58.4408330Z 2ed8e82748d4: Download complete 2025-09-07T08:03:04.8177419Z 8c21cc3715a2: Verifying Checksum 2025-09-07T08:03:04.8177799Z 8c21cc3715a2: Download complete 2025-09-07T08:03:07.0542677Z c988fbcccd70: Verifying Checksum 2025-09-07T08:03:07.0543073Z c988fbcccd70: Download complete 2025-09-07T08:10:17.3867338Z d3ad4df1ba3a: Verifying Checksum 2025-09-07T08:10:17.3867733Z d3ad4df1ba3a: Download complete 2025-09-07T08:11:07.1482145Z df607cfc7c07: Pull complete 2025-09-07T08:11:10.9834109Z 4f4fb700ef54: Pull complete 2025-09-07T08:11:14.5243927Z 40a8e39faeda: Pull complete 2025-09-07T08:11:22.5217718Z d895771c9fac: Pull complete 2025-09-07T08:11:26.2454878Z c4ee04f39d49: Pull complete 2025-09-07T08:11:29.1898683Z 3690c9826e48: Pull complete 2025-09-07T08:11:31.8959722Z 57cbc5013733: Pull complete 2025-09-07T08:11:34.8479491Z f5f4b06b58bb: Pull complete 2025-09-07T08:11:37.6605823Z f59713ce4bf4: Pull complete 2025-09-07T08:11:40.8219373Z fe0486521517: Pull complete 2025-09-07T08:22:55.4956381Z 8c21cc3715a2: Pull complete 2025-09-07T08:22:58.7356700Z d37c58456a6a: Pull complete 2025-09-07T08:23:02.5829938Z d042f63abc13: Pull complete 2025-09-07T08:23:05.7353783Z 621284a9c05a: Pull complete 2025-09-07T08:23:08.9406832Z 85f605d2dd3a: Pull complete 2025-09-07T08:23:45.3702119Z 381b5539e598: Pull complete 2025-09-07T08:23:48.1271967Z a487c0c80029: Pull complete 2025-09-07T08:23:51.9794528Z 48bcb81e2566: Pull complete 2025-09-07T08:23:58.4182668Z 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Digest: sha256:f30843ff9ea9e117a2c8e6d207e85c9e77dfe682f1dfcdfea5b94178d1bf00b3 2025-09-07T08:51:18.2120502Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:51:18.3227535Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:51:18.3433607Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:51:18.3434617Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:51:18.3447612Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:51:18.3447992Z env: 2025-09-07T08:51:18.3448212Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:18.3448476Z ##[endgroup] 2025-09-07T08:51:18.4500105Z ##[group]Run echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:51:18.4500814Z echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:51:18.4512687Z shell: /usr/bin/bash -e {0} 2025-09-07T08:51:18.4512979Z env: 2025-09-07T08:51:18.4513198Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:18.4513462Z ##[endgroup] 2025-09-07T08:51:18.5574307Z ##[group]Run echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:51:18.5575415Z echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:51:18.5587292Z shell: /usr/bin/bash -e {0} 2025-09-07T08:51:18.5587579Z env: 2025-09-07T08:51:18.5587794Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:18.5588137Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:18.5588491Z ##[endgroup] 2025-09-07T08:51:18.6156363Z Prepare all required actions 2025-09-07T08:51:18.6630238Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-09-07T08:51:18.6630594Z with: 2025-09-07T08:51:18.6631008Z github-token: *** 2025-09-07T08:51:18.6631227Z env: 2025-09-07T08:51:18.6631441Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:18.6631786Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:18.6632254Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:51:18.6632638Z ##[endgroup] 2025-09-07T08:51:18.7175237Z ##[group]Run set -eux 2025-09-07T08:51:18.7175518Z set -eux 2025-09-07T08:51:18.7175993Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T08:51:18.7187634Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:51:18.7188009Z env: 2025-09-07T08:51:18.7188229Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:18.7188571Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:18.7189085Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:51:18.7189666Z GITHUB_TOKEN: *** 2025-09-07T08:51:18.7189903Z ##[endgroup] 2025-09-07T08:51:18.7724219Z + python3 .github/scripts/get_workflow_job_id.py 17525309334 i-01a21955dc3821a00-1002 2025-09-07T08:51:19.6763592Z Setting output job-id=49775768421 2025-09-07T08:51:19.6764204Z Setting output job-name=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T08:51:19.7074451Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:51:19.7075255Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:51:19.7076254Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-09-07T08:51:19.7077144Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-09-07T08:51:19.7089753Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:51:19.7090156Z env: 2025-09-07T08:51:19.7090370Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:19.7090718Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:19.7091191Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:51:19.7091594Z JOB_ID: 49775768421 2025-09-07T08:51:19.7092092Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T08:51:19.7092647Z WORKFLOW_NAME: inductor-A100-perf-nightly 2025-09-07T08:51:19.7093153Z WORKFLOW_RUN_ID: 17525309334 2025-09-07T08:51:19.7093447Z MONITOR_LOG_INTERVAL: 15 2025-09-07T08:51:19.7093734Z MONITOR_DATA_COLLECT_INTERVAL: 4 2025-09-07T08:51:19.7094031Z ##[endgroup] 2025-09-07T08:51:20.0743132Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:51:20.6663694Z Collecting psutil==5.9.8 2025-09-07T08:51:20.7428067Z Downloading psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (288 kB) 2025-09-07T08:51:21.0133506Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 KB 1.0 MB/s eta 0:00:00 2025-09-07T08:51:21.4003750Z Collecting dataclasses_json==0.6.7 2025-09-07T08:51:21.4124558Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-09-07T08:51:22.0688022Z Collecting nvidia-ml-py==11.525.84 2025-09-07T08:51:22.0809267Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-09-07T08:51:22.8795013Z Collecting marshmallow<4.0.0,>=3.18.0 2025-09-07T08:51:22.8914959Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-09-07T08:51:23.2444413Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 50.9/50.9 KB 115.8 kB/s eta 0:00:00 2025-09-07T08:51:23.6613829Z Collecting typing-inspect<1,>=0.4.0 2025-09-07T08:51:23.6741081Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-09-07T08:51:24.4443028Z Collecting packaging>=17.0 2025-09-07T08:51:24.4565495Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-09-07T08:51:24.6070850Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 66.5/66.5 KB 378.6 kB/s eta 0:00:00 2025-09-07T08:51:24.6702499Z Collecting mypy-extensions>=0.3.0 2025-09-07T08:51:24.6821259Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-09-07T08:51:24.7846022Z Collecting typing-extensions>=3.7.4 2025-09-07T08:51:24.7968637Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-09-07T08:51:24.8277737Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.6/44.6 KB 1.2 MB/s eta 0:00:00 2025-09-07T08:51:24.8983871Z Installing collected packages: nvidia-ml-py, typing-extensions, psutil, packaging, mypy-extensions, typing-inspect, marshmallow, dataclasses_json 2025-09-07T08:51:29.4751036Z Successfully installed dataclasses_json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 nvidia-ml-py-11.525.84 packaging-25.0 psutil-5.9.8 typing-extensions-4.15.0 typing-inspect-0.9.0 2025-09-07T08:51:29.5486890Z Prepare all required actions 2025-09-07T08:51:29.5487266Z Getting action download info 2025-09-07T08:51:30.0512922Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-09-07T08:51:34.1711778Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-09-07T08:51:44.5558958Z ##[group]Run ./.github/actions/download-build-artifacts 2025-09-07T08:51:44.5559339Z with: 2025-09-07T08:51:44.5559600Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:51:44.5559932Z s3-bucket: gha-artifacts 2025-09-07T08:51:44.5560211Z env: 2025-09-07T08:51:44.5560425Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:44.5560767Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:44.5561221Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:51:44.5561622Z ##[endgroup] 2025-09-07T08:51:44.6472954Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:51:44.6473311Z with: 2025-09-07T08:51:44.6473553Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:51:44.6473897Z s3-bucket: gha-artifacts 2025-09-07T08:51:44.6474173Z region: us-east-1 2025-09-07T08:51:44.6474394Z env: 2025-09-07T08:51:44.6474608Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:44.6474946Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:44.6475421Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:51:44.6475817Z ##[endgroup] 2025-09-07T08:51:45.1082546Z (node:9490) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:51:45.1083095Z 2025-09-07T08:51:45.1083303Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:51:45.1083853Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:51:45.1084440Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:51:45.2350205Z Found 1 objects with prefix pytorch/pytorch/17525309334/linux-jammy-cuda12.8-py3.10-gcc9-sm80/ 2025-09-07T08:51:45.2350895Z Starting download (1/1): /home/bob/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:51:57.4974636Z Finished download (1/1): /home/bob/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:51:57.4984092Z Artifact download has finished successfully 2025-09-07T08:51:57.5231286Z ##[group]Run unzip -o artifacts.zip 2025-09-07T08:51:57.5231633Z unzip -o artifacts.zip 2025-09-07T08:51:57.5244289Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:51:57.5244686Z env: 2025-09-07T08:51:57.5245096Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:51:57.5245436Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:51:57.5245899Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:51:57.5246286Z ##[endgroup] 2025-09-07T08:51:57.5751446Z Archive: artifacts.zip 2025-09-07T08:51:57.5752864Z creating: dist/ 2025-09-07T08:52:10.0038625Z inflating: dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T08:52:10.0039116Z creating: dist/vision/ 2025-09-07T08:52:10.0159370Z inflating: dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:52:10.0159876Z creating: dist/audio/ 2025-09-07T08:52:10.0216735Z inflating: dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:52:10.0217237Z creating: dist/torchrec/ 2025-09-07T08:52:10.0243326Z inflating: dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:52:10.0243749Z creating: dist/fbgemm_gpu/ 2025-09-07T08:52:13.9945533Z inflating: dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:52:13.9946130Z creating: dist/ao/ 2025-09-07T08:52:13.9988034Z inflating: dist/ao/torchao-0.7.0+git51c87b6e-py3-none-any.whl 2025-09-07T08:52:14.0121327Z inflating: dist/.ninja_log 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inflating: build/bin/test_dist_autograd 2025-09-07T08:52:37.0198485Z inflating: build/bin/test_cpp_rpc 2025-09-07T08:52:37.4373499Z inflating: build/bin/test_api 2025-09-07T08:52:37.4375867Z inflating: build/bin/parallel_benchmark 2025-09-07T08:52:37.4443485Z inflating: build/bin/ProcessGroupNCCLTest 2025-09-07T08:52:37.4510322Z inflating: build/bin/ProcessGroupNCCLErrorsTest 2025-09-07T08:52:37.8388562Z inflating: build/bin/test_jit 2025-09-07T08:52:37.8388979Z inflating: build/bin/ProcessGroupGlooTest 2025-09-07T08:52:37.8389380Z inflating: build/bin/ProcessGroupGlooAsyncTest 2025-09-07T08:52:37.8511591Z inflating: build/bin/test_lazy 2025-09-07T08:52:37.8515376Z inflating: build/bin/torch_shm_manager 2025-09-07T08:52:37.8515720Z creating: .additional_ci_files/ 2025-09-07T08:52:37.8605888Z inflating: .additional_ci_files/test-times.json 2025-09-07T08:52:38.0802604Z inflating: .additional_ci_files/test-class-times.json 2025-09-07T08:52:38.2171423Z ##[group]Run rm artifacts.zip 2025-09-07T08:52:38.2171772Z rm artifacts.zip 2025-09-07T08:52:38.2185589Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:38.2185996Z env: 2025-09-07T08:52:38.2186209Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:38.2186558Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:38.2187051Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:38.2187457Z ##[endgroup] 2025-09-07T08:52:38.4592772Z ##[group]Run df -H 2025-09-07T08:52:38.4593028Z df -H 2025-09-07T08:52:38.4604803Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:38.4605183Z env: 2025-09-07T08:52:38.4605403Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:38.4605748Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:38.4606216Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:38.4606602Z ##[endgroup] 2025-09-07T08:52:38.6984369Z Filesystem Size Used Avail Use% Mounted on 2025-09-07T08:52:38.6984780Z overlay 5.3T 593G 4.7T 12% / 2025-09-07T08:52:38.6985162Z tmpfs 68M 0 68M 0% /dev 2025-09-07T08:52:38.6985498Z shm 68M 0 68M 0% /dev/shm 2025-09-07T08:52:38.6985849Z /dev/root 5.3T 593G 4.7T 12% /home/bob/_work 2025-09-07T08:52:38.6986251Z tmpfs 121G 111k 121G 1% /run/docker.sock 2025-09-07T08:52:38.6986777Z tmpfs 603G 13k 603G 1% /proc/driver/nvidia 2025-09-07T08:52:38.6987260Z tmpfs 241G 1.7M 241G 1% /run/.ro4102070540/nvidia-persistenced/socket 2025-09-07T08:52:38.6987708Z tmpfs 603G 0 603G 0% /proc/acpi 2025-09-07T08:52:38.6988065Z tmpfs 603G 0 603G 0% /proc/scsi 2025-09-07T08:52:38.6988424Z tmpfs 603G 0 603G 0% /sys/firmware 2025-09-07T08:52:38.7020661Z Prepare all required actions 2025-09-07T08:52:38.7021468Z Getting action download info 2025-09-07T08:52:39.1229310Z ##[group]Run ./.github/actions/download-td-artifacts 2025-09-07T08:52:39.1229839Z with: 2025-09-07T08:52:39.1230031Z env: 2025-09-07T08:52:39.1230251Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:39.1230601Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:39.1231075Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:39.1231474Z ##[endgroup] 2025-09-07T08:52:39.4605549Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:52:39.4605891Z with: 2025-09-07T08:52:39.4606105Z name: td_results 2025-09-07T08:52:39.4606357Z s3-bucket: gha-artifacts 2025-09-07T08:52:39.4606636Z region: us-east-1 2025-09-07T08:52:39.4606852Z env: 2025-09-07T08:52:39.4607067Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:39.4607409Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:39.4607980Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:39.4608382Z ##[endgroup] 2025-09-07T08:52:39.9179065Z (node:9512) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:52:39.9179616Z 2025-09-07T08:52:39.9179813Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:52:39.9180377Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:52:39.9180962Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:52:40.0394235Z Found 0 objects with prefix pytorch/pytorch/17525309334/td_results/ 2025-09-07T08:52:40.3422215Z Artifact download has finished successfully 2025-09-07T08:52:40.4400837Z ##[group]Run mkdir -p .additional_ci_files 2025-09-07T08:52:40.4401221Z mkdir -p .additional_ci_files 2025-09-07T08:52:40.4401674Z mv td_results.json .additional_ci_files/td_results.json || true 2025-09-07T08:52:40.4414743Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:40.4415143Z env: 2025-09-07T08:52:40.4415364Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:40.4415704Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:40.4416189Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:40.4416573Z ##[endgroup] 2025-09-07T08:52:40.4639227Z mv: cannot stat 'td_results.json': No such file or directory 2025-09-07T08:52:40.8781075Z ##[group]Run .github/scripts/parse_ref.py 2025-09-07T08:52:40.8781463Z .github/scripts/parse_ref.py 2025-09-07T08:52:40.8793907Z shell: /usr/bin/bash -e {0} 2025-09-07T08:52:40.8794212Z env: 2025-09-07T08:52:40.8794442Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:40.8794785Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:40.8795282Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:40.8795692Z ##[endgroup] 2025-09-07T08:52:40.9376818Z Setting output branch=main 2025-09-07T08:52:40.9504774Z Prepare all required actions 2025-09-07T08:52:40.9505290Z Getting action download info 2025-09-07T08:52:41.5665723Z ##[group]Run ./.github/actions/filter-test-configs 2025-09-07T08:52:41.5666142Z with: 2025-09-07T08:52:41.5666602Z github-token: *** 2025-09-07T08:52:41.5672489Z test-matrix: {"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]} 2025-09-07T08:52:41.5679232Z job-name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T08:52:41.5679757Z env: 2025-09-07T08:52:41.5679987Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:41.5680347Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:41.5680814Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:41.5681218Z ##[endgroup] 2025-09-07T08:52:41.6329196Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T08:52:41.6329520Z with: 2025-09-07T08:52:41.6329718Z shell: bash 2025-09-07T08:52:41.6329951Z timeout_minutes: 10 2025-09-07T08:52:41.6330206Z max_attempts: 5 2025-09-07T08:52:41.6330447Z retry_wait_seconds: 30 2025-09-07T08:52:41.6331289Z command: set -eux # PyYAML 6.0 doesn't work with MacOS x86 anymore # This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2 python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:52:41.6332149Z polling_interval_seconds: 1 2025-09-07T08:52:41.6332444Z warning_on_retry: true 2025-09-07T08:52:41.6332721Z continue_on_error: false 2025-09-07T08:52:41.6333228Z env: 2025-09-07T08:52:41.6333446Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:41.6333791Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:41.6334263Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:41.6334830Z GITHUB_TOKEN: *** 2025-09-07T08:52:41.6335071Z ##[endgroup] 2025-09-07T08:52:41.7954270Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:52:42.1039943Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:52:43.7773448Z Collecting requests==2.27.1 2025-09-07T08:52:44.3557663Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-09-07T08:52:44.7924303Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 183.4 kB/s eta 0:00:00 2025-09-07T08:52:45.7003319Z Collecting pyyaml==6.0.2 2025-09-07T08:52:45.9619585Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-09-07T08:52:46.3189023Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 2.4 MB/s eta 0:00:00 2025-09-07T08:52:46.6973918Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.27.1) (3.3) 2025-09-07T08:52:47.1668801Z Collecting charset-normalizer~=2.0.0 2025-09-07T08:52:47.7658814Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-09-07T08:52:48.1117391Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.27.1) (1.26.5) 2025-09-07T08:52:48.1123024Z Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.27.1) (2020.6.20) 2025-09-07T08:52:48.5370932Z Installing collected packages: pyyaml, charset-normalizer, requests 2025-09-07T08:52:51.2858598Z WARNING: The script normalizer is installed in '/home/bob/.local/bin' which is not on PATH. 2025-09-07T08:52:51.2859476Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T08:52:52.6325931Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-09-07T08:52:53.8011155Z Command completed after 1 attempt(s). 2025-09-07T08:52:54.1799471Z ##[group]Run set -x 2025-09-07T08:52:54.1799765Z set -x 2025-09-07T08:52:54.1800024Z  2025-09-07T08:52:54.1800448Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:52:54.1800981Z # in runner workspace 2025-09-07T08:52:54.1801414Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-09-07T08:52:54.1815647Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:54.1816072Z env: 2025-09-07T08:52:54.1816322Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:54.1816716Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:54.1817205Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:54.1817603Z ##[endgroup] 2025-09-07T08:52:54.1946757Z + python3 /home/bob/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-09-07T08:52:54.4675518Z Setting output branch=main 2025-09-07T08:52:54.5023756Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:52:54.5024237Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:52:54.5024608Z echo "Job name: ${JOB_NAME}" 2025-09-07T08:52:54.5025091Z  2025-09-07T08:52:54.5025505Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:52:54.5026021Z # in runner workspace 2025-09-07T08:52:54.5026487Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-09-07T08:52:54.5027028Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-09-07T08:52:54.5027412Z  --job-name "${JOB_NAME}" \ 2025-09-07T08:52:54.5033556Z  --test-matrix "{"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]}" \ 2025-09-07T08:52:54.5039705Z  --selected-test-configs "" \ 2025-09-07T08:52:54.5040065Z  --pr-number "${PR_NUMBER}" \ 2025-09-07T08:52:54.5040404Z  --tag "${TAG}" \ 2025-09-07T08:52:54.5040727Z  --event-name "${EVENT_NAME}" \ 2025-09-07T08:52:54.5041064Z  --schedule "${SCHEDULE}" \ 2025-09-07T08:52:54.5041403Z  --branch "${HEAD_BRANCH}" 2025-09-07T08:52:54.5054461Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:54.5054890Z env: 2025-09-07T08:52:54.5055131Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:54.5055469Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:54.5055953Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:54.5056585Z GITHUB_TOKEN: *** 2025-09-07T08:52:54.5057041Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T08:52:54.5057559Z PR_NUMBER: 2025-09-07T08:52:54.5057774Z TAG: 2025-09-07T08:52:54.5057998Z EVENT_NAME: schedule 2025-09-07T08:52:54.5058266Z SCHEDULE: 0 7 * * 0 2025-09-07T08:52:54.5058529Z HEAD_BRANCH: main 2025-09-07T08:52:54.5058773Z ##[endgroup] 2025-09-07T08:52:55.1840141Z Workflow: inductor-A100-perf-nightly 2025-09-07T08:52:55.1840716Z Job name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T08:52:56.5318997Z Setting output keep-going=True 2025-09-07T08:52:56.5319668Z Setting output ci-verbose-test-logs=False 2025-09-07T08:52:56.5320344Z Setting output ci-test-showlocals=False 2025-09-07T08:52:56.5320993Z Setting output ci-no-test-timeout=False 2025-09-07T08:52:56.5321625Z Setting output ci-no-td=False 2025-09-07T08:52:56.5322190Z Setting output ci-td-distributed=False 2025-09-07T08:52:56.5322540Z Setting output is-unstable=False 2025-09-07T08:52:56.5322866Z Setting output reenabled-issues= 2025-09-07T08:52:56.6936496Z Setting output test-matrix={"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]} 2025-09-07T08:52:56.6942898Z Setting output is-test-matrix-empty=False 2025-09-07T08:52:56.7534520Z ##[group]Run echo "Filtered matrix:" 2025-09-07T08:52:56.7534907Z echo "Filtered matrix:" 2025-09-07T08:52:56.7540730Z echo "{"include": [{"config": "inductor_huggingface_perf", "shard": 1, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 2, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 3, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 4, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_huggingface_perf", "shard": 5, "num_shards": 5, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_timm_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 1, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 2, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 3, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 4, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 5, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "inductor_torchbench_perf", "shard": 6, "num_shards": 6, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 1, "num_shards": 2, "runner": "linux.aws.a100"}, {"config": "cachebench", "shard": 2, "num_shards": 2, "runner": "linux.aws.a100"}]}" 2025-09-07T08:52:56.7547094Z  2025-09-07T08:52:56.7547318Z echo 2025-09-07T08:52:56.7547643Z echo "Is the current job unstable? False" 2025-09-07T08:52:56.7547987Z  2025-09-07T08:52:56.7548204Z echo 2025-09-07T08:52:56.7548468Z echo "Is keep-going label set? True" 2025-09-07T08:52:56.7548806Z  2025-09-07T08:52:56.7549006Z echo 2025-09-07T08:52:56.7549256Z echo "Reenabled issues? " 2025-09-07T08:52:56.7561887Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:56.7562288Z env: 2025-09-07T08:52:56.7562511Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:56.7562841Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:56.7563322Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:56.7563732Z ##[endgroup] 2025-09-07T08:52:56.8090349Z Filtered matrix: 2025-09-07T08:52:56.8097635Z {include: [{config: inductor_huggingface_perf, shard: 1, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 2, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 3, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 4, num_shards: 5, runner: linux.aws.a100}, {config: inductor_huggingface_perf, shard: 5, num_shards: 5, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 1, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 2, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 3, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 4, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 5, num_shards: 6, runner: linux.aws.a100}, {config: inductor_timm_perf, shard: 6, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 1, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 2, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 3, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 4, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 5, num_shards: 6, runner: linux.aws.a100}, {config: inductor_torchbench_perf, shard: 6, num_shards: 6, runner: linux.aws.a100}, {config: cachebench, shard: 1, num_shards: 2, runner: linux.aws.a100}, {config: cachebench, shard: 2, num_shards: 2, runner: linux.aws.a100}]} 2025-09-07T08:52:56.8103462Z 2025-09-07T08:52:56.8103576Z Is the current job unstable? False 2025-09-07T08:52:56.8103800Z 2025-09-07T08:52:56.8103905Z Is keep-going label set? True 2025-09-07T08:52:56.8104108Z 2025-09-07T08:52:56.8104198Z Reenabled issues? 2025-09-07T08:52:57.1110809Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:52:57.1111365Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:52:57.4648660Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:57.4649101Z env: 2025-09-07T08:52:57.4649358Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:57.4649731Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:57.4650234Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:57.4650639Z JOB_TIMEOUT: 1440 2025-09-07T08:52:57.4650904Z ##[endgroup] 2025-09-07T08:52:58.0817448Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:52:58.0818020Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:52:58.0818513Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:52:58.0831235Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:52:58.0831642Z env: 2025-09-07T08:52:58.0831885Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:58.0832245Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:58.0832723Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:58.0833114Z ##[endgroup] 2025-09-07T08:52:58.3275854Z ##[group]Run set -x 2025-09-07T08:52:58.3276278Z set -x 2025-09-07T08:52:58.3276517Z  2025-09-07T08:52:58.3276769Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-09-07T08:52:58.3277196Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-09-07T08:52:58.3277620Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-09-07T08:52:58.3278009Z  TEST_COMMAND=.ci/onnx/test.sh 2025-09-07T08:52:58.3278311Z else 2025-09-07T08:52:58.3278576Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:52:58.3278899Z fi 2025-09-07T08:52:58.3279119Z  2025-09-07T08:52:58.3279383Z # Leaving 1GB for the runner and other things 2025-09-07T08:52:58.3280016Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-09-07T08:52:58.3280968Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-09-07T08:52:58.3281717Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-09-07T08:52:58.3282264Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-09-07T08:52:58.3282706Z  2025-09-07T08:52:58.3282990Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:52:58.3283388Z  SHM_OPTS= 2025-09-07T08:52:58.3283638Z  JENKINS_USER= 2025-09-07T08:52:58.3284008Z  # ensure that docker container cleanly exits in 12 hours 2025-09-07T08:52:58.3284515Z  # if for some reason cleanup action doesn't stop container 2025-09-07T08:52:58.3284937Z  # when job is cancelled 2025-09-07T08:52:58.3285341Z  DOCKER_SHELL_CMD="sleep 12h" 2025-09-07T08:52:58.3285650Z else 2025-09-07T08:52:58.3285922Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-09-07T08:52:58.3286287Z  JENKINS_USER="--user jenkins" 2025-09-07T08:52:58.3286628Z  DOCKER_SHELL_CMD= 2025-09-07T08:52:58.3286893Z fi 2025-09-07T08:52:58.3287116Z  2025-09-07T08:52:58.3287476Z # detached container should get cleaned up by teardown_ec2_linux 2025-09-07T08:52:58.3288039Z # TODO: Stop building test binaries as part of the build phase 2025-09-07T08:52:58.3288671Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-09-07T08:52:58.3289243Z # shellcheck disable=SC2086,SC2090 2025-09-07T08:52:58.3289600Z container_name=$(docker run \ 2025-09-07T08:52:58.3289930Z  ${GPU_FLAG:-} \ 2025-09-07T08:52:58.3290254Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-09-07T08:52:58.3290851Z  -e BUILD_ENVIRONMENT \ 2025-09-07T08:52:58.3291172Z  -e PR_NUMBER \ 2025-09-07T08:52:58.3291471Z  -e GITHUB_ACTIONS \ 2025-09-07T08:52:58.3291782Z  -e GITHUB_REPOSITORY \ 2025-09-07T08:52:58.3292089Z  -e GITHUB_WORKFLOW \ 2025-09-07T08:52:58.3292393Z  -e GITHUB_JOB \ 2025-09-07T08:52:58.3292685Z  -e GITHUB_RUN_ID \ 2025-09-07T08:52:58.3293206Z  -e GITHUB_RUN_NUMBER \ 2025-09-07T08:52:58.3293504Z  -e GITHUB_RUN_ATTEMPT \ 2025-09-07T08:52:58.3293809Z  -e JOB_ID \ 2025-09-07T08:52:58.3294076Z  -e JOB_NAME \ 2025-09-07T08:52:58.3294385Z  -e BASE_SHA \ 2025-09-07T08:52:58.3294639Z  -e BRANCH \ 2025-09-07T08:52:58.3294900Z  -e SHA1 \ 2025-09-07T08:52:58.3295163Z  -e AWS_DEFAULT_REGION \ 2025-09-07T08:52:58.3295475Z  -e IN_WHEEL_TEST \ 2025-09-07T08:52:58.3295758Z  -e SHARD_NUMBER \ 2025-09-07T08:52:58.3296047Z  -e TEST_CONFIG \ 2025-09-07T08:52:58.3296337Z  -e NUM_TEST_SHARDS \ 2025-09-07T08:52:58.3296646Z  -e REENABLED_ISSUES \ 2025-09-07T08:52:58.3296952Z  -e CONTINUE_THROUGH_ERROR \ 2025-09-07T08:52:58.3297545Z  -e VERBOSE_TEST_LOGS \ 2025-09-07T08:52:58.3297863Z  -e TEST_SHOWLOCALS \ 2025-09-07T08:52:58.3298173Z  -e NO_TEST_TIMEOUT \ 2025-09-07T08:52:58.3298452Z  -e NO_TD \ 2025-09-07T08:52:58.3298720Z  -e TD_DISTRIBUTED \ 2025-09-07T08:52:58.3299016Z  -e PR_LABELS \ 2025-09-07T08:52:58.3299332Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-09-07T08:52:58.3299674Z  -e SCCACHE_BUCKET \ 2025-09-07T08:52:58.3299975Z  -e SCCACHE_REGION \ 2025-09-07T08:52:58.3300268Z  -e XLA_CUDA \ 2025-09-07T08:52:58.3300575Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-09-07T08:52:58.3300959Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-09-07T08:52:58.3301342Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-09-07T08:52:58.3301734Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-09-07T08:52:58.3302101Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-09-07T08:52:58.3302457Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-09-07T08:52:58.3302804Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-09-07T08:52:58.3303147Z  -e DASHBOARD_TAG \ 2025-09-07T08:52:58.3303452Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-09-07T08:52:58.3303834Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-09-07T08:52:58.3304263Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-09-07T08:52:58.3304702Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-09-07T08:52:58.3305269Z  --security-opt seccomp=unconfined \ 2025-09-07T08:52:58.3305637Z  --cap-add=SYS_PTRACE \ 2025-09-07T08:52:58.3305951Z  --ipc=host \ 2025-09-07T08:52:58.3306217Z  ${SHM_OPTS} \ 2025-09-07T08:52:58.3306486Z  --tty \ 2025-09-07T08:52:58.3306736Z  --detach \ 2025-09-07T08:52:58.3307013Z  --name="${container_name}" \ 2025-09-07T08:52:58.3307332Z  ${JENKINS_USER} \ 2025-09-07T08:52:58.3307706Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-09-07T08:52:58.3308124Z  -w /var/lib/jenkins/workspace \ 2025-09-07T08:52:58.3308461Z  "${DOCKER_IMAGE}" \ 2025-09-07T08:52:58.3308743Z  ${DOCKER_SHELL_CMD} 2025-09-07T08:52:58.3309023Z ) 2025-09-07T08:52:58.3309330Z # Propagate download.pytorch.org IP to container 2025-09-07T08:52:58.3310036Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-09-07T08:52:58.3310788Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-09-07T08:52:58.3311202Z  2025-09-07T08:52:58.3311687Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:52:58.3312299Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-09-07T08:52:58.3312851Z fi 2025-09-07T08:52:58.3313056Z  2025-09-07T08:52:58.3313576Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-09-07T08:52:58.3325520Z shell: /usr/bin/bash -e {0} 2025-09-07T08:52:58.3325826Z env: 2025-09-07T08:52:58.3326055Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:52:58.3326396Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:52:58.3326893Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T08:52:58.3327392Z BUILD_ENVIRONMENT: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:52:58.3327787Z PR_NUMBER: 2025-09-07T08:52:58.3328031Z GITHUB_REPOSITORY: pytorch/pytorch 2025-09-07T08:52:58.3328393Z GITHUB_WORKFLOW: inductor-A100-perf-nightly 2025-09-07T08:52:58.3328751Z GITHUB_JOB: test 2025-09-07T08:52:58.3329003Z GITHUB_RUN_ID: 17525309334 2025-09-07T08:52:58.3329277Z GITHUB_RUN_NUMBER: 5418 2025-09-07T08:52:58.3329562Z GITHUB_RUN_ATTEMPT: 1 2025-09-07T08:52:58.3329830Z JOB_ID: 49775768421 2025-09-07T08:52:58.3330488Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T08:52:58.3330992Z BRANCH: main 2025-09-07T08:52:58.3331270Z SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:52:58.3331666Z BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:52:58.3332051Z TEST_CONFIG: inductor_torchbench_perf 2025-09-07T08:52:58.3332367Z SHARD_NUMBER: 5 2025-09-07T08:52:58.3332615Z NUM_TEST_SHARDS: 6 2025-09-07T08:52:58.3333072Z REENABLED_ISSUES: 2025-09-07T08:52:58.3333345Z CONTINUE_THROUGH_ERROR: True 2025-09-07T08:52:58.3333629Z VERBOSE_TEST_LOGS: False 2025-09-07T08:52:58.3333910Z TEST_SHOWLOCALS: False 2025-09-07T08:52:58.3334199Z NO_TEST_TIMEOUT: False 2025-09-07T08:52:58.3334470Z NO_TD: False 2025-09-07T08:52:58.3334697Z TD_DISTRIBUTED: False 2025-09-07T08:52:58.3335027Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-09-07T08:52:58.3335412Z SCCACHE_REGION: us-east-1 2025-09-07T08:52:58.3335689Z SHM_SIZE: 2g 2025-09-07T08:52:58.3336634Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:52:58.3337619Z XLA_CUDA: 2025-09-07T08:52:58.3337989Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:52:58.3338466Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-09-07T08:52:58.3338799Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-09-07T08:52:58.3340138Z 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 2025-09-07T08:52:58.3341693Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-09-07T08:52:58.3342104Z HUGGING_FACE_HUB_TOKEN: *** 2025-09-07T08:52:58.3342541Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-09-07T08:52:58.3343040Z ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T08:52:58.3343552Z ##[endgroup] 2025-09-07T08:52:58.3612433Z + [[ inductor_torchbench_perf == \m\u\l\t\i\g\p\u ]] 2025-09-07T08:52:58.3613047Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *onnx* ]] 2025-09-07T08:52:58.3616166Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:52:58.3616588Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-09-07T08:52:58.3627568Z + TOTAL_AVAILABLE_MEMORY_IN_GB='1120.797 ' 2025-09-07T08:52:58.3627936Z + TOTAL_MEMORY_WITH_SWAP=1123 2025-09-07T08:52:58.3628318Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *\s\3\9\0\x* ]] 2025-09-07T08:52:58.3628718Z + SHM_OPTS=--shm-size=2g 2025-09-07T08:52:58.3628995Z + JENKINS_USER='--user jenkins' 2025-09-07T08:52:58.3629486Z + DOCKER_SHELL_CMD= 2025-09-07T08:52:58.3636833Z +++ nproc --ignore=2 2025-09-07T08:52:58.3650839Z ++ docker run --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all -e SCCACHE_SERVER_PORT=5228 -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=10 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e VLLM_TEST_HUGGING_FACE_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=1120g --memory-swap=1123g --env-file=/tmp/github_env_17525309334 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=2g --tty --detach --name= --user jenkins -v /home/bob/_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 2025-09-07T09:13:38.6402722Z + container_name=31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T09:13:38.6405343Z + grep download.pytorch.org /etc/hosts 2025-09-07T09:13:38.6407439Z + docker exec -i 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea sudo bash -c '/bin/cat >> /etc/hosts' 2025-09-07T09:13:38.6776702Z + echo DOCKER_CONTAINER_ID=31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T09:13:38.6778179Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *\s\3\9\0\x* ]] 2025-09-07T09:13:38.6781114Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T09:13:38.6783635Z + docker exec -t 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-09-07T09:13:39.0748521Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d) 2025-09-07T09:13:39.8963661Z 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) 2025-09-07T09:13:39.8967311Z 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) 2025-09-07T09:13:39.8971942Z 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) 2025-09-07T09:13:39.8977351Z 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) 2025-09-07T09:13:39.8981298Z 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) 2025-09-07T09:13:39.8986472Z 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) 2025-09-07T09:13:39.9000135Z 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) 2025-09-07T09:13:39.9367628Z 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) 2025-09-07T09:13:39.9387242Z 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) 2025-09-07T09:13:39.9423088Z 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) 2025-09-07T09:13:40.8426773Z Installing collected packages: torch 2025-09-07T09:13:52.8956568Z 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. 2025-09-07T09:13:52.8957571Z dall-e 0.1 requires torchvision, which is not installed. 2025-09-07T09:13:52.8958036Z effdet 0.4.1 requires torchvision, which is not installed. 2025-09-07T09:13:52.8958556Z python-doctr 1.0.0 requires torchvision>=0.15.0, which is not installed. 2025-09-07T09:13:52.8959187Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed. 2025-09-07T09:13:52.8959985Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed. 2025-09-07T09:13:52.8960850Z timm 1.0.14 requires torchvision, which is not installed. 2025-09-07T09:13:52.8961751Z Successfully installed torch-2.9.0a0+git93fb23d 2025-09-07T09:13:52.9783335Z + export TERM=vt100 2025-09-07T09:13:52.9783605Z + TERM=vt100 2025-09-07T09:13:52.9786223Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:13:52.9794213Z + source .ci/pytorch/common.sh 2025-09-07T09:13:52.9798055Z +++ dirname .ci/pytorch/common.sh 2025-09-07T09:13:52.9804535Z ++ source .ci/pytorch/common_utils.sh 2025-09-07T09:13:52.9807162Z +++ declare -f -t trap_add 2025-09-07T09:13:52.9810203Z ++ set -ex -o pipefail 2025-09-07T09:13:52.9810535Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:13:52.9810924Z ++ BUILD_TEST_LIBTORCH=0 2025-09-07T09:13:52.9814225Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:13:52.9820930Z + source .ci/pytorch/common-build.sh 2025-09-07T09:13:52.9822408Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *win-* ]] 2025-09-07T09:13:52.9828352Z ++++ dirname .ci/pytorch/common-build.sh 2025-09-07T09:13:52.9835651Z +++ cd .ci/pytorch 2025-09-07T09:13:52.9835902Z +++ pwd -P 2025-09-07T09:13:52.9838165Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-09-07T09:13:52.9838671Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-pch* ]] 2025-09-07T09:13:52.9839039Z ++ which sccache 2025-09-07T09:13:52.9850407Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-09-07T09:13:52.9850855Z ++ sccache --stop-server 2025-09-07T09:13:52.9875658Z ++ true 2025-09-07T09:13:52.9875982Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-09-07T09:13:52.9884869Z ++ trap_add sccache_epilogue EXIT 2025-09-07T09:13:52.9885245Z ++ trap_add_cmd=sccache_epilogue 2025-09-07T09:13:52.9885529Z ++ shift 2025-09-07T09:13:52.9885755Z ++ for trap_add_name in "$@" 2025-09-07T09:13:52.9891210Z ++++ trap -p EXIT 2025-09-07T09:13:52.9893992Z +++ eval 'extract_trap_cmd ' 2025-09-07T09:13:52.9894305Z ++++ extract_trap_cmd 2025-09-07T09:13:52.9894562Z ++++ printf '%s\n' '' 2025-09-07T09:13:52.9894833Z +++ printf '%s\n' sccache_epilogue 2025-09-07T09:13:52.9895877Z ++ trap -- ' 2025-09-07T09:13:52.9896114Z sccache_epilogue' EXIT 2025-09-07T09:13:52.9896700Z ++ [[ -n 1 ]] 2025-09-07T09:13:52.9897152Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-09-07T09:13:52.9897770Z Skipping sccache server initialization, setting environment variables 2025-09-07T09:13:52.9898236Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:13:52.9898550Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:13:52.9898912Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:13:52.9899360Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:13:52.9899785Z ++ export RUST_LOG=sccache::server=error 2025-09-07T09:13:52.9900118Z ++ RUST_LOG=sccache::server=error 2025-09-07T09:13:53.0029312Z ++ sccache --zero-stats 2025-09-07T09:13:53.7519374Z Statistics zeroed. 2025-09-07T09:13:53.7523926Z ++ which ccache 2025-09-07T09:13:53.7540408Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *rocm* ]] 2025-09-07T09:13:53.7540918Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *s390x* ]] 2025-09-07T09:13:53.7541373Z + [[ -d /var/lib/jenkins/workspace ]] 2025-09-07T09:13:53.7544146Z ++ stat -c %u /var/lib/jenkins/workspace 2025-09-07T09:13:53.7556683Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-09-07T09:13:53.7557049Z + trap_add cleanup_workspace EXIT 2025-09-07T09:13:53.7557393Z + trap_add_cmd=cleanup_workspace 2025-09-07T09:13:53.7557740Z + shift 2025-09-07T09:13:53.7557964Z + for trap_add_name in "$@" 2025-09-07T09:13:53.7565293Z +++ trap -p EXIT 2025-09-07T09:13:53.7568064Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-09-07T09:13:53.7568419Z sccache_epilogue'\'' EXIT' 2025-09-07T09:13:53.7568735Z +++ extract_trap_cmd trap -- ' 2025-09-07T09:13:53.7569031Z sccache_epilogue' EXIT 2025-09-07T09:13:53.7569327Z +++ printf '%s\n' ' 2025-09-07T09:13:53.7569585Z sccache_epilogue' 2025-09-07T09:13:53.7569868Z ++ printf '%s\n' cleanup_workspace 2025-09-07T09:13:53.7571190Z + trap -- ' 2025-09-07T09:13:53.7571439Z sccache_epilogue 2025-09-07T09:13:53.7571712Z cleanup_workspace' EXIT 2025-09-07T09:13:53.7572431Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-09-07T09:14:15.5470746Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-09-07T09:14:15.5488881Z + echo 'Environment variables:' 2025-09-07T09:14:15.5489288Z Environment variables: 2025-09-07T09:14:15.5489543Z + env 2025-09-07T09:14:15.5498670Z GITHUB_WORKSPACE=/home/bob/_work/pytorch/pytorch 2025-09-07T09:14:15.5499140Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:14:15.5499493Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T09:14:15.5501515Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:14:15.5501828Z HOSTNAME=31b9433f3a80 2025-09-07T09:14:15.5502339Z GITHUB_PATH=/home/bob/_work/_temp/_runner_file_commands/add_path_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:15.5502928Z GITHUB_ACTION=__run_2 2025-09-07T09:14:15.5503187Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:14:15.5503498Z GITHUB_RUN_NUMBER=5418 2025-09-07T09:14:15.5503779Z TEST_CONFIG=inductor_torchbench_perf 2025-09-07T09:14:15.5504099Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:14:15.5504431Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:14:15.5504847Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:14:15.5505259Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:14:15.5505563Z GITHUB_TRIGGERING_ACTOR=desertfire 2025-09-07T09:14:15.5505852Z GITHUB_REF_TYPE=branch 2025-09-07T09:14:15.5506148Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:15.5506481Z XLA_CUDA= 2025-09-07T09:14:15.5506707Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:14:15.5507104Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:14:15.5507506Z *** 2025-09-07T09:14:15.5507727Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:14:15.5508014Z GITHUB_ACTIONS=true 2025-09-07T09:14:15.5508284Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:14:15.5508621Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:14:15.5509021Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:15.5509402Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:15.5510049Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly.yml@refs/heads/main 2025-09-07T09:14:15.5510627Z UCC_HOME=/usr 2025-09-07T09:14:15.5510857Z VERBOSE_TEST_LOGS=False 2025-09-07T09:14:15.5511122Z GITHUB_REF=refs/heads/main 2025-09-07T09:14:15.5511389Z SHARD_NUMBER=5 2025-09-07T09:14:15.5511614Z GITHUB_REF_PROTECTED=true 2025-09-07T09:14:15.5511884Z HOME=/var/lib/jenkins 2025-09-07T09:14:15.5512141Z SCCACHE_SERVER_PORT=5228 2025-09-07T09:14:15.5512438Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:14:15.5512760Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:14:15.5513117Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:14:15.5513472Z USE_SYSTEM_NCCL=1 2025-09-07T09:14:15.5514040Z NUM_TEST_SHARDS=6 2025-09-07T09:14:15.5514257Z UCX_HOME=/usr 2025-09-07T09:14:15.5514743Z GITHUB_STATE=/home/bob/_work/_temp/_runner_file_commands/save_state_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:15.5515517Z JOB_NAME=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T09:14:15.5516262Z GITHUB_ENV=/home/bob/_work/_temp/_runner_file_commands/set_env_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:15.5516905Z GITHUB_EVENT_PATH=/home/bob/_work/_temp/_github_workflow/event.json 2025-09-07T09:14:15.5517334Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:14:15.5518632Z 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 2025-09-07T09:14:15.5519974Z GITHUB_RUN_ID=17525309334 2025-09-07T09:14:15.5520243Z INSTALLED_OPENBLAS= 2025-09-07T09:14:15.5520772Z GITHUB_STEP_SUMMARY=/home/bob/_work/_temp/_runner_file_commands/step_summary_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:15.5521385Z GITHUB_ACTOR=desertfire 2025-09-07T09:14:15.5521636Z PR_NUMBER= 2025-09-07T09:14:15.5521850Z DESIRED_CUDA=12.8.1 2025-09-07T09:14:15.5522074Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:14:15.5522535Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:14:15.5522885Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:14:15.5523237Z TERM=vt100 2025-09-07T09:14:15.5523439Z INSTALLED_VISION=yes 2025-09-07T09:14:15.5523681Z BRANCH=main 2025-09-07T09:14:15.5523905Z SCCACHE_REGION=us-east-1 2025-09-07T09:14:15.5524180Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:14:15.5524461Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:14:15.5524895Z GITHUB_ACTION_PATH=/home/bob/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:14:15.5525400Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:14:15.5525763Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:14:15.5526103Z REENABLED_ISSUES= 2025-09-07T09:14:15.5526326Z DOCS= 2025-09-07T09:14:15.5526521Z SHLVL=1 2025-09-07T09:14:15.5526720Z MAX_JOBS=10 2025-09-07T09:14:15.5526926Z GITHUB_ACTOR_ID=3659962 2025-09-07T09:14:15.5527267Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:15.5527662Z GITHUB_REF_NAME=main 2025-09-07T09:14:15.5528048Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:14:15.5528471Z GITHUB_JOB=test 2025-09-07T09:14:15.5528702Z NO_TEST_TIMEOUT=False 2025-09-07T09:14:15.5528955Z TD_DISTRIBUTED=False 2025-09-07T09:14:15.5529211Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:14:15.5529518Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:14:15.5529784Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:14:15.5530069Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:14:15.5530875Z 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 2025-09-07T09:14:15.5531702Z GITHUB_BASE_REF= 2025-09-07T09:14:15.5531943Z INSTALLED_ACL= 2025-09-07T09:14:15.5532362Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T09:14:15.5533103Z CI=true 2025-09-07T09:14:15.5533316Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:14:15.5533662Z RUST_LOG=sccache::server=error 2025-09-07T09:14:15.5533937Z JOB_ID=49775768421 2025-09-07T09:14:15.5534164Z GITHUB_HEAD_REF= 2025-09-07T09:14:15.5534380Z GITHUB_ACTION_REF= 2025-09-07T09:14:15.5534669Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:14:15.5535031Z TEST_SHOWLOCALS=False 2025-09-07T09:14:15.5535317Z GITHUB_WORKFLOW=inductor-A100-perf-nightly 2025-09-07T09:14:15.5535650Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:14:15.5536197Z GITHUB_OUTPUT=/home/bob/_work/_temp/_runner_file_commands/set_output_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:15.5536759Z NO_TD=False 2025-09-07T09:14:15.5537000Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:14:15.5537299Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:14:15.5537809Z _=/usr/bin/env 2025-09-07T09:14:15.5538129Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-09-07T09:14:15.5788878Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-09-07T09:14:15.5789559Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-09-07T09:14:15.5790167Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-09-07T09:14:15.5790789Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-09-07T09:14:15.5791258Z + BUILD_DIR=build 2025-09-07T09:14:15.5791513Z + BUILD_RENAMED_DIR=build_renamed 2025-09-07T09:14:15.5791801Z + BUILD_BIN_DIR=build/bin 2025-09-07T09:14:15.5792060Z + SHARD_NUMBER=5 2025-09-07T09:14:15.5792289Z + NUM_TEST_SHARDS=6 2025-09-07T09:14:15.5792547Z + export TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:14:15.5792852Z + TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:14:15.5793133Z + export VALGRIND=ON 2025-09-07T09:14:15.5793383Z + VALGRIND=ON 2025-09-07T09:14:15.5793681Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *clang9* ]] 2025-09-07T09:14:15.5794106Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *xpu* ]] 2025-09-07T09:14:15.5794463Z + detect_cuda_arch 2025-09-07T09:14:16.0132054Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:14:16.0132590Z + command -v nvidia-smi 2025-09-07T09:14:16.0133129Z /usr/bin/nvidia-smi 2025-09-07T09:14:16.0133456Z ++ nvidia-smi --query-gpu=compute_cap --format=csv 2025-09-07T09:14:16.0133835Z ++ tail -n 1 2025-09-07T09:14:16.0339450Z + TORCH_CUDA_ARCH_LIST=8.0 2025-09-07T09:14:16.0339794Z + export TORCH_CUDA_ARCH_LIST 2025-09-07T09:14:16.0340142Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *s390x* ]] 2025-09-07T09:14:16.0340512Z + [[ 0 == \1 ]] 2025-09-07T09:14:16.0340922Z + [[ True == \1 ]] 2025-09-07T09:14:16.0341227Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *bazel* ]] 2025-09-07T09:14:16.0343774Z ++ realpath build/custom_test_artifacts 2025-09-07T09:14:16.0352505Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-09-07T09:14:16.0353032Z + [[ -n '' ]] 2025-09-07T09:14:16.0353277Z + echo 'Environment variables' 2025-09-07T09:14:16.0353556Z Environment variables 2025-09-07T09:14:16.0353800Z + env 2025-09-07T09:14:16.0360570Z GITHUB_WORKSPACE=/home/bob/_work/pytorch/pytorch 2025-09-07T09:14:16.0360974Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:14:16.0361337Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T09:14:16.0361950Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:14:16.0362251Z HOSTNAME=31b9433f3a80 2025-09-07T09:14:16.0362758Z GITHUB_PATH=/home/bob/_work/_temp/_runner_file_commands/add_path_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:16.0363322Z GITHUB_ACTION=__run_2 2025-09-07T09:14:16.0363581Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:14:16.0363893Z GITHUB_RUN_NUMBER=5418 2025-09-07T09:14:16.0364167Z TEST_CONFIG=inductor_torchbench_perf 2025-09-07T09:14:16.0364501Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:14:16.0364828Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:14:16.0365152Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:14:16.0365548Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:14:16.0365853Z GITHUB_TRIGGERING_ACTOR=desertfire 2025-09-07T09:14:16.0366163Z GITHUB_REF_TYPE=branch 2025-09-07T09:14:16.0366406Z TORCH_CUDA_ARCH_LIST=8.0 2025-09-07T09:14:16.0366711Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:16.0367046Z XLA_CUDA= 2025-09-07T09:14:16.0367315Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:14:16.0367728Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:14:16.0368212Z *** 2025-09-07T09:14:16.0368422Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:14:16.0368710Z GITHUB_ACTIONS=true 2025-09-07T09:14:16.0368967Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:14:16.0369302Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:14:16.0369703Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:16.0370080Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:16.0370999Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly.yml@refs/heads/main 2025-09-07T09:14:16.0371592Z UCC_HOME=/usr 2025-09-07T09:14:16.0371818Z TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:14:16.0372106Z VERBOSE_TEST_LOGS=False 2025-09-07T09:14:16.0372381Z GITHUB_REF=refs/heads/main 2025-09-07T09:14:16.0372648Z SHARD_NUMBER=5 2025-09-07T09:14:16.0373040Z GITHUB_REF_PROTECTED=true 2025-09-07T09:14:16.0373320Z HOME=/var/lib/jenkins 2025-09-07T09:14:16.0373579Z SCCACHE_SERVER_PORT=5228 2025-09-07T09:14:16.0373868Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:14:16.0374211Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:14:16.0374567Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:14:16.0374914Z USE_SYSTEM_NCCL=1 2025-09-07T09:14:16.0375136Z NUM_TEST_SHARDS=6 2025-09-07T09:14:16.0375366Z UCX_HOME=/usr 2025-09-07T09:14:16.0375850Z GITHUB_STATE=/home/bob/_work/_temp/_runner_file_commands/save_state_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:16.0376623Z JOB_NAME=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T09:14:16.0377362Z GITHUB_ENV=/home/bob/_work/_temp/_runner_file_commands/set_env_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:16.0378156Z GITHUB_EVENT_PATH=/home/bob/_work/_temp/_github_workflow/event.json 2025-09-07T09:14:16.0378591Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:14:16.0379893Z 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 2025-09-07T09:14:16.0381223Z GITHUB_RUN_ID=17525309334 2025-09-07T09:14:16.0381495Z INSTALLED_OPENBLAS= 2025-09-07T09:14:16.0382024Z GITHUB_STEP_SUMMARY=/home/bob/_work/_temp/_runner_file_commands/step_summary_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:16.0382637Z GITHUB_ACTOR=desertfire 2025-09-07T09:14:16.0382891Z PR_NUMBER= 2025-09-07T09:14:16.0383115Z DESIRED_CUDA=12.8.1 2025-09-07T09:14:16.0383344Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:14:16.0383583Z VALGRIND=ON 2025-09-07T09:14:16.0383813Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:14:16.0384141Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:14:16.0384495Z TERM=vt100 2025-09-07T09:14:16.0384788Z INSTALLED_VISION=yes 2025-09-07T09:14:16.0385048Z BRANCH=main 2025-09-07T09:14:16.0385257Z SCCACHE_REGION=us-east-1 2025-09-07T09:14:16.0385537Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:14:16.0385833Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:14:16.0386272Z GITHUB_ACTION_PATH=/home/bob/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:14:16.0386768Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:14:16.0387134Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:14:16.0387487Z REENABLED_ISSUES= 2025-09-07T09:14:16.0387719Z DOCS= 2025-09-07T09:14:16.0387908Z SHLVL=1 2025-09-07T09:14:16.0388109Z MAX_JOBS=10 2025-09-07T09:14:16.0388338Z GITHUB_ACTOR_ID=3659962 2025-09-07T09:14:16.0388680Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:16.0389059Z GITHUB_REF_NAME=main 2025-09-07T09:14:16.0389447Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:14:16.0389885Z GITHUB_JOB=test 2025-09-07T09:14:16.0390122Z NO_TEST_TIMEOUT=False 2025-09-07T09:14:16.0390366Z TD_DISTRIBUTED=False 2025-09-07T09:14:16.0390633Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:14:16.0390944Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:14:16.0391216Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:14:16.0391479Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:14:16.0392289Z 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 2025-09-07T09:14:16.0393130Z GITHUB_BASE_REF= 2025-09-07T09:14:16.0393366Z INSTALLED_ACL= 2025-09-07T09:14:16.0393775Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T09:14:16.0394433Z CI=true 2025-09-07T09:14:16.0394663Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:14:16.0394999Z RUST_LOG=sccache::server=error 2025-09-07T09:14:16.0395263Z JOB_ID=49775768421 2025-09-07T09:14:16.0395498Z GITHUB_HEAD_REF= 2025-09-07T09:14:16.0395735Z GITHUB_ACTION_REF= 2025-09-07T09:14:16.0396035Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:14:16.0396388Z TEST_SHOWLOCALS=False 2025-09-07T09:14:16.0396685Z GITHUB_WORKFLOW=inductor-A100-perf-nightly 2025-09-07T09:14:16.0397035Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:14:16.0397592Z GITHUB_OUTPUT=/home/bob/_work/_temp/_runner_file_commands/set_output_2a57e6bd-b4de-4aa5-855b-4b0e4377597c 2025-09-07T09:14:16.0398160Z NO_TD=False 2025-09-07T09:14:16.0398388Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:14:16.0398713Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:14:16.0399037Z _=/usr/bin/env 2025-09-07T09:14:16.0399254Z + echo 'Testing pytorch' 2025-09-07T09:14:16.0399519Z Testing pytorch 2025-09-07T09:14:16.0399763Z + export LANG=C.UTF-8 2025-09-07T09:14:16.0400012Z + LANG=C.UTF-8 2025-09-07T09:14:16.0400219Z + PR_NUMBER= 2025-09-07T09:14:16.0400484Z + [[ inductor_torchbench_perf == \d\e\f\a\u\l\t ]] 2025-09-07T09:14:16.0400895Z + [[ inductor_torchbench_perf == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-09-07T09:14:16.0401445Z + [[ inductor_torchbench_perf == \s\l\o\w ]] 2025-09-07T09:14:16.0401870Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *slow-gradcheck* ]] 2025-09-07T09:14:16.0402343Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:14:16.0402745Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:14:16.0403107Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:14:16.0403459Z + [[ inductor_torchbench_perf == *crossref* ]] 2025-09-07T09:14:16.0403843Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:14:16.0404279Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *xpu* ]] 2025-09-07T09:14:16.0404713Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *-bazel-* ]] 2025-09-07T09:14:16.0405109Z + pip_install ninja==1.10.2 2025-09-07T09:14:16.0405472Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:14:16.0405950Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-09-07T09:14:17.2463743Z Collecting ninja==1.10.2 2025-09-07T09:14:17.6318938Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-09-07T09:14:17.8952579Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-09-07T09:14:19.9437380Z Installing collected packages: ninja 2025-09-07T09:14:19.9437798Z Attempting uninstall: ninja 2025-09-07T09:14:19.9447161Z Found existing installation: ninja 1.11.1.3 2025-09-07T09:14:19.9468237Z Uninstalling ninja-1.11.1.3: 2025-09-07T09:14:20.0709445Z Successfully uninstalled ninja-1.11.1.3 2025-09-07T09:14:20.3444461Z Successfully installed ninja-1.10.2 2025-09-07T09:14:20.4308885Z + 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 2025-09-07T09:14:20.4310619Z + 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 2025-09-07T09:14:20.4311670Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *aarch64* ]] 2025-09-07T09:14:20.4312131Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *asan* ]] 2025-09-07T09:14:20.4312560Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-debug* ]] 2025-09-07T09:14:20.4313000Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *-bazel-* ]] 2025-09-07T09:14:20.4313616Z + echo 'We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm80. Expect the assertion to pass' 2025-09-07T09:14:20.4314387Z We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm80. Expect the assertion to pass 2025-09-07T09:14:20.4314906Z + cd test 2025-09-07T09:14:20.4315646Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-09-07T09:14:21.1133073Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:21.1134536Z import pynvml # type: ignore[import] 2025-09-07T09:14:22.3284103Z + [[ inductor_torchbench_perf == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-09-07T09:14:22.3284627Z + [[ inductor_torchbench_perf == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-09-07T09:14:22.3285135Z + [[ inductor_torchbench_perf == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-09-07T09:14:22.3287959Z + DYNAMO_BENCHMARK_FLAGS=() 2025-09-07T09:14:22.3288824Z + [[ inductor_torchbench_perf == *pr_time_benchmarks* ]] 2025-09-07T09:14:22.3289280Z + [[ inductor_torchbench_perf == *dynamo_eager* ]] 2025-09-07T09:14:22.3289692Z + [[ inductor_torchbench_perf == *aot_eager* ]] 2025-09-07T09:14:22.3290071Z + [[ inductor_torchbench_perf == *aot_inductor* ]] 2025-09-07T09:14:22.3290482Z + [[ inductor_torchbench_perf == *max_autotune_inductor* ]] 2025-09-07T09:14:22.3290907Z + [[ inductor_torchbench_perf == *inductor* ]] 2025-09-07T09:14:22.3291652Z + [[ inductor_torchbench_perf != *perf* ]] 2025-09-07T09:14:22.3292003Z + [[ inductor_torchbench_perf == *dynamic* ]] 2025-09-07T09:14:22.3292343Z + [[ inductor_torchbench_perf == *cpu* ]] 2025-09-07T09:14:22.3292704Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-09-07T09:14:22.3311984Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *libtorch* ]] 2025-09-07T09:14:22.3312448Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-bazel-* ]] 2025-09-07T09:14:22.3315384Z + cd test 2025-09-07T09:14:22.3316205Z + python -c 'import torch; print(torch.__config__.show())' 2025-09-07T09:14:22.8945975Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:22.8947432Z import pynvml # type: ignore[import] 2025-09-07T09:14:24.2607158Z PyTorch built with: 2025-09-07T09:14:24.2607507Z - GCC 9.5 2025-09-07T09:14:24.2607734Z - C++ Version: 201703 2025-09-07T09:14:24.2608323Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:14:24.2609065Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:14:24.2609532Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:14:24.2609887Z - LAPACK is enabled (usually provided by MKL) 2025-09-07T09:14:24.2610229Z - NNPACK is enabled 2025-09-07T09:14:24.2610483Z - CPU capability usage: AVX512 2025-09-07T09:14:24.2610781Z - CUDA Runtime 12.8 2025-09-07T09:14:24.2611137Z - NVCC architecture flags: -gencode;arch=compute_80,code=sm_80 2025-09-07T09:14:24.2611553Z - CuDNN 90.8 2025-09-07T09:14:24.2616635Z - 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, 2025-09-07T09:14:24.2621987Z 2025-09-07T09:14:26.2711679Z + cd test 2025-09-07T09:14:26.2712096Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-09-07T09:14:26.9816966Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:26.9819511Z import pynvml # type: ignore[import] 2025-09-07T09:14:27.7820284Z ATen/Parallel: 2025-09-07T09:14:27.7820627Z at::get_num_threads() : 12 2025-09-07T09:14:27.7820937Z at::get_num_interop_threads() : 48 2025-09-07T09:14:27.7821243Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:14:27.7821573Z omp_get_max_threads() : 12 2025-09-07T09:14:27.7822158Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:14:27.7822780Z mkl_get_max_threads() : 12 2025-09-07T09:14:27.7829534Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:14:27.7830258Z std::thread::hardware_concurrency() : 96 2025-09-07T09:14:27.7830589Z Environment variables: 2025-09-07T09:14:27.7830859Z OMP_NUM_THREADS : [not set] 2025-09-07T09:14:27.7831129Z MKL_NUM_THREADS : [not set] 2025-09-07T09:14:27.7831417Z ATen parallel backend: OpenMP 2025-09-07T09:14:27.7831622Z 2025-09-07T09:14:28.0816961Z + [[ inductor_torchbench_perf == *numpy_2* ]] 2025-09-07T09:14:28.0817443Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *aarch64* ]] 2025-09-07T09:14:28.0817871Z + [[ inductor_torchbench_perf == *backward* ]] 2025-09-07T09:14:28.0818213Z + [[ inductor_torchbench_perf == *xla* ]] 2025-09-07T09:14:28.0818580Z + [[ inductor_torchbench_perf == *vllm* ]] 2025-09-07T09:14:28.0818936Z + [[ inductor_torchbench_perf == *executorch* ]] 2025-09-07T09:14:28.0819337Z + [[ inductor_torchbench_perf == \j\i\t\_\l\e\g\a\c\y ]] 2025-09-07T09:14:28.0819766Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *libtorch* ]] 2025-09-07T09:14:28.0820200Z + [[ inductor_torchbench_perf == distributed ]] 2025-09-07T09:14:28.0820605Z + [[ inductor_torchbench_perf == *operator_benchmark* ]] 2025-09-07T09:14:28.0821040Z + [[ inductor_torchbench_perf == *inductor_distributed* ]] 2025-09-07T09:14:28.0821460Z + [[ inductor_torchbench_perf == *inductor-halide* ]] 2025-09-07T09:14:28.0821886Z + [[ inductor_torchbench_perf == *inductor-triton-cpu* ]] 2025-09-07T09:14:28.0822349Z + [[ inductor_torchbench_perf == *inductor-micro-benchmark* ]] 2025-09-07T09:14:28.0822790Z + [[ inductor_torchbench_perf == *huggingface* ]] 2025-09-07T09:14:28.0823138Z + [[ inductor_torchbench_perf == *timm* ]] 2025-09-07T09:14:28.0823491Z + [[ inductor_torchbench_perf == cachebench ]] 2025-09-07T09:14:28.0823879Z + [[ inductor_torchbench_perf == verify_cachebench ]] 2025-09-07T09:14:28.0824267Z + [[ inductor_torchbench_perf == *torchbench* ]] 2025-09-07T09:14:28.0824590Z + install_torchaudio 2025-09-07T09:14:28.0824926Z + local commit 2025-09-07T09:14:28.0825172Z ++ get_pinned_commit audio 2025-09-07T09:14:28.0825461Z ++ cat .github/ci_commit_pins/audio.txt 2025-09-07T09:14:28.0834941Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:14:28.0835666Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio 2025-09-07T09:14:28.0836584Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:14:28.0837165Z + local wheel_dir=dist/audio 2025-09-07T09:14:28.0837442Z + local found_whl=0 2025-09-07T09:14:28.0837685Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:28.0838141Z + [[ -f dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:14:28.0838951Z + found_whl=1 2025-09-07T09:14:28.0839162Z + break 2025-09-07T09:14:28.0839347Z + '[' 1 == 0 ']' 2025-09-07T09:14:28.0839584Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:28.0840084Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:28.0840739Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:14:28.0841198Z + local args 2025-09-07T09:14:28.0841575Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:14:28.0842061Z + for path in "${args[@]}" 2025-09-07T09:14:28.0842530Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:14:28.0843213Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:28.0843983Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:28.4470926Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:28.4550131Z Installing collected packages: torchaudio 2025-09-07T09:14:29.0804697Z Successfully installed torchaudio-2.8.0a0+2e30055 2025-09-07T09:14:29.1207855Z + install_torchvision 2025-09-07T09:14:29.1208525Z + local orig_preload 2025-09-07T09:14:29.1208773Z + local commit 2025-09-07T09:14:29.1209030Z ++ get_pinned_commit vision 2025-09-07T09:14:29.1209343Z ++ cat .github/ci_commit_pins/vision.txt 2025-09-07T09:14:29.1216376Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:14:29.1216727Z + orig_preload= 2025-09-07T09:14:29.1216950Z + '[' -n '' ']' 2025-09-07T09:14:29.1217250Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:14:29.1217621Z + export FORCE_CUDA=1 2025-09-07T09:14:29.1217868Z + FORCE_CUDA=1 2025-09-07T09:14:29.1218083Z + export WITH_CUDA=1 2025-09-07T09:14:29.1218323Z + WITH_CUDA=1 2025-09-07T09:14:29.1218920Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-09-07T09:14:29.1219862Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:14:29.1220444Z + local wheel_dir=dist/vision 2025-09-07T09:14:29.1220730Z + local found_whl=0 2025-09-07T09:14:29.1220986Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:29.1221455Z + [[ -f dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:14:29.1221910Z + found_whl=1 2025-09-07T09:14:29.1222127Z + break 2025-09-07T09:14:29.1222325Z + '[' 1 == 0 ']' 2025-09-07T09:14:29.1222572Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:29.1223059Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.1223750Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:14:29.1224218Z + local args 2025-09-07T09:14:29.1224626Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:14:29.1225243Z + for path in "${args[@]}" 2025-09-07T09:14:29.1225719Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:14:29.1226442Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.1227259Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.4818390Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.4986891Z Installing collected packages: torchvision 2025-09-07T09:14:30.3553572Z Successfully installed torchvision-0.22.0a0+966da7e 2025-09-07T09:14:30.3999348Z + '[' -n '' ']' 2025-09-07T09:14:30.3999597Z + id=4 2025-09-07T09:14:30.3999824Z + pip_install opencv-python==4.8.0.74 2025-09-07T09:14:30.4000247Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:14:30.4002177Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74 2025-09-07T09:14:31.1489369Z Collecting opencv-python==4.8.0.74 2025-09-07T09:14:31.1902951Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB) 2025-09-07T09:14:31.6294167Z 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) 2025-09-07T09:14:31.6458469Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB) 2025-09-07T09:14:37.6995207Z Installing collected packages: opencv-python 2025-09-07T09:14:37.6995643Z Attempting uninstall: opencv-python 2025-09-07T09:14:37.7008208Z Found existing installation: opencv-python 4.11.0.86 2025-09-07T09:14:37.7082316Z Uninstalling opencv-python-4.11.0.86: 2025-09-07T09:14:37.8618818Z Successfully uninstalled opencv-python-4.11.0.86 2025-09-07T09:14:39.1011080Z Successfully installed opencv-python-4.8.0.74 2025-09-07T09:14:39.1991427Z + [[ inductor_torchbench_perf == *inductor_torchbench_smoketest_perf* ]] 2025-09-07T09:14:39.1992050Z + [[ inductor_torchbench_perf == *inductor_torchbench_cpu_smoketest_perf* ]] 2025-09-07T09:14:39.1992599Z + [[ inductor_torchbench_perf == *torchbench_gcp_smoketest* ]] 2025-09-07T09:14:39.1993480Z + [[ inductor_torchbench_perf != *cpu* ]] 2025-09-07T09:14:39.1993824Z + install_torchrec_and_fbgemm 2025-09-07T09:14:39.1994099Z + local torchrec_commit 2025-09-07T09:14:39.1995605Z ++ get_pinned_commit torchrec 2025-09-07T09:14:39.1995921Z ++ cat .github/ci_commit_pins/torchrec.txt 2025-09-07T09:14:39.2007469Z + torchrec_commit=6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:14:39.2007853Z + local fbgemm_commit 2025-09-07T09:14:39.2011126Z ++ get_pinned_commit fbgemm 2025-09-07T09:14:39.2011423Z ++ cat .github/ci_commit_pins/fbgemm.txt 2025-09-07T09:14:39.2022582Z + fbgemm_commit=de731af65b4f04696e85c729e3282450b51b95fd 2025-09-07T09:14:39.2023013Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:14:39.2023410Z + pip_uninstall torchrec-nightly 2025-09-07T09:14:39.2023736Z + pip3 uninstall -y torchrec-nightly 2025-09-07T09:14:39.5650364Z WARNING: Skipping torchrec-nightly as it is not installed. 2025-09-07T09:14:39.6030968Z + pip_uninstall fbgemm-gpu-nightly 2025-09-07T09:14:39.6031367Z + pip3 uninstall -y fbgemm-gpu-nightly 2025-09-07T09:14:39.9625774Z WARNING: Skipping fbgemm-gpu-nightly as it is not installed. 2025-09-07T09:14:39.9996112Z + pip_install setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:14:39.9996688Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:14:39.9997340Z + python3 -m pip install --progress-bar off setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:14:40.3520847Z Requirement already satisfied: setuptools-git-versioning in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (2.1.0) 2025-09-07T09:14:40.3521855Z Requirement already satisfied: scikit-build in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.18.1) 2025-09-07T09:14:40.3522806Z Requirement already satisfied: pyre-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.0.32) 2025-09-07T09:14:40.3536242Z Requirement already satisfied: packaging in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (25.0) 2025-09-07T09:14:40.3539400Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (80.9.0) 2025-09-07T09:14:40.3546688Z 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) 2025-09-07T09:14:40.3591221Z Requirement already satisfied: distro in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (1.9.0) 2025-09-07T09:14:40.3600104Z 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) 2025-09-07T09:14:40.3608196Z Requirement already satisfied: typing-inspect in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (0.9.0) 2025-09-07T09:14:40.3611567Z Requirement already satisfied: typing-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (4.15.0) 2025-09-07T09:14:40.3694034Z 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) 2025-09-07T09:14:41.3835512Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:14:41.3836337Z + pip_build_and_install git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 dist/torchrec 2025-09-07T09:14:41.3837304Z + local build_target=git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:14:41.3837919Z + local wheel_dir=dist/torchrec 2025-09-07T09:14:41.3838204Z + local found_whl=0 2025-09-07T09:14:41.3838481Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:41.3838855Z + [[ -f dist/torchrec/torchrec-0.3.2-py3-none-any.whl ]] 2025-09-07T09:14:41.3839209Z + found_whl=1 2025-09-07T09:14:41.3839423Z + break 2025-09-07T09:14:41.3839625Z + '[' 1 == 0 ']' 2025-09-07T09:14:41.3839870Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:41.3846105Z + pip_install_whl dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:41.3846830Z + args=('dist/torchrec/torchrec-0.3.2-py3-none-any.whl') 2025-09-07T09:14:41.3847200Z + local args 2025-09-07T09:14:41.3847523Z + [[ dist/torchrec/torchrec-0.3.2-py3-none-any.whl == *\ * ]] 2025-09-07T09:14:41.3847919Z + for path in "${args[@]}" 2025-09-07T09:14:41.3848305Z + echo 'Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl' 2025-09-07T09:14:41.3848803Z Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:41.3849389Z + python3 -mpip install --no-index --no-deps dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:41.7405902Z Processing ./dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:41.7480116Z Installing collected packages: torchrec 2025-09-07T09:14:42.4184091Z Successfully installed torchrec-0.3.2 2025-09-07T09:14:42.4569949Z + pip_build_and_install git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu dist/fbgemm_gpu 2025-09-07T09:14:42.4571174Z + local build_target=git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu 2025-09-07T09:14:42.4571892Z + local wheel_dir=dist/fbgemm_gpu 2025-09-07T09:14:42.4572190Z + local found_whl=0 2025-09-07T09:14:42.4572477Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:42.4573260Z + [[ -f dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:14:42.4573716Z + found_whl=1 2025-09-07T09:14:42.4573934Z + break 2025-09-07T09:14:42.4574135Z + '[' 1 == 0 ']' 2025-09-07T09:14:42.4574382Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:42.4574876Z + pip_install_whl dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:42.4575542Z + args=('dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:14:42.4575996Z + local args 2025-09-07T09:14:42.4576394Z + [[ dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:14:42.4576884Z + for path in "${args[@]}" 2025-09-07T09:14:42.4577340Z + echo 'Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:14:42.4578028Z Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:42.4578822Z + python3 -mpip install --no-index --no-deps dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:42.8124731Z Processing ./dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:43.0952083Z Installing collected packages: fbgemm-gpu 2025-09-07T09:14:45.5717899Z Successfully installed fbgemm-gpu-0.4.1.post421 2025-09-07T09:14:45.6144888Z + PYTHONPATH=/torchbench 2025-09-07T09:14:45.6145216Z + test_dynamo_benchmark torchbench 4 2025-09-07T09:14:45.6149272Z ++ pwd 2025-09-07T09:14:45.6151489Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:45.6152158Z + local suite=torchbench 2025-09-07T09:14:45.6152536Z + shift 2025-09-07T09:14:45.6152861Z + local shard_id=4 2025-09-07T09:14:45.6153197Z + shift 2025-09-07T09:14:45.6153579Z + [[ inductor_torchbench_perf == *perf_compare* ]] 2025-09-07T09:14:45.6154128Z + [[ inductor_torchbench_perf == *perf* ]] 2025-09-07T09:14:45.6154623Z + [[ inductor_torchbench_perf == *b200* ]] 2025-09-07T09:14:45.6155201Z + test_single_dynamo_benchmark dashboard torchbench 4 2025-09-07T09:14:45.6155760Z ++ pwd 2025-09-07T09:14:45.6157624Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:45.6158369Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:45.6174083Z + local name=dashboard 2025-09-07T09:14:45.6174510Z + shift 2025-09-07T09:14:45.6174849Z + local suite=torchbench 2025-09-07T09:14:45.6175227Z + shift 2025-09-07T09:14:45.6175511Z + local shard_id=4 2025-09-07T09:14:45.6175824Z + shift 2025-09-07T09:14:45.6176128Z + partition_flags=() 2025-09-07T09:14:45.6176519Z + local partition_flags 2025-09-07T09:14:45.6177272Z + [[ -n 6 ]] 2025-09-07T09:14:45.6177599Z + [[ -n 4 ]] 2025-09-07T09:14:45.6178224Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id") 2025-09-07T09:14:45.6179049Z + [[ inductor_torchbench_perf == *perf_compare* ]] 2025-09-07T09:14:45.6179625Z + [[ inductor_torchbench_perf == *perf* ]] 2025-09-07T09:14:45.6180389Z + test_perf_for_dashboard torchbench --device cuda --total-partitions 6 --partition-id 4 2025-09-07T09:14:45.6181165Z ++ pwd 2025-09-07T09:14:45.6181620Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:45.6182324Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:45.6193520Z + local suite=torchbench 2025-09-07T09:14:45.6193962Z + shift 2025-09-07T09:14:45.6194295Z + local backend=inductor 2025-09-07T09:14:45.6194675Z + modes=() 2025-09-07T09:14:45.6194987Z + local modes 2025-09-07T09:14:45.6196987Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *training-true* ]] 2025-09-07T09:14:45.6199131Z + modes+=(training) 2025-09-07T09:14:45.6201151Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *inference-true* ]] 2025-09-07T09:14:45.6203281Z + modes+=(inference) 2025-09-07T09:14:45.6203687Z + targets=('accuracy' 'performance') 2025-09-07T09:14:45.6204141Z + local targets 2025-09-07T09:14:45.6204478Z + local device=cuda 2025-09-07T09:14:45.6204854Z + [[ inductor_torchbench_perf == *cpu* ]] 2025-09-07T09:14:45.6205422Z + [[ inductor_torchbench_perf == *cuda_a10g* ]] 2025-09-07T09:14:45.6205966Z + [[ inductor_torchbench_perf == *h100* ]] 2025-09-07T09:14:45.6206513Z + [[ inductor_torchbench_perf == *b200* ]] 2025-09-07T09:14:45.6207011Z + [[ inductor_torchbench_perf == *rocm* ]] 2025-09-07T09:14:45.6207508Z + for mode in "${modes[@]}" 2025-09-07T09:14:45.6207919Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:14:45.6208400Z + [[ training == \t\r\a\i\n\i\n\g ]] 2025-09-07T09:14:45.6208844Z + dtype=amp 2025-09-07T09:14:45.6209189Z + for target in "${targets[@]}" 2025-09-07T09:14:45.6209605Z + target_flag=('--accuracy') 2025-09-07T09:14:45.6210000Z + local target_flag 2025-09-07T09:14:45.6210379Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:14:45.6210876Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T09:14:45.6211378Z + target_flag+=(--no-translation-validation) 2025-09-07T09:14:45.6213908Z + [[ 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* ]] 2025-09-07T09:14:45.6218090Z + [[ 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* ]] 2025-09-07T09:14:45.6222034Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:14:46.2235349Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:46.2237851Z import pynvml # type: ignore[import] 2025-09-07T09:14:50.0643652Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:50.0645120Z import pynvml # type: ignore[import] 2025-09-07T09:14:52.7083626Z 2025-09-07T09:14:53.6092212Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:14:53.6093201Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:14:53.6093789Z cuda train phlippe_resnet 2025-09-07T09:15:05.5181109Z pass 2025-09-07T09:15:08.7095891Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:15:08.7097366Z import pynvml # type: ignore[import] 2025-09-07T09:15:11.3437044Z 2025-09-07T09:15:12.7551758Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:12.7552121Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:15:12.7552492Z cuda train pytorch_CycleGAN_and_pix2pix 2025-09-07T09:15:38.0761703Z W0907 09:15:38.075000 938 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:15:46.5275127Z pass 2025-09-07T09:15:49.8684822Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:15:49.8686254Z import pynvml # type: ignore[import] 2025-09-07T09:15:52.6359630Z 2025-09-07T09:15:54.1457180Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:54.1457567Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:15:54.1457905Z cuda train pytorch_stargan 2025-09-07T09:16:10.8564244Z pass 2025-09-07T09:16:14.0667186Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:14.0668619Z import pynvml # type: ignore[import] 2025-09-07T09:16:17.1057326Z 2025-09-07T09:16:18.3024002Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:16:18.3024395Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:16:18.3024800Z cuda train pytorch_unet 2025-09-07T09:16:47.7893627Z W0907 09:16:47.788000 2578 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:16:59.5277676Z pass_due_to_skip 2025-09-07T09:17:03.4415569Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:17:03.4417028Z import pynvml # type: ignore[import] 2025-09-07T09:17:06.2830709Z 2025-09-07T09:17:07.1510095Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/resnet152-394f9c45.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/resnet152-394f9c45.pth 2025-09-07T09:17:07.1677830Z 2025-09-07T09:17:07.1678021Z 2025-09-07T09:17:07.2685708Z 0% 0.00/230M [00:00 will be ignored 2025-09-07T09:19:40.1961178Z pass 2025-09-07T09:19:48.3043829Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:19:48.3045274Z import pynvml # type: ignore[import] 2025-09-07T09:19:51.0538164Z 2025-09-07T09:19:51.3822472Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth 2025-09-07T09:19:51.4049308Z 2025-09-07T09:19:51.4049321Z 2025-09-07T09:19:51.5053338Z 0% 0.00/44.7M [00:00 will be ignored 2025-09-07T09:21:11.9254074Z pass 2025-09-07T09:21:16.5195468Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:21:16.5196942Z import pynvml # type: ignore[import] 2025-09-07T09:21:19.3157647Z 2025-09-07T09:21:21.7122958Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:21:21.7123352Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:21:21.7123686Z cuda train resnet50_quantized_qat 2025-09-07T09:21:21.7124078Z Traceback (most recent call last): 2025-09-07T09:21:21.7124629Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:21:21.7125233Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:21:21.7125907Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:21:21.7126588Z pred = mod(*cloned_inputs) 2025-09-07T09:21:21.7127180Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:21:21.7127853Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:21:21.7128508Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:21:21.7129100Z raise e 2025-09-07T09:21:21.7129605Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:21:21.7130325Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:21:21.7131126Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:21:21.7131813Z return self._call_impl(*args, **kwargs) 2025-09-07T09:21:21.7132448Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:21:21.7133344Z return forward_call(*args, **kwargs) 2025-09-07T09:21:21.7133682Z File ".3", line 167, in forward 2025-09-07T09:21:21.7134177Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:21:21.7134999Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:21:21.7135691Z return self._call_impl(*args, **kwargs) 2025-09-07T09:21:21.7136311Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:21:21.7136948Z return forward_call(*args, **kwargs) 2025-09-07T09:21:21.7137620Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:21:21.7138336Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:21:21.7139087Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:21:21.7139368Z 2025-09-07T09:21:21.7139584Z The above exception was the direct cause of the following exception: 2025-09-07T09:21:21.7139928Z 2025-09-07T09:21:21.7140036Z Traceback (most recent call last): 2025-09-07T09:21:21.7140535Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:21:21.7141044Z ) = runner.load_model( 2025-09-07T09:21:21.7141552Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:21:21.7142132Z self.validate_model(model, example_inputs) 2025-09-07T09:21:21.7142718Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:21:21.7143318Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:21:21.7143677Z RuntimeError: Eager run failed 2025-09-07T09:21:21.7143863Z 2025-09-07T09:21:21.7143949Z eager_fail_to_run 2025-09-07T09:21:23.4785016Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:21:23.4788022Z import pynvml # type: ignore[import] 2025-09-07T09:21:26.4853694Z 2025-09-07T09:21:27.1265331Z 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 2025-09-07T09:21:27.1536131Z 2025-09-07T09:21:27.1536153Z 2025-09-07T09:21:27.2541080Z 0% 0.00/95.8M [00:00 will be ignored 2025-09-07T09:22:21.7742344Z pass 2025-09-07T09:22:26.4539576Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:22:26.4542320Z import pynvml # type: ignore[import] 2025-09-07T09:22:29.1185581Z 2025-09-07T09:22:37.1712692Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:22:37.1713074Z loading model: 0it [00:08, ?it/s] 2025-09-07T09:22:37.1713392Z cuda train sam 2025-09-07T09:22:37.1723771Z Traceback (most recent call last): 2025-09-07T09:22:37.1724401Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:22:37.1725007Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:22:37.1725680Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:22:37.1726348Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:22:37.1726918Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:22:37.1727485Z torch.autograd.backward( 2025-09-07T09:22:37.1728061Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:22:37.1728664Z _engine_run_backward( 2025-09-07T09:22:37.1729626Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:22:37.1730539Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:22:37.1731282Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:22:37.1731686Z 2025-09-07T09:22:37.1731902Z The above exception was the direct cause of the following exception: 2025-09-07T09:22:37.1732234Z 2025-09-07T09:22:37.1732361Z Traceback (most recent call last): 2025-09-07T09:22:37.1733101Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:22:37.1733606Z ) = runner.load_model( 2025-09-07T09:22:37.1734119Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:22:37.1734719Z self.validate_model(model, example_inputs) 2025-09-07T09:22:37.1735310Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:22:37.1735899Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:22:37.1736255Z RuntimeError: Eager run failed 2025-09-07T09:22:37.1736459Z 2025-09-07T09:22:37.1736547Z eager_fail_to_run 2025-09-07T09:22:38.8997374Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:22:38.8998849Z import pynvml # type: ignore[import] 2025-09-07T09:22:41.6740752Z 2025-09-07T09:22:41.8804072Z 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 2025-09-07T09:22:41.9057988Z 2025-09-07T09:22:41.9058300Z 2025-09-07T09:22:41.9848801Z 0% 0.00/8.79M [00:00 will be ignored 2025-09-07T09:24:22.1997772Z pass 2025-09-07T09:24:25.5738475Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:24:25.5739916Z import pynvml # type: ignore[import] 2025-09-07T09:24:28.3416158Z 2025-09-07T09:24:29.8109527Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:24:29.8109905Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:24:29.8110240Z cuda train pytorch_stargan 2025-09-07T09:24:46.4106200Z pass 2025-09-07T09:24:49.4193960Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:24:49.4195393Z import pynvml # type: ignore[import] 2025-09-07T09:24:52.1715246Z 2025-09-07T09:24:53.3697840Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:24:53.3698209Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:24:53.3698542Z cuda train pytorch_unet 2025-09-07T09:25:18.5760971Z W0907 09:25:18.575000 11309 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:25:28.4055757Z pass_due_to_skip 2025-09-07T09:25:32.2757985Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:25:32.2759447Z import pynvml # type: ignore[import] 2025-09-07T09:25:35.1042870Z 2025-09-07T09:25:37.9294876Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:25:37.9295502Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:25:37.9296058Z cuda train resnet152 2025-09-07T09:26:42.7556129Z W0907 09:26:42.754000 11435 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:28:12.9985021Z pass 2025-09-07T09:28:19.9825804Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:28:19.9827668Z import pynvml # type: ignore[import] 2025-09-07T09:28:22.6727858Z 2025-09-07T09:28:24.1841803Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:28:24.1842190Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:28:24.1842519Z cuda train resnet18 2025-09-07T09:28:40.0029913Z pass 2025-09-07T09:28:43.5990915Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:28:43.5992329Z import pynvml # type: ignore[import] 2025-09-07T09:28:46.4547153Z 2025-09-07T09:28:49.1224723Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:28:49.1225198Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:28:49.1225509Z cuda train resnet50 2025-09-07T09:29:18.8106994Z W0907 09:29:18.809000 11711 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:29:41.5313866Z pass 2025-09-07T09:29:46.4822512Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:29:46.4823982Z import pynvml # type: ignore[import] 2025-09-07T09:29:49.4182948Z 2025-09-07T09:29:51.8146299Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:51.8146694Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:29:51.8147017Z cuda train resnet50_quantized_qat 2025-09-07T09:29:51.8147821Z Traceback (most recent call last): 2025-09-07T09:29:51.8148459Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:29:51.8149093Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:29:51.8149796Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:29:51.8150440Z pred = mod(*cloned_inputs) 2025-09-07T09:29:51.8151062Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:29:51.8151736Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:29:51.8152379Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:29:51.8152956Z raise e 2025-09-07T09:29:51.8153464Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:29:51.8154200Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:29:51.8155011Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:29:51.8155708Z return self._call_impl(*args, **kwargs) 2025-09-07T09:29:51.8156335Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:29:51.8156983Z return forward_call(*args, **kwargs) 2025-09-07T09:29:51.8157336Z File ".3", line 167, in forward 2025-09-07T09:29:51.8157825Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:29:51.8158627Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:29:51.8159319Z return self._call_impl(*args, **kwargs) 2025-09-07T09:29:51.8159951Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:29:51.8160582Z return forward_call(*args, **kwargs) 2025-09-07T09:29:51.8161250Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:29:51.8162300Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:29:51.8162727Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:29:51.8163025Z 2025-09-07T09:29:51.8163249Z The above exception was the direct cause of the following exception: 2025-09-07T09:29:51.8163584Z 2025-09-07T09:29:51.8163705Z Traceback (most recent call last): 2025-09-07T09:29:51.8164202Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:29:51.8164693Z ) = runner.load_model( 2025-09-07T09:29:51.8165210Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:29:51.8165802Z self.validate_model(model, example_inputs) 2025-09-07T09:29:51.8166384Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:29:51.8166968Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:29:51.8167334Z RuntimeError: Eager run failed 2025-09-07T09:29:51.8167542Z 2025-09-07T09:29:51.8167630Z eager_fail_to_run 2025-09-07T09:29:53.6103386Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:29:53.6106010Z import pynvml # type: ignore[import] 2025-09-07T09:29:56.3672409Z 2025-09-07T09:29:59.3145270Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:59.3145649Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:29:59.3145964Z cuda train resnext50_32x4d 2025-09-07T09:30:26.1441004Z W0907 09:30:26.143000 11879 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:30:49.5351912Z pass 2025-09-07T09:30:53.9820437Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:30:53.9823040Z import pynvml # type: ignore[import] 2025-09-07T09:30:56.6357408Z 2025-09-07T09:31:04.5486497Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:04.5487116Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:31:04.5487686Z cuda train sam 2025-09-07T09:31:04.5497828Z Traceback (most recent call last): 2025-09-07T09:31:04.5498940Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:31:04.5500046Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:31:04.5501202Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:31:04.5502381Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:31:04.5503407Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:31:04.5504384Z torch.autograd.backward( 2025-09-07T09:31:04.5505491Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:31:04.5506665Z _engine_run_backward( 2025-09-07T09:31:04.5518080Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:31:04.5519711Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:31:04.5520966Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:31:04.5521713Z 2025-09-07T09:31:04.5522127Z The above exception was the direct cause of the following exception: 2025-09-07T09:31:04.5522790Z 2025-09-07T09:31:04.5522991Z Traceback (most recent call last): 2025-09-07T09:31:04.5524379Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:31:04.5525354Z ) = runner.load_model( 2025-09-07T09:31:04.5526313Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:31:04.5527449Z self.validate_model(model, example_inputs) 2025-09-07T09:31:04.5528473Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:31:04.5529565Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:31:04.5530237Z RuntimeError: Eager run failed 2025-09-07T09:31:04.5530592Z 2025-09-07T09:31:04.5530754Z eager_fail_to_run 2025-09-07T09:31:06.2399567Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:06.2402203Z import pynvml # type: ignore[import] 2025-09-07T09:31:08.9135240Z 2025-09-07T09:31:10.6178697Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:10.6179085Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:31:10.6179406Z cuda train shufflenet_v2_x1_0 2025-09-07T09:31:47.4995259Z pass 2025-09-07T09:31:50.9125861Z accuracy pass_rate=72.73% 2025-09-07T09:31:50.9133425Z calls_captured gmean=0.00x mean=561.818x 2025-09-07T09:31:50.9137927Z unique_graphs gmean=0.00x mean=2.091x 2025-09-07T09:31:50.9142270Z graph_breaks gmean=0.00x mean=5.364x 2025-09-07T09:31:50.9146776Z unique_graph_breaks gmean=0.00x mean=4.091x 2025-09-07T09:31:50.9151150Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:31:50.9155490Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:31:50.9159722Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:31:50.9161061Z compilation_latency mean=34.495 seconds 2025-09-07T09:31:51.8235541Z + [[ 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* ]] 2025-09-07T09:31:51.8238344Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:31:52.4339474Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:52.4340958Z import pynvml # type: ignore[import] 2025-09-07T09:31:56.4107736Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:56.4111406Z import pynvml # type: ignore[import] 2025-09-07T09:31:59.0770403Z 2025-09-07T09:32:00.0350197Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:00.0350823Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:00.0351483Z cuda train phlippe_resnet 2025-09-07T09:32:12.6771130Z pass 2025-09-07T09:32:15.6787128Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:32:15.6788559Z import pynvml # type: ignore[import] 2025-09-07T09:32:18.4965136Z 2025-09-07T09:32:20.0579137Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:20.0580058Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:32:20.0580408Z cuda train pytorch_CycleGAN_and_pix2pix 2025-09-07T09:32:26.7556552Z W0907 09:32:26.754000 12455 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:32:28.1045713Z pass 2025-09-07T09:32:31.0137692Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:32:31.0139118Z import pynvml # type: ignore[import] 2025-09-07T09:32:33.6940945Z 2025-09-07T09:32:35.1876565Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:35.1877154Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:32:35.1877729Z cuda train pytorch_stargan 2025-09-07T09:32:48.0512457Z pass 2025-09-07T09:32:51.0627738Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:32:51.0630442Z import pynvml # type: ignore[import] 2025-09-07T09:32:53.8589030Z 2025-09-07T09:32:55.0259120Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:55.0259739Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:32:55.0260292Z cuda train pytorch_unet 2025-09-07T09:33:07.1055468Z W0907 09:33:07.104000 12723 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:33:09.1351106Z pass_due_to_skip 2025-09-07T09:33:12.0811636Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:33:12.0813310Z import pynvml # type: ignore[import] 2025-09-07T09:33:15.2586013Z 2025-09-07T09:33:18.2425018Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:33:18.2425423Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:33:18.2427045Z cuda train resnet152 2025-09-07T09:33:36.5292480Z W0907 09:33:36.528000 12872 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:33:50.7209983Z pass 2025-09-07T09:33:54.3669046Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:33:54.3670528Z import pynvml # type: ignore[import] 2025-09-07T09:33:57.1051622Z 2025-09-07T09:33:58.6317440Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:33:58.6317838Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:33:58.6318197Z cuda train resnet18 2025-09-07T09:34:09.1568384Z pass 2025-09-07T09:34:12.0978186Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:34:12.0979722Z import pynvml # type: ignore[import] 2025-09-07T09:34:14.9657479Z 2025-09-07T09:34:17.3012735Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:34:17.3013345Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:34:17.3013710Z cuda train resnet50 2025-09-07T09:34:29.4993048Z W0907 09:34:29.498000 13196 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:34:33.6920715Z pass 2025-09-07T09:34:36.8105470Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:34:36.8106918Z import pynvml # type: ignore[import] 2025-09-07T09:34:39.6280795Z 2025-09-07T09:34:41.9964151Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:34:41.9964812Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:34:41.9965420Z cuda train resnet50_quantized_qat 2025-09-07T09:34:41.9966059Z Traceback (most recent call last): 2025-09-07T09:34:41.9967095Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:34:41.9968205Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:34:41.9969460Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:34:41.9970639Z pred = mod(*cloned_inputs) 2025-09-07T09:34:41.9972230Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:34:41.9973830Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:34:41.9974886Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:34:41.9975897Z raise e 2025-09-07T09:34:41.9976877Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:34:41.9978309Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:34:41.9979893Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:34:41.9981274Z return self._call_impl(*args, **kwargs) 2025-09-07T09:34:41.9982511Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:34:41.9983781Z return forward_call(*args, **kwargs) 2025-09-07T09:34:41.9984446Z File ".3", line 167, in forward 2025-09-07T09:34:41.9985505Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:34:41.9987027Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:34:41.9988390Z return self._call_impl(*args, **kwargs) 2025-09-07T09:34:41.9989617Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:34:41.9990879Z return forward_call(*args, **kwargs) 2025-09-07T09:34:41.9992210Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:34:41.9993631Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:34:41.9994455Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:34:41.9995010Z 2025-09-07T09:34:41.9995435Z The above exception was the direct cause of the following exception: 2025-09-07T09:34:41.9996105Z 2025-09-07T09:34:41.9996307Z Traceback (most recent call last): 2025-09-07T09:34:41.9997282Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:34:41.9998288Z ) = runner.load_model( 2025-09-07T09:34:41.9999221Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:34:42.0000378Z self.validate_model(model, example_inputs) 2025-09-07T09:34:42.0001517Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:34:42.0002699Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:34:42.0003391Z RuntimeError: Eager run failed 2025-09-07T09:34:42.0004077Z 2025-09-07T09:34:42.0004237Z eager_fail_to_run 2025-09-07T09:34:43.6749561Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:34:43.6752084Z import pynvml # type: ignore[import] 2025-09-07T09:34:46.4460596Z 2025-09-07T09:34:49.0273826Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:34:49.0274220Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:34:49.0274986Z cuda train resnext50_32x4d 2025-09-07T09:35:01.1875405Z W0907 09:35:01.186000 13386 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:35:05.4670350Z pass 2025-09-07T09:35:08.5338605Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:08.5341310Z import pynvml # type: ignore[import] 2025-09-07T09:35:11.1950016Z 2025-09-07T09:35:19.1895008Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:19.1895370Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:35:19.1895688Z cuda train sam 2025-09-07T09:35:19.1906063Z Traceback (most recent call last): 2025-09-07T09:35:19.1906657Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:35:19.1907244Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:35:19.1907913Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:35:19.1908585Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:35:19.1909203Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:35:19.1909773Z torch.autograd.backward( 2025-09-07T09:35:19.1910357Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:35:19.1910970Z _engine_run_backward( 2025-09-07T09:35:19.1911588Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:35:19.1912493Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:35:19.1913222Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:35:19.1913629Z 2025-09-07T09:35:19.1913846Z The above exception was the direct cause of the following exception: 2025-09-07T09:35:19.1914188Z 2025-09-07T09:35:19.1914298Z Traceback (most recent call last): 2025-09-07T09:35:19.1914804Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:35:19.1915317Z ) = runner.load_model( 2025-09-07T09:35:19.1915821Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:35:19.1916420Z self.validate_model(model, example_inputs) 2025-09-07T09:35:19.1917008Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:35:19.1917610Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:35:19.1917973Z RuntimeError: Eager run failed 2025-09-07T09:35:19.1918160Z 2025-09-07T09:35:19.1918252Z eager_fail_to_run 2025-09-07T09:35:20.9159564Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:20.9161438Z import pynvml # type: ignore[import] 2025-09-07T09:35:23.7915488Z 2025-09-07T09:35:25.4352409Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:25.4352793Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:35:25.4353343Z cuda train shufflenet_v2_x1_0 2025-09-07T09:35:40.0256660Z pass 2025-09-07T09:35:42.3853765Z accuracy pass_rate=72.73% 2025-09-07T09:35:42.3864114Z calls_captured gmean=0.00x mean=561.818x 2025-09-07T09:35:42.3870953Z unique_graphs gmean=0.00x mean=2.091x 2025-09-07T09:35:42.3878034Z graph_breaks gmean=0.00x mean=5.364x 2025-09-07T09:35:42.3884510Z unique_graph_breaks gmean=0.00x mean=4.091x 2025-09-07T09:35:42.3891073Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:35:42.3898353Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:35:42.3905101Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:35:42.3907413Z compilation_latency mean=10.432 seconds 2025-09-07T09:35:43.4359759Z + [[ 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* ]] 2025-09-07T09:35:43.4361269Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T09:35:43.4363268Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:35:44.0424254Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:44.0425713Z import pynvml # type: ignore[import] 2025-09-07T09:35:47.9357949Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:47.9359429Z import pynvml # type: ignore[import] 2025-09-07T09:35:50.5896924Z 2025-09-07T09:35:51.4986518Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:51.4986895Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:51.4987232Z cuda train phlippe_resnet 2025-09-07T09:36:19.1808689Z pass 2025-09-07T09:36:22.4150596Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:36:22.4152038Z import pynvml # type: ignore[import] 2025-09-07T09:36:25.2046240Z 2025-09-07T09:36:26.6895387Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:36:26.6895773Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:36:26.6896114Z cuda train pytorch_CycleGAN_and_pix2pix 2025-09-07T09:37:01.2610792Z W0907 09:37:01.260000 14696 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:37:12.2790255Z pass 2025-09-07T09:37:16.1542975Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:37:16.1544427Z import pynvml # type: ignore[import] 2025-09-07T09:37:18.9285119Z 2025-09-07T09:37:20.4172775Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:37:20.4173401Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:37:20.4173741Z cuda train pytorch_stargan 2025-09-07T09:37:47.5515233Z pass 2025-09-07T09:37:50.9274409Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:37:50.9275847Z import pynvml # type: ignore[import] 2025-09-07T09:37:53.6928235Z 2025-09-07T09:37:54.8769860Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:37:54.8770224Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:37:54.8770566Z cuda train pytorch_unet 2025-09-07T09:38:40.0315021Z W0907 09:38:40.030000 15590 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:38:55.3099857Z pass_due_to_skip 2025-09-07T09:38:59.3986258Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:38:59.3987722Z import pynvml # type: ignore[import] 2025-09-07T09:39:02.2257148Z 2025-09-07T09:39:05.0004505Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:05.0005169Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:39:05.0005706Z cuda train resnet152 2025-09-07T09:41:24.8866856Z W0907 09:41:24.885000 16006 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:43:51.4056603Z pass 2025-09-07T09:44:00.3982634Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:44:00.3984107Z import pynvml # type: ignore[import] 2025-09-07T09:44:03.1071332Z 2025-09-07T09:44:04.6577467Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:44:04.6578348Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:44:04.6579157Z cuda train resnet18 2025-09-07T09:44:32.3174319Z pass 2025-09-07T09:44:35.7716349Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:44:35.7717780Z import pynvml # type: ignore[import] 2025-09-07T09:44:38.5633605Z 2025-09-07T09:44:40.7637502Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:44:40.7637878Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:44:40.7638205Z cuda train resnet50 2025-09-07T09:45:35.3453988Z W0907 09:45:35.344000 16782 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:46:11.3609528Z pass 2025-09-07T09:46:16.6374435Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:46:16.6375900Z import pynvml # type: ignore[import] 2025-09-07T09:46:19.5611204Z 2025-09-07T09:46:22.1453148Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:46:22.1453541Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:46:22.1453879Z cuda train resnet50_quantized_qat 2025-09-07T09:46:22.1454256Z Traceback (most recent call last): 2025-09-07T09:46:22.1454821Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:46:22.1455840Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:46:22.1456503Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:46:22.1457159Z pred = mod(*cloned_inputs) 2025-09-07T09:46:22.1457775Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:46:22.1458435Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:46:22.1459077Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:46:22.1459661Z raise e 2025-09-07T09:46:22.1460162Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:46:22.1460888Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:46:22.1461680Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:46:22.1462378Z return self._call_impl(*args, **kwargs) 2025-09-07T09:46:22.1463013Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:46:22.1463870Z return forward_call(*args, **kwargs) 2025-09-07T09:46:22.1464217Z File ".3", line 167, in forward 2025-09-07T09:46:22.1464692Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:46:22.1465609Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:46:22.1466300Z return self._call_impl(*args, **kwargs) 2025-09-07T09:46:22.1466936Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:46:22.1467564Z return forward_call(*args, **kwargs) 2025-09-07T09:46:22.1468242Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:46:22.1468978Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:46:22.1469401Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:46:22.1469685Z 2025-09-07T09:46:22.1469931Z The above exception was the direct cause of the following exception: 2025-09-07T09:46:22.1470265Z 2025-09-07T09:46:22.1470375Z Traceback (most recent call last): 2025-09-07T09:46:22.1470874Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:46:22.1471387Z ) = runner.load_model( 2025-09-07T09:46:22.1471899Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:46:22.1472496Z self.validate_model(model, example_inputs) 2025-09-07T09:46:22.1473064Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:46:22.1473667Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:46:22.1474028Z RuntimeError: Eager run failed 2025-09-07T09:46:22.1474218Z 2025-09-07T09:46:22.1474322Z eager_fail_to_run 2025-09-07T09:46:23.9700979Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:46:23.9702486Z import pynvml # type: ignore[import] 2025-09-07T09:46:26.9474238Z 2025-09-07T09:46:29.5436891Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:46:29.5437270Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:46:29.5437593Z cuda train resnext50_32x4d 2025-09-07T09:47:20.0747362Z W0907 09:47:20.073000 17140 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:47:56.6387845Z pass 2025-09-07T09:48:01.7776111Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:48:01.7777566Z import pynvml # type: ignore[import] 2025-09-07T09:48:04.7448475Z 2025-09-07T09:48:12.6859465Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:48:12.6859870Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:48:12.6860194Z cuda train sam 2025-09-07T09:48:12.6872192Z Traceback (most recent call last): 2025-09-07T09:48:12.6872830Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:48:12.6873443Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:48:12.6874106Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:48:12.6874801Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:48:12.6875391Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:48:12.6875966Z torch.autograd.backward( 2025-09-07T09:48:12.6876944Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:48:12.6877650Z _engine_run_backward( 2025-09-07T09:48:12.6878268Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:48:12.6879182Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:48:12.6879931Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:48:12.6880326Z 2025-09-07T09:48:12.6880560Z The above exception was the direct cause of the following exception: 2025-09-07T09:48:12.6880892Z 2025-09-07T09:48:12.6881004Z Traceback (most recent call last): 2025-09-07T09:48:12.6881514Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:48:12.6882025Z ) = runner.load_model( 2025-09-07T09:48:12.6882538Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:48:12.6883127Z self.validate_model(model, example_inputs) 2025-09-07T09:48:12.6883714Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:48:12.6884317Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:48:12.6884677Z RuntimeError: Eager run failed 2025-09-07T09:48:12.6884865Z 2025-09-07T09:48:12.6884968Z eager_fail_to_run 2025-09-07T09:48:14.5046659Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:48:14.5049631Z import pynvml # type: ignore[import] 2025-09-07T09:48:17.1997409Z 2025-09-07T09:48:18.8664645Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:48:18.8665096Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:48:18.8665454Z cuda train shufflenet_v2_x1_0 2025-09-07T09:49:24.2326482Z pass 2025-09-07T09:49:28.0871915Z accuracy pass_rate=72.73% 2025-09-07T09:49:28.0882153Z calls_captured gmean=0.00x mean=561.818x 2025-09-07T09:49:28.0888373Z unique_graphs gmean=0.00x mean=2.091x 2025-09-07T09:49:28.0894866Z graph_breaks gmean=0.00x mean=5.364x 2025-09-07T09:49:28.0902311Z unique_graph_breaks gmean=0.00x mean=4.091x 2025-09-07T09:49:28.0908689Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:49:28.0914785Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:49:28.0920965Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:49:28.0922869Z compilation_latency mean=63.674 seconds 2025-09-07T09:49:29.0681863Z + [[ 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* ]] 2025-09-07T09:49:29.0683405Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:49:29.0684874Z + [[ 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* ]] 2025-09-07T09:49:29.0686346Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:49:29.0687759Z + [[ 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* ]] 2025-09-07T09:49:29.0689151Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:49:29.0690554Z + [[ 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* ]] 2025-09-07T09:49:29.0691950Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T09:49:29.0694144Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:49:29.6743006Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:49:29.6744466Z import pynvml # type: ignore[import] 2025-09-07T09:49:33.6278351Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:49:33.6279809Z import pynvml # type: ignore[import] 2025-09-07T09:49:36.4429382Z 2025-09-07T09:49:37.3644221Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:49:37.3644871Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:49:37.3645475Z cuda train phlippe_resnet 2025-09-07T09:49:46.4620601Z Autotune Choices Stats: 2025-09-07T09:49:46.4621975Z {"num_choices": 6, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_0", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:49:46.4632505Z AUTOTUNE convolution(4x3x32x32, 16x3x3x3) 2025-09-07T09:49:46.4633180Z strides: [3072, 1024, 32, 1], [27, 9, 3, 1] 2025-09-07T09:49:46.4638061Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:46.4639064Z triton_convolution2d_0 0.0092 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:46.4640571Z triton_convolution2d_3 0.0092 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:46.4642061Z triton_convolution2d_1 0.0102 ms 90.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:46.4643540Z triton_convolution2d_4 0.0102 ms 90.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:46.4644807Z convolution 0.0113 ms 81.8% 2025-09-07T09:49:46.4645695Z triton_convolution2d_2 0.0154 ms 60.0% 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 2025-09-07T09:49:46.4646855Z SingleProcess AUTOTUNE benchmarking takes 0.0886 seconds and 0.0003 seconds precompiling for 6 choices 2025-09-07T09:49:46.8924423Z Autotune Choices Stats: 2025-09-07T09:49:46.8925794Z {"num_choices": 6, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:49:46.8929904Z AUTOTUNE convolution(4x16x32x32, 16x16x3x3) 2025-09-07T09:49:46.8930273Z strides: [16384, 1024, 32, 1], [144, 9, 3, 1] 2025-09-07T09:49:46.8930622Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:46.8931959Z triton_convolution2d_5 0.0092 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:46.8933692Z triton_convolution2d_8 0.0102 ms 90.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:46.8935183Z triton_convolution2d_6 0.0133 ms 69.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:46.8936679Z triton_convolution2d_9 0.0133 ms 69.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:46.8937588Z convolution 0.0215 ms 42.9% 2025-09-07T09:49:46.8938465Z triton_convolution2d_7 0.0266 ms 34.6% 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 2025-09-07T09:49:46.8939629Z SingleProcess AUTOTUNE benchmarking takes 0.0863 seconds and 0.0002 seconds precompiling for 6 choices 2025-09-07T09:49:47.4151905Z Autotune Choices Stats: 2025-09-07T09:49:47.4153272Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_35", "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=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:49:47.4156911Z AUTOTUNE convolution(4x16x32x32, 32x16x3x3) 2025-09-07T09:49:47.4157254Z strides: [16384, 1024, 32, 1], [144, 9, 3, 1] 2025-09-07T09:49:47.4157597Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:47.4158515Z triton_convolution2d_35 0.0102 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=4 2025-09-07T09:49:47.4160008Z triton_convolution2d_38 0.0102 ms 100.0% 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 2025-09-07T09:49:47.4161518Z triton_convolution2d_39 0.0102 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 2025-09-07T09:49:47.4163342Z triton_convolution2d_40 0.0123 ms 83.3% 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 2025-09-07T09:49:47.4164845Z triton_convolution2d_36 0.0133 ms 76.9% 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=4 2025-09-07T09:49:47.4165740Z convolution 0.0215 ms 47.6% 2025-09-07T09:49:47.4166627Z triton_convolution2d_37 0.0676 ms 15.2% 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 2025-09-07T09:49:47.4167803Z SingleProcess AUTOTUNE benchmarking takes 0.1016 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:49:47.7925212Z Autotune Choices Stats: 2025-09-07T09:49:47.7926888Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_48", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, 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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:49:47.7930636Z AUTOTUNE convolution(4x16x32x32, 32x16x1x1) 2025-09-07T09:49:47.7930997Z strides: [16384, 1024, 32, 1], [16, 1, 1, 1] 2025-09-07T09:49:47.7931335Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:47.7932236Z triton_convolution2d_48 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, 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 2025-09-07T09:49:47.7933954Z triton_convolution2d_51 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, 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 2025-09-07T09:49:47.7935458Z triton_convolution2d_52 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, 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 2025-09-07T09:49:47.7936942Z triton_convolution2d_49 0.0082 ms 87.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, 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 2025-09-07T09:49:47.7938424Z triton_convolution2d_53 0.0082 ms 87.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, 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 2025-09-07T09:49:47.7939914Z triton_convolution2d_50 0.0154 ms 46.7% 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 2025-09-07T09:49:47.7940830Z convolution 0.0184 ms 38.9% 2025-09-07T09:49:47.7941376Z SingleProcess AUTOTUNE benchmarking takes 0.0946 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:49:48.2452327Z Autotune Choices Stats: 2025-09-07T09:49:48.2453935Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_59", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T09:49:48.2459346Z AUTOTUNE convolution(4x32x16x16, 32x32x3x3) 2025-09-07T09:49:48.2459739Z strides: [8192, 256, 16, 1], [288, 9, 3, 1] 2025-09-07T09:49:48.2460075Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:48.2460990Z triton_convolution2d_59 0.0113 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:48.2462845Z triton_convolution2d_58 0.0123 ms 91.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:48.2464321Z triton_convolution2d_54 0.0143 ms 78.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:48.2465859Z triton_convolution2d_57 0.0143 ms 78.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:48.2467348Z triton_convolution2d_55 0.0184 ms 61.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:48.2468839Z triton_convolution2d_60 0.0184 ms 61.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:48.2469926Z convolution 0.0225 ms 50.0% 2025-09-07T09:49:48.2470822Z triton_convolution2d_56 0.0471 ms 23.9% 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 2025-09-07T09:49:48.2472003Z SingleProcess AUTOTUNE benchmarking takes 0.1164 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:48.7544406Z Autotune Choices Stats: 2025-09-07T09:49:48.7545856Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_86", "best_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", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:49:48.7550776Z AUTOTUNE convolution(4x32x16x16, 64x32x3x3) 2025-09-07T09:49:48.7551176Z strides: [8192, 256, 16, 1], [288, 9, 3, 1] 2025-09-07T09:49:48.7551536Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:48.7552438Z triton_convolution2d_86 0.0123 ms 100.0% 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 2025-09-07T09:49:48.7553926Z triton_convolution2d_87 0.0123 ms 100.0% 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=8 2025-09-07T09:49:48.7555403Z triton_convolution2d_82 0.0154 ms 80.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:48.7556895Z triton_convolution2d_85 0.0154 ms 80.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:48.7558370Z triton_convolution2d_88 0.0195 ms 63.2% 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 2025-09-07T09:49:48.7559839Z triton_convolution2d_83 0.0236 ms 52.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:48.7560733Z convolution 0.0276 ms 44.4% 2025-09-07T09:49:48.7561609Z triton_convolution2d_84 0.0563 ms 21.8% 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 2025-09-07T09:49:48.7563151Z SingleProcess AUTOTUNE benchmarking takes 0.1176 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:49.1475960Z Autotune Choices Stats: 2025-09-07T09:49:49.1477377Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_100", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:49:49.1482772Z AUTOTUNE convolution(4x32x16x16, 64x32x1x1) 2025-09-07T09:49:49.1483121Z strides: [8192, 256, 16, 1], [32, 1, 1, 1] 2025-09-07T09:49:49.1483455Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:49.1484352Z triton_convolution2d_100 0.0072 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 2025-09-07T09:49:49.1486267Z triton_convolution2d_101 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:49:49.1487757Z triton_convolution2d_96 0.0082 ms 87.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:49:49.1489233Z triton_convolution2d_99 0.0082 ms 87.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:49:49.1490721Z triton_convolution2d_102 0.0092 ms 77.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:49:49.1492221Z triton_convolution2d_97 0.0102 ms 70.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:49:49.1493966Z triton_convolution2d_98 0.0133 ms 53.8% 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 2025-09-07T09:49:49.1494877Z convolution 0.0174 ms 41.2% 2025-09-07T09:49:49.1495421Z SingleProcess AUTOTUNE benchmarking takes 0.1102 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:49.6062613Z Autotune Choices Stats: 2025-09-07T09:49:49.6063987Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_107", "best_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", "best_time": 0.018432000651955605, "best_triton_pos": 0} 2025-09-07T09:49:49.6070297Z AUTOTUNE convolution(4x64x8x8, 64x64x3x3) 2025-09-07T09:49:49.6070714Z strides: [4096, 64, 8, 1], [576, 9, 3, 1] 2025-09-07T09:49:49.6071039Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:49.6071964Z triton_convolution2d_107 0.0184 ms 100.0% 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 2025-09-07T09:49:49.6073467Z triton_convolution2d_108 0.0184 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:49.6074957Z triton_convolution2d_103 0.0225 ms 81.8% 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 2025-09-07T09:49:49.6076198Z convolution 0.0236 ms 78.3% 2025-09-07T09:49:49.6077075Z triton_convolution2d_106 0.0236 ms 78.3% 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 2025-09-07T09:49:49.6078570Z triton_convolution2d_105 0.0307 ms 60.0% 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 2025-09-07T09:49:49.6080060Z triton_convolution2d_109 0.0328 ms 56.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:49.6081555Z triton_convolution2d_104 0.0389 ms 47.4% 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 2025-09-07T09:49:49.6082736Z SingleProcess AUTOTUNE benchmarking takes 0.1187 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:50.9286484Z Autotune Choices Stats: 2025-09-07T09:49:50.9295301Z {"num_choices": 12, "num_triton_choices": 10, "best_kernel": "triton_mm_132", "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=2, num_warps=1", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:49:50.9296532Z AUTOTUNE addmm(4x10, 4x64, 64x10) 2025-09-07T09:49:50.9296835Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T09:49:50.9297181Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:49:50.9297995Z triton_mm_132 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T09:49:50.9299190Z triton_mm_133 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T09:49:50.9300382Z triton_mm_134 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T09:49:50.9301564Z triton_mm_136 0.0072 ms 100.0% 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 2025-09-07T09:49:50.9302743Z triton_mm_137 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T09:49:50.9303921Z triton_mm_138 0.0072 ms 100.0% 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 2025-09-07T09:49:50.9305206Z triton_mm_139 0.0072 ms 100.0% 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=4, num_warps=1 2025-09-07T09:49:50.9306398Z triton_mm_140 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T09:49:50.9307138Z bias_addmm 0.0082 ms 87.5% 2025-09-07T09:49:50.9307853Z triton_mm_131 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=1 2025-09-07T09:49:50.9308872Z SingleProcess AUTOTUNE benchmarking takes 0.1689 seconds and 0.0002 seconds precompiling for 12 choices 2025-09-07T09:49:55.2006577Z Autotune Choices Stats: 2025-09-07T09:49:55.2007800Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_mm_150", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T09:49:55.2013516Z AUTOTUNE mm(10x4, 4x64) 2025-09-07T09:49:55.2013782Z strides: [1, 10], [64, 1] 2025-09-07T09:49:55.2014053Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:55.2014830Z triton_mm_150 0.0061 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 2025-09-07T09:49:55.2016037Z triton_mm_152 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:49:55.2017229Z triton_mm_153 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:49:55.2018425Z triton_mm_154 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:49:55.2019394Z mm 0.0072 ms 85.7% 2025-09-07T09:49:55.2020072Z triton_mm_148 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:49:55.2021250Z triton_mm_149 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:49:55.2022432Z triton_mm_151 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:49:55.2023457Z SingleProcess AUTOTUNE benchmarking takes 0.0980 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:49:55.6829076Z Autotune Choices Stats: 2025-09-07T09:49:55.6830262Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_mm_143", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T09:49:55.6836309Z AUTOTUNE mm(4x10, 10x64) 2025-09-07T09:49:55.6836598Z strides: [10, 1], [64, 1] 2025-09-07T09:49:55.6836889Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:55.6837658Z triton_mm_143 0.0061 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 2025-09-07T09:49:55.6838868Z triton_mm_145 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:49:55.6840064Z triton_mm_146 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:49:55.6841264Z triton_mm_147 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:49:55.6842015Z mm 0.0072 ms 85.7% 2025-09-07T09:49:55.6842703Z triton_mm_141 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:49:55.6843888Z triton_mm_142 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:49:55.6845072Z triton_mm_144 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:49:55.6846341Z SingleProcess AUTOTUNE benchmarking takes 0.0953 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:57.8362031Z pass 2025-09-07T09:50:00.9271403Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:50:00.9272836Z import pynvml # type: ignore[import] 2025-09-07T09:50:03.6924964Z 2025-09-07T09:50:05.3356662Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:50:05.3357065Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:50:05.3357415Z cuda train pytorch_CycleGAN_and_pix2pix 2025-09-07T09:50:18.2997587Z Autotune Choices Stats: 2025-09-07T09:50:18.2999770Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.12902399897575378, "best_triton_pos": 1, "best_triton_time": 0.22118400037288666, "best_triton_kernel": "triton_convolution2d_151", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:50:18.3005649Z AUTOTUNE convolution(1x64x262x262, 3x64x7x7) 2025-09-07T09:50:18.3006039Z strides: [4393216, 68644, 262, 1], [3136, 49, 7, 1] 2025-09-07T09:50:18.3006398Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:18.3006713Z convolution 0.1290 ms 100.0% 2025-09-07T09:50:18.3007595Z triton_convolution2d_151 0.2212 ms 58.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:18.3009093Z triton_convolution2d_150 0.2294 ms 56.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.3010593Z triton_convolution2d_149 0.2314 ms 55.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:18.3012075Z triton_convolution2d_146 0.3379 ms 38.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.3013776Z triton_convolution2d_147 0.3492 ms 37.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.3015269Z triton_convolution2d_148 0.4700 ms 27.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:18.3016459Z SingleProcess AUTOTUNE benchmarking takes 0.2447 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T09:50:18.8181620Z Autotune Choices Stats: 2025-09-07T09:50:18.8183289Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.0798719972372055, "best_triton_pos": 1, "best_triton_time": 0.0798719972372055, "best_triton_kernel": "triton_convolution2d_5", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:50:18.8189773Z AUTOTUNE convolution(1x3x262x262, 64x3x7x7) 2025-09-07T09:50:18.8190144Z strides: [205932, 68644, 262, 1], [147, 49, 7, 1] 2025-09-07T09:50:18.8190502Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:18.8191122Z convolution 0.0799 ms 100.0% 2025-09-07T09:50:18.8192011Z triton_convolution2d_5 0.0799 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:18.8193504Z triton_convolution2d_0 0.0850 ms 94.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.8194977Z triton_convolution2d_1 0.0850 ms 94.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.8196453Z triton_convolution2d_3 0.0922 ms 86.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:18.8197924Z triton_convolution2d_4 0.0973 ms 82.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:18.8199551Z triton_convolution2d_2 0.1239 ms 64.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:18.8200729Z SingleProcess AUTOTUNE benchmarking takes 0.1462 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:50:18.9924808Z Autotune Choices Stats: 2025-09-07T09:50:18.9926162Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_7", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.058368001133203506, "best_triton_pos": 0} 2025-09-07T09:50:18.9932957Z AUTOTUNE convolution(1x64x256x256, 128x64x3x3) 2025-09-07T09:50:18.9933332Z strides: [4194304, 65536, 256, 1], [576, 9, 3, 1] 2025-09-07T09:50:18.9933687Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:18.9934610Z triton_convolution2d_7 0.0584 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.9935512Z convolution 0.0594 ms 98.3% 2025-09-07T09:50:18.9936383Z triton_convolution2d_12 0.0666 ms 87.7% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:18.9937862Z triton_convolution2d_6 0.0676 ms 86.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:18.9939351Z triton_convolution2d_9 0.0768 ms 76.0% 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 2025-09-07T09:50:18.9940834Z triton_convolution2d_11 0.0922 ms 63.3% 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 2025-09-07T09:50:18.9942313Z triton_convolution2d_10 0.0942 ms 62.0% 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 2025-09-07T09:50:18.9943785Z triton_convolution2d_8 0.2959 ms 19.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:18.9945313Z SingleProcess AUTOTUNE benchmarking takes 0.1734 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:19.1819243Z Autotune Choices Stats: 2025-09-07T09:50:19.1820933Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.04710400104522705, "best_triton_pos": 1, "best_triton_time": 0.07577600330114365, "best_triton_kernel": "triton_convolution2d_19", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:50:19.1829563Z AUTOTUNE convolution(1x128x128x128, 256x128x3x3) 2025-09-07T09:50:19.1829959Z strides: [2097152, 16384, 128, 1], [1152, 9, 3, 1] 2025-09-07T09:50:19.1830307Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:19.1830631Z convolution 0.0471 ms 100.0% 2025-09-07T09:50:19.1831522Z triton_convolution2d_19 0.0758 ms 62.2% 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 2025-09-07T09:50:19.1833332Z triton_convolution2d_16 0.0850 ms 55.4% 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 2025-09-07T09:50:19.1834834Z triton_convolution2d_14 0.0891 ms 52.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:19.1836315Z triton_convolution2d_17 0.0973 ms 48.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:19.1837795Z triton_convolution2d_18 0.1331 ms 35.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:19.1839336Z triton_convolution2d_13 0.1423 ms 33.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:19.1840830Z triton_convolution2d_15 0.2990 ms 15.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:19.1842009Z SingleProcess AUTOTUNE benchmarking takes 0.1890 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:19.4271260Z Autotune Choices Stats: 2025-09-07T09:50:19.4272947Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.060416001826524734, "best_triton_pos": 1, "best_triton_time": 0.14028799533843994, "best_triton_kernel": "triton_convolution2d_26", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:50:19.4279936Z AUTOTUNE convolution(1x256x66x66, 256x256x3x3) 2025-09-07T09:50:19.4280318Z strides: [1115136, 4356, 66, 1], [2304, 9, 3, 1] 2025-09-07T09:50:19.4280658Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:19.4280979Z convolution 0.0604 ms 100.0% 2025-09-07T09:50:19.4281867Z triton_convolution2d_26 0.1403 ms 43.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:19.4283360Z triton_convolution2d_24 0.1659 ms 36.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:19.4285130Z triton_convolution2d_23 0.1710 ms 35.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:19.4286630Z triton_convolution2d_21 0.1731 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:19.4288114Z triton_convolution2d_25 0.2468 ms 24.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:19.4289651Z triton_convolution2d_22 0.2714 ms 22.3% 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=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:19.4291144Z triton_convolution2d_20 0.2806 ms 21.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:19.4292485Z SingleProcess AUTOTUNE benchmarking takes 0.2443 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:34.6573661Z W0907 09:50:34.656000 20354 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:50:41.5950436Z pass 2025-09-07T09:50:45.3401881Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:50:45.3403331Z import pynvml # type: ignore[import] 2025-09-07T09:50:48.0910459Z 2025-09-07T09:50:49.6560289Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:50:49.6560815Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:50:49.6561318Z cuda train pytorch_stargan 2025-09-07T09:51:02.9562163Z Autotune Choices Stats: 2025-09-07T09:51:02.9563533Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_1", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.2467840015888214, "best_triton_pos": 0} 2025-09-07T09:51:02.9572779Z AUTOTUNE convolution(16x8x128x128, 64x8x7x7) 2025-09-07T09:51:02.9573288Z strides: [131072, 16384, 128, 1], [392, 49, 7, 1] 2025-09-07T09:51:02.9573649Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:02.9574574Z triton_convolution2d_1 0.2468 ms 100.0% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:02.9576108Z triton_convolution2d_5 0.2488 ms 99.2% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:02.9577014Z convolution 0.2755 ms 89.6% 2025-09-07T09:51:02.9577875Z triton_convolution2d_3 0.3174 ms 77.7% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:02.9579355Z triton_convolution2d_0 0.3338 ms 73.9% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:02.9580823Z triton_convolution2d_4 0.3963 ms 62.3% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:02.9582595Z triton_convolution2d_2 0.6994 ms 35.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:02.9583771Z SingleProcess AUTOTUNE benchmarking takes 0.2654 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T09:51:03.6134066Z Autotune Choices Stats: 2025-09-07T09:51:03.6135801Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.187391996383667, "best_triton_pos": 1, "best_triton_time": 0.3768320083618164, "best_triton_kernel": "triton_convolution2d_7", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:03.6145148Z AUTOTUNE convolution(16x64x128x128, 128x64x4x4) 2025-09-07T09:51:03.6145575Z strides: [1048576, 16384, 128, 1], [1024, 16, 4, 1] 2025-09-07T09:51:03.6145939Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:03.6146249Z convolution 0.1874 ms 100.0% 2025-09-07T09:51:03.6147521Z triton_convolution2d_7 0.3768 ms 49.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:03.6149051Z triton_convolution2d_12 0.4065 ms 46.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:03.6150555Z triton_convolution2d_9 0.7025 ms 26.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:03.6152056Z triton_convolution2d_6 0.7291 ms 25.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:03.6153544Z triton_convolution2d_10 0.8530 ms 22.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:03.6155029Z triton_convolution2d_11 0.9984 ms 18.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:03.6156526Z triton_convolution2d_8 1.3322 ms 14.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:03.6157691Z SingleProcess AUTOTUNE benchmarking takes 0.3024 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:04.2038062Z Autotune Choices Stats: 2025-09-07T09:51:04.2039772Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.13619199395179749, "best_triton_pos": 1, "best_triton_time": 0.47206398844718933, "best_triton_kernel": "triton_convolution2d_14", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:04.2049264Z AUTOTUNE convolution(16x128x64x64, 256x128x4x4) 2025-09-07T09:51:04.2049695Z strides: [524288, 4096, 64, 1], [2048, 16, 4, 1] 2025-09-07T09:51:04.2050054Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:04.2050374Z convolution 0.1362 ms 100.0% 2025-09-07T09:51:04.2051276Z triton_convolution2d_14 0.4721 ms 28.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:04.2053346Z triton_convolution2d_19 0.5325 ms 25.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:04.2054846Z triton_convolution2d_16 0.7557 ms 18.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:04.2056331Z triton_convolution2d_17 0.9964 ms 13.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:04.2057806Z triton_convolution2d_18 1.1715 ms 11.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:04.2059475Z triton_convolution2d_13 1.3517 ms 10.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:04.2061042Z triton_convolution2d_15 1.5493 ms 8.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:04.2062212Z SingleProcess AUTOTUNE benchmarking takes 0.3031 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:04.7863120Z Autotune Choices Stats: 2025-09-07T09:51:04.7864911Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.12800000607967377, "best_triton_pos": 1, "best_triton_time": 0.4116480052471161, "best_triton_kernel": "triton_convolution2d_26", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:51:04.7875091Z AUTOTUNE convolution(16x256x32x32, 256x256x3x3) 2025-09-07T09:51:04.7875504Z strides: [262144, 1024, 32, 1], [2304, 9, 3, 1] 2025-09-07T09:51:04.7875852Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:04.7876157Z convolution 0.1280 ms 100.0% 2025-09-07T09:51:04.7877045Z triton_convolution2d_26 0.4116 ms 31.1% 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 2025-09-07T09:51:04.7878549Z triton_convolution2d_21 0.4147 ms 30.9% 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 2025-09-07T09:51:04.7880042Z triton_convolution2d_23 0.5181 ms 24.7% 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 2025-09-07T09:51:04.7881542Z triton_convolution2d_24 0.6124 ms 20.9% 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 2025-09-07T09:51:04.7883028Z triton_convolution2d_20 0.6840 ms 18.7% 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 2025-09-07T09:51:04.7884516Z triton_convolution2d_25 0.8356 ms 15.3% 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 2025-09-07T09:51:04.7886015Z triton_convolution2d_22 1.0854 ms 11.8% 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 2025-09-07T09:51:04.7887580Z SingleProcess AUTOTUNE benchmarking takes 0.2942 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:05.4853347Z Autotune Choices Stats: 2025-09-07T09:51:05.4855048Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.4341759979724884, "best_triton_pos": 1, "best_triton_time": 0.7106559872627258, "best_triton_kernel": "triton_convolution2d_109", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:51:05.4865198Z AUTOTUNE convolution(16x64x128x128, 3x64x7x7) 2025-09-07T09:51:05.4865659Z strides: [1048576, 16384, 128, 1], [3136, 49, 7, 1] 2025-09-07T09:51:05.4866044Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:05.4866352Z convolution 0.4342 ms 100.0% 2025-09-07T09:51:05.4867572Z triton_convolution2d_109 0.7107 ms 61.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:05.4869082Z triton_convolution2d_108 0.7608 ms 57.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:05.4870573Z triton_convolution2d_107 0.7741 ms 56.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:05.4872076Z triton_convolution2d_105 1.0179 ms 42.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:05.4873586Z triton_convolution2d_104 1.1182 ms 38.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:05.4875090Z triton_convolution2d_106 1.3199 ms 32.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:05.4876272Z SingleProcess AUTOTUNE benchmarking takes 0.2712 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:51:11.6642871Z pass 2025-09-07T09:51:15.2773162Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:51:15.2774638Z import pynvml # type: ignore[import] 2025-09-07T09:51:18.1102699Z 2025-09-07T09:51:19.3075147Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:19.3075531Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:51:19.3075895Z cuda train pytorch_unet 2025-09-07T09:51:33.6404889Z Autotune Choices Stats: 2025-09-07T09:51:33.6406693Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.22937600314617157, "best_triton_pos": 0} 2025-09-07T09:51:33.6417549Z AUTOTUNE convolution(2x3x640x959, 64x3x3x3) 2025-09-07T09:51:33.6418031Z strides: [1841280, 613760, 959, 1], [27, 9, 3, 1] 2025-09-07T09:51:33.6418437Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:33.6419388Z triton_convolution2d_5 0.2294 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:33.6421315Z triton_convolution2d_1 0.2990 ms 76.7% 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 2025-09-07T09:51:33.6422834Z triton_convolution2d_0 0.3133 ms 73.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:33.6424347Z triton_convolution2d_3 0.3256 ms 70.4% 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 2025-09-07T09:51:33.6425966Z triton_convolution2d_4 0.3441 ms 66.7% 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=8 2025-09-07T09:51:33.6426913Z convolution 0.3860 ms 59.4% 2025-09-07T09:51:33.6428028Z triton_convolution2d_2 0.5898 ms 38.9% 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 2025-09-07T09:51:33.6429244Z SingleProcess AUTOTUNE benchmarking takes 0.2680 seconds and 0.0004 seconds precompiling for 7 choices 2025-09-07T09:51:34.4793518Z Autotune Choices Stats: 2025-09-07T09:51:34.4795663Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 1.0158079862594604, "best_triton_pos": 1, "best_triton_time": 1.21343994140625, "best_triton_kernel": "triton_convolution2d_7", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:34.4805244Z AUTOTUNE convolution(2x64x640x959, 64x64x3x3) 2025-09-07T09:51:34.4805893Z strides: [39280640, 613760, 959, 1], [576, 9, 3, 1] 2025-09-07T09:51:34.4895076Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:34.4895614Z convolution 1.0158 ms 100.0% 2025-09-07T09:51:34.4896507Z triton_convolution2d_7 1.2134 ms 83.7% 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 2025-09-07T09:51:34.4898129Z triton_convolution2d_12 1.2626 ms 80.5% 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 2025-09-07T09:51:34.4899615Z triton_convolution2d_9 1.3588 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 2025-09-07T09:51:34.4901111Z triton_convolution2d_10 1.7490 ms 58.1% 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 2025-09-07T09:51:34.4902584Z triton_convolution2d_11 1.8125 ms 56.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:34.4904051Z triton_convolution2d_6 1.9681 ms 51.6% 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 2025-09-07T09:51:34.4905613Z triton_convolution2d_8 3.4058 ms 29.8% 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 2025-09-07T09:51:34.4907218Z SingleProcess AUTOTUNE benchmarking takes 0.3479 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:51:35.7554685Z Autotune Choices Stats: 2025-09-07T09:51:35.7556418Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 1.649664044380188, "best_triton_pos": 1, "best_triton_time": 2.5968639850616455, "best_triton_kernel": "triton_convolution2d_112", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:35.7566463Z AUTOTUNE convolution(2x128x640x959, 64x128x3x3) 2025-09-07T09:51:35.7566934Z strides: [78561280, 613760, 959, 1], [1152, 9, 3, 1] 2025-09-07T09:51:35.7567299Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:35.7567621Z convolution 1.6497 ms 100.0% 2025-09-07T09:51:35.7568530Z triton_convolution2d_112 2.5969 ms 63.5% 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 2025-09-07T09:51:35.7570435Z triton_convolution2d_114 3.1355 ms 52.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:35.7571941Z triton_convolution2d_117 3.2604 ms 50.6% 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 2025-09-07T09:51:35.7573661Z triton_convolution2d_115 3.8973 ms 42.3% 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 2025-09-07T09:51:35.7575139Z triton_convolution2d_116 4.0991 ms 40.2% 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=8 2025-09-07T09:51:35.7576636Z triton_convolution2d_111 4.2803 ms 38.5% 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 2025-09-07T09:51:35.7578133Z triton_convolution2d_113 8.4050 ms 19.6% 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 2025-09-07T09:51:35.7579320Z SingleProcess AUTOTUNE benchmarking takes 0.4402 seconds and 0.6415 seconds precompiling for 8 choices 2025-09-07T09:51:36.2680616Z Autotune Choices Stats: 2025-09-07T09:51:36.2682304Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.4352000057697296, "best_triton_pos": 1, "best_triton_time": 0.6512640118598938, "best_triton_kernel": "triton_convolution2d_14", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:36.2693055Z AUTOTUNE convolution(2x64x320x479, 128x64x3x3) 2025-09-07T09:51:36.2693438Z strides: [9809920, 153280, 479, 1], [576, 9, 3, 1] 2025-09-07T09:51:36.2693804Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:36.2694109Z convolution 0.4352 ms 100.0% 2025-09-07T09:51:36.2694991Z triton_convolution2d_14 0.6513 ms 66.8% 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 2025-09-07T09:51:36.2696480Z triton_convolution2d_19 0.6615 ms 65.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:36.2698236Z triton_convolution2d_16 0.7690 ms 56.6% 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 2025-09-07T09:51:36.2699722Z triton_convolution2d_17 0.8694 ms 50.1% 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 2025-09-07T09:51:36.2701203Z triton_convolution2d_13 0.9667 ms 45.0% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:36.2702687Z triton_convolution2d_18 1.1715 ms 37.2% 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 2025-09-07T09:51:36.2704183Z triton_convolution2d_15 1.7162 ms 25.4% 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 2025-09-07T09:51:36.2705609Z SingleProcess AUTOTUNE benchmarking takes 0.3117 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:37.0086483Z Autotune Choices Stats: 2025-09-07T09:51:37.0088155Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.6584320068359375, "best_triton_pos": 1, "best_triton_time": 1.3281279802322388, "best_triton_kernel": "triton_convolution2d_21", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:37.0099376Z AUTOTUNE convolution(2x128x320x479, 128x128x3x3) 2025-09-07T09:51:37.0099847Z strides: [19619840, 153280, 479, 1], [1152, 9, 3, 1] 2025-09-07T09:51:37.0100215Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:37.0100522Z convolution 0.6584 ms 100.0% 2025-09-07T09:51:37.0101431Z triton_convolution2d_21 1.3281 ms 49.6% 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 2025-09-07T09:51:37.0102935Z triton_convolution2d_26 1.6374 ms 40.2% 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 2025-09-07T09:51:37.0104426Z triton_convolution2d_20 1.8350 ms 35.9% 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 2025-09-07T09:51:37.0106010Z triton_convolution2d_23 2.0347 ms 32.4% 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 2025-09-07T09:51:37.0107515Z triton_convolution2d_24 2.0767 ms 31.7% 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 2025-09-07T09:51:37.0109002Z triton_convolution2d_25 2.6173 ms 25.2% 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 2025-09-07T09:51:37.0110478Z triton_convolution2d_22 4.2957 ms 15.3% 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 2025-09-07T09:51:37.0111655Z SingleProcess AUTOTUNE benchmarking takes 0.3539 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:37.6239989Z Autotune Choices Stats: 2025-09-07T09:51:37.6241658Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 1.1325440406799316, "best_triton_pos": 1, "best_triton_time": 3.0074880123138428, "best_triton_kernel": "triton_convolution2d_98", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:37.6252736Z AUTOTUNE convolution(2x256x320x479, 128x256x3x3) 2025-09-07T09:51:37.6253224Z strides: [39239680, 153280, 479, 1], [2304, 9, 3, 1] 2025-09-07T09:51:37.6253585Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:37.6253904Z convolution 1.1325 ms 100.0% 2025-09-07T09:51:37.6254797Z triton_convolution2d_98 3.0075 ms 37.7% 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 2025-09-07T09:51:37.6256616Z triton_convolution2d_103 3.2348 ms 35.0% 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 2025-09-07T09:51:37.6258111Z triton_convolution2d_97 3.6362 ms 31.1% 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 2025-09-07T09:51:37.6259590Z triton_convolution2d_101 4.1923 ms 27.0% 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 2025-09-07T09:51:37.6261083Z triton_convolution2d_100 4.2066 ms 26.9% 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 2025-09-07T09:51:37.6262586Z triton_convolution2d_102 5.0432 ms 22.5% 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 2025-09-07T09:51:37.6264081Z triton_convolution2d_99 11.1084 ms 10.2% 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 2025-09-07T09:51:37.6265333Z SingleProcess AUTOTUNE benchmarking takes 0.4606 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:38.0931648Z Autotune Choices Stats: 2025-09-07T09:51:38.0933537Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.43724799156188965, "best_triton_pos": 1, "best_triton_time": 0.6983680129051208, "best_triton_kernel": "triton_convolution2d_105", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:38.0945647Z AUTOTUNE convolution(2x128x320x479, 64x128x3x3) 2025-09-07T09:51:38.0946068Z strides: [19619840, 153280, 479, 1], [1152, 9, 3, 1] 2025-09-07T09:51:38.0946427Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:38.0946732Z convolution 0.4372 ms 100.0% 2025-09-07T09:51:38.0947621Z triton_convolution2d_105 0.6984 ms 62.6% 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 2025-09-07T09:51:38.0949124Z triton_convolution2d_107 0.8028 ms 54.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:38.0950640Z triton_convolution2d_110 0.8397 ms 52.1% 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 2025-09-07T09:51:38.0952442Z triton_convolution2d_108 0.9646 ms 45.3% 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 2025-09-07T09:51:38.0953912Z triton_convolution2d_109 1.0271 ms 42.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:38.0955393Z triton_convolution2d_104 1.0650 ms 41.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:38.0956889Z triton_convolution2d_106 2.1924 ms 19.9% 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 2025-09-07T09:51:38.0958071Z SingleProcess AUTOTUNE benchmarking takes 0.3154 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:38.7859454Z Autotune Choices Stats: 2025-09-07T09:51:38.7861172Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.3532800078392029, "best_triton_pos": 1, "best_triton_time": 0.6717439889907837, "best_triton_kernel": "triton_convolution2d_28", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:38.7872257Z AUTOTUNE convolution(2x128x160x239, 256x128x3x3) 2025-09-07T09:51:38.7872658Z strides: [4898816, 38272, 239, 1], [1152, 9, 3, 1] 2025-09-07T09:51:38.7873003Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:38.7873333Z convolution 0.3533 ms 100.0% 2025-09-07T09:51:38.7874227Z triton_convolution2d_28 0.6717 ms 52.6% 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 2025-09-07T09:51:38.7875717Z triton_convolution2d_33 0.7823 ms 45.2% 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 2025-09-07T09:51:38.7877196Z triton_convolution2d_31 1.0516 ms 33.6% 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 2025-09-07T09:51:38.7878683Z triton_convolution2d_30 1.0875 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 2025-09-07T09:51:38.7880181Z triton_convolution2d_27 1.1039 ms 32.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:38.7881659Z triton_convolution2d_29 1.6671 ms 21.2% 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 2025-09-07T09:51:38.7883151Z triton_convolution2d_32 1.6783 ms 21.0% 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 2025-09-07T09:51:38.7884325Z SingleProcess AUTOTUNE benchmarking takes 0.3159 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:51:39.5008314Z Autotune Choices Stats: 2025-09-07T09:51:39.5010025Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.5038080215454102, "best_triton_pos": 1, "best_triton_time": 1.4039039611816406, "best_triton_kernel": "triton_convolution2d_35", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:39.5020569Z AUTOTUNE convolution(2x256x160x239, 256x256x3x3) 2025-09-07T09:51:39.5020972Z strides: [9789440, 38240, 239, 1], [2304, 9, 3, 1] 2025-09-07T09:51:39.5021331Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:39.5021650Z convolution 0.5038 ms 100.0% 2025-09-07T09:51:39.5022521Z triton_convolution2d_35 1.4039 ms 35.9% 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 2025-09-07T09:51:39.5024016Z triton_convolution2d_40 1.5933 ms 31.6% 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 2025-09-07T09:51:39.5025797Z triton_convolution2d_37 2.1105 ms 23.9% 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 2025-09-07T09:51:39.5027292Z triton_convolution2d_34 2.1371 ms 23.6% 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 2025-09-07T09:51:39.5028763Z triton_convolution2d_38 2.3409 ms 21.5% 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 2025-09-07T09:51:39.5030242Z triton_convolution2d_39 3.3423 ms 15.1% 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 2025-09-07T09:51:39.5031735Z triton_convolution2d_36 4.7360 ms 10.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:39.5032909Z SingleProcess AUTOTUNE benchmarking takes 0.3647 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:40.0939171Z Autotune Choices Stats: 2025-09-07T09:51:40.0940836Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.9103360176086426, "best_triton_pos": 1, "best_triton_time": 3.0648319721221924, "best_triton_kernel": "triton_convolution2d_84", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:40.0952410Z AUTOTUNE convolution(2x512x160x239, 256x512x3x3) 2025-09-07T09:51:40.0952850Z strides: [19578880, 38240, 239, 1], [4608, 9, 3, 1] 2025-09-07T09:51:40.0953216Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:40.0953540Z convolution 0.9103 ms 100.0% 2025-09-07T09:51:40.0954463Z triton_convolution2d_84 3.0648 ms 29.7% 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 2025-09-07T09:51:40.0955966Z triton_convolution2d_89 3.4560 ms 26.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:40.0957455Z triton_convolution2d_83 4.1380 ms 22.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:40.0964637Z triton_convolution2d_86 4.2076 ms 21.6% 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 2025-09-07T09:51:40.0966141Z triton_convolution2d_87 4.5701 ms 19.9% 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 2025-09-07T09:51:40.0967622Z triton_convolution2d_88 6.6580 ms 13.7% 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 2025-09-07T09:51:40.0969111Z triton_convolution2d_85 10.1990 ms 8.9% 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 2025-09-07T09:51:40.0970277Z SingleProcess AUTOTUNE benchmarking takes 0.4711 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:40.5340688Z Autotune Choices Stats: 2025-09-07T09:51:40.5347938Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2959359884262085, "best_triton_pos": 1, "best_triton_time": 0.7331839799880981, "best_triton_kernel": "triton_convolution2d_91", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:40.5354926Z AUTOTUNE convolution(2x256x160x239, 128x256x3x3) 2025-09-07T09:51:40.5355297Z strides: [9789440, 38240, 239, 1], [2304, 9, 3, 1] 2025-09-07T09:51:40.5355658Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:40.5355981Z convolution 0.2959 ms 100.0% 2025-09-07T09:51:40.5356866Z triton_convolution2d_91 0.7332 ms 40.4% 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 2025-09-07T09:51:40.5358378Z triton_convolution2d_96 0.8724 ms 33.9% 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 2025-09-07T09:51:40.5359865Z triton_convolution2d_90 0.9155 ms 32.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:40.5361331Z triton_convolution2d_94 1.0732 ms 27.6% 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 2025-09-07T09:51:40.5362808Z triton_convolution2d_93 1.1028 ms 26.8% 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 2025-09-07T09:51:40.5364300Z triton_convolution2d_95 1.3281 ms 22.3% 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 2025-09-07T09:51:40.5365785Z triton_convolution2d_92 2.4044 ms 12.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:40.5366960Z SingleProcess AUTOTUNE benchmarking takes 0.3180 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:41.1990500Z Autotune Choices Stats: 2025-09-07T09:51:41.1992198Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2693119943141937, "best_triton_pos": 1, "best_triton_time": 0.6553599834442139, "best_triton_kernel": "triton_convolution2d_42", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:41.2004013Z AUTOTUNE convolution(2x256x80x119, 512x256x3x3) 2025-09-07T09:51:41.2004439Z strides: [2441216, 9536, 119, 1], [2304, 9, 3, 1] 2025-09-07T09:51:41.2004793Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:41.2005111Z convolution 0.2693 ms 100.0% 2025-09-07T09:51:41.2005997Z triton_convolution2d_42 0.6554 ms 41.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:41.2007491Z triton_convolution2d_47 0.8335 ms 32.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:41.2008980Z triton_convolution2d_45 1.0035 ms 26.8% 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 2025-09-07T09:51:41.2010661Z triton_convolution2d_41 1.0824 ms 24.9% 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 2025-09-07T09:51:41.2012162Z triton_convolution2d_44 1.1080 ms 24.3% 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 2025-09-07T09:51:41.2013948Z triton_convolution2d_43 1.6640 ms 16.2% 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 2025-09-07T09:51:41.2015448Z triton_convolution2d_46 1.7828 ms 15.1% 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 2025-09-07T09:51:41.2016611Z SingleProcess AUTOTUNE benchmarking takes 0.3160 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:51:41.9044532Z Autotune Choices Stats: 2025-09-07T09:51:41.9046193Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.4403199851512909, "best_triton_pos": 1, "best_triton_time": 1.334272027015686, "best_triton_kernel": "triton_convolution2d_49", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:41.9058936Z AUTOTUNE convolution(2x512x80x119, 512x512x3x3) 2025-09-07T09:51:41.9059316Z strides: [4874240, 9520, 119, 1], [4608, 9, 3, 1] 2025-09-07T09:51:41.9059706Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:41.9060029Z convolution 0.4403 ms 100.0% 2025-09-07T09:51:41.9060931Z triton_convolution2d_49 1.3343 ms 33.0% 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 2025-09-07T09:51:41.9062433Z triton_convolution2d_54 1.6527 ms 26.6% 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 2025-09-07T09:51:41.9063926Z triton_convolution2d_48 2.1811 ms 20.2% 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 2025-09-07T09:51:41.9065457Z triton_convolution2d_52 2.2876 ms 19.2% 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 2025-09-07T09:51:41.9067289Z triton_convolution2d_51 2.3736 ms 18.6% 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 2025-09-07T09:51:41.9068787Z triton_convolution2d_50 3.3792 ms 13.0% 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 2025-09-07T09:51:41.9070271Z triton_convolution2d_53 3.5768 ms 12.3% 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 2025-09-07T09:51:41.9071445Z SingleProcess AUTOTUNE benchmarking takes 0.3622 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:42.4971404Z Autotune Choices Stats: 2025-09-07T09:51:42.4973733Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.8243200182914734, "best_triton_pos": 1, "best_triton_time": 2.899967908859253, "best_triton_kernel": "triton_convolution2d_70", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:42.4985887Z AUTOTUNE convolution(2x1024x80x119, 512x1024x3x3) 2025-09-07T09:51:42.4986282Z strides: [9748480, 9520, 119, 1], [9216, 9, 3, 1] 2025-09-07T09:51:42.4986640Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:42.4986945Z convolution 0.8243 ms 100.0% 2025-09-07T09:51:42.4987826Z triton_convolution2d_70 2.9000 ms 28.4% 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 2025-09-07T09:51:42.4989326Z triton_convolution2d_75 3.6035 ms 22.9% 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 2025-09-07T09:51:42.4990810Z triton_convolution2d_69 4.5926 ms 17.9% 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 2025-09-07T09:51:42.4992298Z triton_convolution2d_72 4.6295 ms 17.8% 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 2025-09-07T09:51:42.4993789Z triton_convolution2d_73 4.8712 ms 16.9% 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 2025-09-07T09:51:42.4995281Z triton_convolution2d_74 7.2602 ms 11.4% 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 2025-09-07T09:51:42.4996776Z triton_convolution2d_71 8.0435 ms 10.2% 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 2025-09-07T09:51:42.4997935Z SingleProcess AUTOTUNE benchmarking takes 0.4818 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:42.9228811Z Autotune Choices Stats: 2025-09-07T09:51:42.9230467Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2611199915409088, "best_triton_pos": 1, "best_triton_time": 0.8468480110168457, "best_triton_kernel": "triton_convolution2d_82", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:51:42.9242745Z AUTOTUNE convolution(2x512x80x119, 256x512x3x3) 2025-09-07T09:51:42.9243131Z strides: [4874240, 9520, 119, 1], [4608, 9, 3, 1] 2025-09-07T09:51:42.9243492Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:42.9243830Z convolution 0.2611 ms 100.0% 2025-09-07T09:51:42.9244722Z triton_convolution2d_82 0.8468 ms 30.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:42.9246216Z triton_convolution2d_77 0.8632 ms 30.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:42.9247690Z triton_convolution2d_80 1.0486 ms 24.9% 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 2025-09-07T09:51:42.9249359Z triton_convolution2d_79 1.1182 ms 23.4% 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 2025-09-07T09:51:42.9250861Z triton_convolution2d_76 1.3496 ms 19.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:42.9252355Z triton_convolution2d_78 1.7060 ms 15.3% 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 2025-09-07T09:51:42.9254090Z triton_convolution2d_81 1.7992 ms 14.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:42.9255276Z SingleProcess AUTOTUNE benchmarking takes 0.3163 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:43.5195895Z Autotune Choices Stats: 2025-09-07T09:51:43.5197283Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_130", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, 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=2, num_warps=8", "best_time": 0.15564799308776855, "best_triton_pos": 0} 2025-09-07T09:51:43.5210204Z AUTOTUNE convolution(2x64x640x959, 2x64x1x1) 2025-09-07T09:51:43.5210604Z strides: [39280640, 613760, 959, 1], [64, 1, 1, 1] 2025-09-07T09:51:43.5210967Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:43.5211873Z triton_convolution2d_130 0.1556 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, 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=2, num_warps=8 2025-09-07T09:51:43.5213070Z convolution 0.1638 ms 95.0% 2025-09-07T09:51:43.5213960Z triton_convolution2d_129 0.1638 ms 95.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, 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=2, num_warps=4 2025-09-07T09:51:43.5215447Z triton_convolution2d_128 0.1649 ms 94.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, 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=2, num_warps=8 2025-09-07T09:51:43.5216932Z triton_convolution2d_126 0.1659 ms 93.8% 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=2, num_warps=4 2025-09-07T09:51:43.5218410Z triton_convolution2d_125 0.1731 ms 89.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, 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=2, num_warps=4 2025-09-07T09:51:43.5220254Z triton_convolution2d_127 0.1802 ms 86.4% 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=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:43.5221147Z conv1x1_via_mm 0.8059 ms 19.3% 2025-09-07T09:51:43.5221719Z SingleProcess AUTOTUNE benchmarking takes 0.2422 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:44.1163119Z Autotune Choices Stats: 2025-09-07T09:51:44.1164799Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.17100800573825836, "best_triton_pos": 1, "best_triton_time": 0.4259839951992035, "best_triton_kernel": "triton_convolution2d_56", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:44.1179517Z AUTOTUNE convolution(2x512x40x59, 512x512x3x3) 2025-09-07T09:51:44.1179918Z strides: [1212416, 2368, 59, 1], [4608, 9, 3, 1] 2025-09-07T09:51:44.1180276Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:44.1180962Z convolution 0.1710 ms 100.0% 2025-09-07T09:51:44.1181866Z triton_convolution2d_56 0.4260 ms 40.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:44.1183355Z triton_convolution2d_61 0.5417 ms 31.6% 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 2025-09-07T09:51:44.1184921Z triton_convolution2d_59 0.6963 ms 24.6% 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 2025-09-07T09:51:44.1186433Z triton_convolution2d_58 0.7035 ms 24.3% 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 2025-09-07T09:51:44.1187930Z triton_convolution2d_55 0.8049 ms 21.2% 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 2025-09-07T09:51:44.1189419Z triton_convolution2d_57 1.0506 ms 16.3% 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 2025-09-07T09:51:44.1190908Z triton_convolution2d_60 1.1377 ms 15.0% 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 2025-09-07T09:51:44.1192082Z SingleProcess AUTOTUNE benchmarking takes 0.3005 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:44.7582921Z Autotune Choices Stats: 2025-09-07T09:51:44.7584702Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.16076800227165222, "best_triton_pos": 1, "best_triton_time": 0.4188160002231598, "best_triton_kernel": "triton_convolution2d_63", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:51:44.7597910Z AUTOTUNE convolution(2x512x40x59, 512x512x3x3) 2025-09-07T09:51:44.7598333Z strides: [1208320, 2360, 59, 1], [4608, 9, 3, 1] 2025-09-07T09:51:44.7598705Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:44.7599014Z convolution 0.1608 ms 100.0% 2025-09-07T09:51:44.7599903Z triton_convolution2d_63 0.4188 ms 38.4% 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 2025-09-07T09:51:44.7601779Z triton_convolution2d_68 0.5356 ms 30.0% 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 2025-09-07T09:51:44.7603265Z triton_convolution2d_66 0.6482 ms 24.8% 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 2025-09-07T09:51:44.7604760Z triton_convolution2d_65 0.7434 ms 21.6% 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 2025-09-07T09:51:44.7606250Z triton_convolution2d_62 0.8059 ms 19.9% 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 2025-09-07T09:51:44.7607917Z triton_convolution2d_64 1.0516 ms 15.3% 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 2025-09-07T09:51:44.7609429Z triton_convolution2d_67 1.1233 ms 14.3% 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 2025-09-07T09:51:44.7610608Z SingleProcess AUTOTUNE benchmarking takes 0.2992 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:05.9773659Z W0907 09:52:05.976000 23013 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:52:15.9178872Z pass_due_to_skip 2025-09-07T09:52:19.9656253Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:52:19.9657691Z import pynvml # type: ignore[import] 2025-09-07T09:52:22.8762604Z 2025-09-07T09:52:25.6907799Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:25.6908188Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:52:25.6908516Z cuda train resnet152 2025-09-07T09:53:07.0810952Z Autotune Choices Stats: 2025-09-07T09:53:07.0812174Z {"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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T09:53:07.0828017Z AUTOTUNE mm(12544x64, 64x256) 2025-09-07T09:53:07.0828359Z strides: [64, 1], [1, 64] 2025-09-07T09:53:07.0828649Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:07.0829430Z triton_mm_58 0.0133 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 2025-09-07T09:53:07.0830631Z triton_mm_61 0.0133 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 2025-09-07T09:53:07.0831822Z triton_mm_62 0.0133 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:07.0833014Z triton_mm_65 0.0133 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=2, num_warps=8 2025-09-07T09:53:07.0834565Z triton_mm_68 0.0133 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 2025-09-07T09:53:07.0835758Z triton_mm_57 0.0143 ms 92.9% 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 2025-09-07T09:53:07.0836935Z triton_mm_59 0.0143 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=3, num_warps=4 2025-09-07T09:53:07.0838173Z triton_mm_63 0.0143 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 2025-09-07T09:53:07.0839353Z triton_mm_64 0.0143 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=4, num_warps=8 2025-09-07T09:53:07.0840540Z triton_mm_66 0.0143 ms 92.9% 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 2025-09-07T09:53:07.0841757Z SingleProcess AUTOTUNE benchmarking takes 0.3453 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T09:53:08.6629267Z Autotune Choices Stats: 2025-09-07T09:53:08.6631372Z {"num_choices": 19, "num_triton_choices": 18, "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": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T09:53:08.6645383Z AUTOTUNE mm(12544x256, 256x128) 2025-09-07T09:53:08.6645914Z strides: [256, 1], [1, 256] 2025-09-07T09:53:08.6646414Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:08.6647770Z triton_mm_168 0.0164 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:08.6649929Z triton_mm_173 0.0164 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 2025-09-07T09:53:08.6651226Z mm 0.0174 ms 94.1% 2025-09-07T09:53:08.6652398Z triton_mm_166 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:08.6654804Z triton_mm_167 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:08.6656834Z triton_mm_169 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:08.6658847Z triton_mm_170 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:08.6660897Z triton_mm_172 0.0174 ms 94.1% 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 2025-09-07T09:53:08.6662928Z triton_mm_174 0.0174 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 2025-09-07T09:53:08.6665089Z triton_mm_163 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:08.6666948Z SingleProcess AUTOTUNE benchmarking takes 0.2695 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:09.2130036Z Autotune Choices Stats: 2025-09-07T09:53:09.2133304Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_241", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T09:53:09.2146580Z AUTOTUNE mm(3136x128, 128x512) 2025-09-07T09:53:09.2147108Z strides: [128, 1], [1, 128] 2025-09-07T09:53:09.2147638Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:09.2149122Z triton_mm_241 0.0113 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 2025-09-07T09:53:09.2151525Z triton_mm_247 0.0113 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 2025-09-07T09:53:09.2153029Z mm 0.0123 ms 91.7% 2025-09-07T09:53:09.2154376Z triton_mm_238 0.0123 ms 91.7% 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 2025-09-07T09:53:09.2157165Z triton_mm_240 0.0123 ms 91.7% 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 2025-09-07T09:53:09.2159518Z triton_mm_242 0.0123 ms 91.7% 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 2025-09-07T09:53:09.2161885Z triton_mm_243 0.0123 ms 91.7% 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 2025-09-07T09:53:09.2164242Z triton_mm_244 0.0123 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 2025-09-07T09:53:09.2166627Z triton_mm_245 0.0123 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=4, num_warps=8 2025-09-07T09:53:09.2169018Z triton_mm_248 0.0123 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=3, num_warps=4 2025-09-07T09:53:09.2171072Z SingleProcess AUTOTUNE benchmarking takes 0.2539 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:10.3576898Z Autotune Choices Stats: 2025-09-07T09:53:10.3579121Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_7", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:53:10.3595158Z AUTOTUNE mm(12544x64, 64x64) 2025-09-07T09:53:10.3595750Z strides: [64, 1], [1, 64] 2025-09-07T09:53:10.3596248Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:10.3597648Z triton_mm_7 0.0102 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 2025-09-07T09:53:10.3599915Z triton_mm_10 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:10.3601865Z triton_mm_12 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:53:10.3603633Z triton_mm_13 0.0102 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 2025-09-07T09:53:10.3605600Z triton_mm_14 0.0102 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 2025-09-07T09:53:10.3608413Z triton_mm_15 0.0102 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 2025-09-07T09:53:10.3610463Z triton_mm_16 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:10.3612576Z triton_mm_17 0.0102 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 2025-09-07T09:53:10.3615210Z triton_mm_18 0.0102 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 2025-09-07T09:53:10.3617445Z triton_mm_19 0.0102 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 2025-09-07T09:53:10.3619410Z SingleProcess AUTOTUNE benchmarking takes 0.2572 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:10.9302611Z Autotune Choices Stats: 2025-09-07T09:53:10.9304948Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_76", "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T09:53:10.9320371Z AUTOTUNE mm(12544x256, 256x64) 2025-09-07T09:53:10.9320900Z strides: [256, 1], [1, 256] 2025-09-07T09:53:10.9321438Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:10.9322899Z triton_mm_76 0.0154 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 2025-09-07T09:53:10.9325267Z triton_mm_78 0.0154 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 2025-09-07T09:53:10.9327618Z triton_mm_80 0.0154 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 2025-09-07T09:53:10.9329983Z triton_mm_82 0.0154 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 2025-09-07T09:53:10.9332352Z triton_mm_85 0.0154 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:10.9335084Z triton_mm_86 0.0154 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 2025-09-07T09:53:10.9337444Z triton_mm_79 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:10.9339768Z triton_mm_83 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:10.9341240Z mm 0.0174 ms 88.2% 2025-09-07T09:53:10.9342575Z triton_mm_70 0.0174 ms 88.2% 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 2025-09-07T09:53:10.9344604Z SingleProcess AUTOTUNE benchmarking takes 0.2668 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T09:53:11.2553854Z Autotune Choices Stats: 2025-09-07T09:53:11.2556769Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_mm_518", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8"} 2025-09-07T09:53:11.2572677Z AUTOTUNE mm(3136x512, 512x256) 2025-09-07T09:53:11.2573378Z strides: [512, 1], [1, 512] 2025-09-07T09:53:11.2573915Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:11.2574458Z mm 0.0143 ms 100.0% 2025-09-07T09:53:11.2575796Z triton_mm_518 0.0143 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 2025-09-07T09:53:11.2578183Z triton_mm_519 0.0143 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 2025-09-07T09:53:11.2580544Z triton_mm_515 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:53:11.2583255Z triton_mm_521 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:11.2585684Z triton_mm_517 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:11.2588006Z triton_mm_520 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:11.2590372Z triton_mm_524 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:11.2592752Z triton_mm_525 0.0164 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 2025-09-07T09:53:11.2595127Z triton_mm_516 0.0174 ms 82.4% 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 2025-09-07T09:53:11.2597157Z SingleProcess AUTOTUNE benchmarking takes 0.2656 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:11.8030070Z Autotune Choices Stats: 2025-09-07T09:53:11.8032337Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_593", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T09:53:11.8049529Z AUTOTUNE mm(784x256, 256x1024) 2025-09-07T09:53:11.8049911Z strides: [256, 1], [1, 256] 2025-09-07T09:53:11.8050203Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:11.8050973Z triton_mm_593 0.0113 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 2025-09-07T09:53:11.8052195Z triton_mm_594 0.0113 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 2025-09-07T09:53:11.8053150Z mm 0.0123 ms 91.7% 2025-09-07T09:53:11.8053847Z triton_mm_590 0.0123 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 2025-09-07T09:53:11.8055041Z triton_mm_592 0.0123 ms 91.7% 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 2025-09-07T09:53:11.8056603Z triton_mm_599 0.0123 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=3, num_warps=4 2025-09-07T09:53:11.8057793Z triton_mm_595 0.0133 ms 84.6% 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 2025-09-07T09:53:11.8058982Z triton_mm_596 0.0133 ms 84.6% 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 2025-09-07T09:53:11.8060174Z triton_mm_598 0.0133 ms 84.6% 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 2025-09-07T09:53:11.8061370Z triton_mm_600 0.0133 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=5, num_warps=8 2025-09-07T09:53:11.8062412Z SingleProcess AUTOTUNE benchmarking takes 0.2598 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:13.6670343Z Autotune Choices Stats: 2025-09-07T09:53:13.6673193Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_215", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:53:13.6691553Z AUTOTUNE mm(3136x512, 512x128) 2025-09-07T09:53:13.6692058Z strides: [512, 1], [1, 512] 2025-09-07T09:53:13.6692559Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:13.6694338Z triton_mm_215 0.0123 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 2025-09-07T09:53:13.6695670Z mm 0.0133 ms 92.3% 2025-09-07T09:53:13.6696903Z triton_mm_214 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:53:13.6699086Z triton_mm_208 0.0143 ms 85.7% 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 2025-09-07T09:53:13.6701233Z triton_mm_209 0.0143 ms 85.7% 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 2025-09-07T09:53:13.6703286Z triton_mm_210 0.0143 ms 85.7% 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 2025-09-07T09:53:13.6705495Z triton_mm_217 0.0143 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=4, num_warps=8 2025-09-07T09:53:13.6707588Z triton_mm_218 0.0143 ms 85.7% 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 2025-09-07T09:53:13.6709721Z triton_mm_220 0.0143 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 2025-09-07T09:53:13.6711829Z triton_mm_211 0.0154 ms 80.0% 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 2025-09-07T09:53:13.6713648Z SingleProcess AUTOTUNE benchmarking takes 0.2568 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:14.9331852Z Autotune Choices Stats: 2025-09-07T09:53:14.9334799Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_mm_2071", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:53:14.9361206Z AUTOTUNE mm(784x1024, 1024x512) 2025-09-07T09:53:14.9361709Z strides: [1024, 1], [1, 1024] 2025-09-07T09:53:14.9362236Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:14.9362773Z mm 0.0143 ms 100.0% 2025-09-07T09:53:14.9364035Z triton_mm_2071 0.0143 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 2025-09-07T09:53:14.9366093Z triton_mm_2070 0.0164 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=8 2025-09-07T09:53:14.9368305Z triton_mm_2067 0.0184 ms 77.8% 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 2025-09-07T09:53:14.9370398Z triton_mm_2074 0.0184 ms 77.8% 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 2025-09-07T09:53:14.9373151Z triton_mm_2064 0.0205 ms 70.0% 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 2025-09-07T09:53:14.9375240Z triton_mm_2065 0.0205 ms 70.0% 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 2025-09-07T09:53:14.9377409Z triton_mm_2066 0.0205 ms 70.0% 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 2025-09-07T09:53:14.9379511Z triton_mm_2073 0.0205 ms 70.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:14.9381670Z triton_mm_2076 0.0205 ms 70.0% 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 2025-09-07T09:53:14.9383564Z SingleProcess AUTOTUNE benchmarking takes 0.2755 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:15.4892276Z Autotune Choices Stats: 2025-09-07T09:53:15.4895277Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "best_triton_kernel": "triton_mm_2149", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:53:15.4913256Z AUTOTUNE mm(196x512, 512x2048) 2025-09-07T09:53:15.4913648Z strides: [512, 1], [1, 512] 2025-09-07T09:53:15.4913987Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:15.4914284Z mm 0.0133 ms 100.0% 2025-09-07T09:53:15.4915005Z triton_mm_2149 0.0133 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 2025-09-07T09:53:15.4916231Z triton_mm_2145 0.0143 ms 92.9% 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 2025-09-07T09:53:15.4917419Z triton_mm_2148 0.0143 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 2025-09-07T09:53:15.4918616Z triton_mm_2151 0.0143 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=4, num_warps=8 2025-09-07T09:53:15.4919809Z triton_mm_2139 0.0164 ms 81.2% 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 2025-09-07T09:53:15.4921340Z triton_mm_2146 0.0164 ms 81.2% 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 2025-09-07T09:53:15.4922537Z triton_mm_2147 0.0164 ms 81.2% 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 2025-09-07T09:53:15.4923728Z triton_mm_2150 0.0164 ms 81.2% 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 2025-09-07T09:53:15.4924929Z triton_mm_2154 0.0164 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:15.4925968Z SingleProcess AUTOTUNE benchmarking takes 0.2547 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:16.7823048Z Autotune Choices Stats: 2025-09-07T09:53:16.7824841Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_562", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:53:16.7846471Z AUTOTUNE mm(784x1024, 1024x256) 2025-09-07T09:53:16.7846836Z strides: [1024, 1], [1, 1024] 2025-09-07T09:53:16.7847132Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:16.7847893Z triton_mm_562 0.0123 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 2025-09-07T09:53:16.7848656Z mm 0.0133 ms 92.3% 2025-09-07T09:53:16.7849348Z triton_mm_566 0.0133 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 2025-09-07T09:53:16.7850557Z triton_mm_560 0.0154 ms 80.0% 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 2025-09-07T09:53:16.7851735Z triton_mm_561 0.0154 ms 80.0% 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 2025-09-07T09:53:16.7853136Z triton_mm_559 0.0164 ms 75.0% 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 2025-09-07T09:53:16.7854306Z triton_mm_565 0.0164 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 2025-09-07T09:53:16.7855489Z triton_mm_569 0.0174 ms 70.6% 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 2025-09-07T09:53:16.7856687Z triton_mm_568 0.0205 ms 60.0% 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 2025-09-07T09:53:16.7857871Z triton_mm_571 0.0205 ms 60.0% 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 2025-09-07T09:53:16.7858899Z SingleProcess AUTOTUNE benchmarking takes 0.2881 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:18.2465769Z Autotune Choices Stats: 2025-09-07T09:53:18.2466996Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_2117", "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T09:53:18.2488189Z AUTOTUNE mm(196x2048, 2048x512) 2025-09-07T09:53:18.2488732Z strides: [2048, 1], [1, 2048] 2025-09-07T09:53:18.2489251Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:18.2490721Z triton_mm_2117 0.0154 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 2025-09-07T09:53:18.2492196Z mm 0.0174 ms 88.2% 2025-09-07T09:53:18.2493849Z triton_mm_2121 0.0184 ms 83.3% 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 2025-09-07T09:53:18.2496211Z triton_mm_2115 0.0215 ms 71.4% 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 2025-09-07T09:53:18.2498527Z triton_mm_2116 0.0215 ms 71.4% 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 2025-09-07T09:53:18.2501309Z triton_mm_2114 0.0225 ms 68.2% 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 2025-09-07T09:53:18.2503650Z triton_mm_2120 0.0236 ms 65.2% 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 2025-09-07T09:53:18.2506050Z triton_mm_2124 0.0276 ms 55.6% 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 2025-09-07T09:53:18.2508379Z triton_mm_2123 0.0317 ms 48.4% 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 2025-09-07T09:53:18.2510749Z triton_mm_2126 0.0328 ms 46.9% 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 2025-09-07T09:53:18.2512774Z SingleProcess AUTOTUNE benchmarking takes 0.3000 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:53:20.0129565Z Autotune Choices Stats: 2025-09-07T09:53:20.0132708Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.048128001391887665, "best_triton_pos": 1, "best_triton_time": 0.1157120019197464, "best_triton_kernel": "triton_convolution2d_3", "best_triton_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"} 2025-09-07T09:53:20.0152387Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T09:53:20.0152802Z strides: [150528, 1, 672, 3], [147, 1, 21, 3] 2025-09-07T09:53:20.0153146Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.0153480Z convolution 0.0481 ms 100.0% 2025-09-07T09:53:20.0154382Z triton_convolution2d_3 0.1157 ms 41.6% 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 2025-09-07T09:53:20.0155879Z triton_convolution2d_0 0.1167 ms 41.2% 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 2025-09-07T09:53:20.0157359Z triton_convolution2d_2 0.1372 ms 35.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:53:20.0158834Z triton_convolution2d_4 0.1372 ms 35.1% 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 2025-09-07T09:53:20.0160639Z triton_convolution2d_5 0.1495 ms 32.2% 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=8 2025-09-07T09:53:20.0162131Z triton_convolution2d_1 0.3308 ms 14.6% 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 2025-09-07T09:53:20.0163306Z SingleProcess AUTOTUNE benchmarking takes 0.2583 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:53:20.1417036Z Autotune Choices Stats: 2025-09-07T09:53:20.1426198Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_convolution2d_28", "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"} 2025-09-07T09:53:20.1441035Z AUTOTUNE convolution(4x64x56x56, 64x64x3x3) 2025-09-07T09:53:20.1441415Z strides: [200704, 1, 3584, 64], [576, 1, 192, 64] 2025-09-07T09:53:20.1442098Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.1442426Z convolution 0.0164 ms 100.0% 2025-09-07T09:53:20.1443311Z triton_convolution2d_28 0.0225 ms 72.7% 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 2025-09-07T09:53:20.1444794Z triton_convolution2d_29 0.0236 ms 69.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.1446272Z triton_convolution2d_27 0.0246 ms 66.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.1447761Z triton_convolution2d_24 0.0307 ms 53.3% 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 2025-09-07T09:53:20.1449233Z triton_convolution2d_30 0.0338 ms 48.5% 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 2025-09-07T09:53:20.1450698Z triton_convolution2d_25 0.0399 ms 41.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:20.1452191Z triton_convolution2d_26 0.0604 ms 27.1% 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 2025-09-07T09:53:20.1453715Z SingleProcess AUTOTUNE benchmarking takes 0.1277 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:20.2963053Z Autotune Choices Stats: 2025-09-07T09:53:20.2964733Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.03891199827194214, "best_triton_kernel": "triton_convolution2d_179", "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"} 2025-09-07T09:53:20.2986052Z AUTOTUNE convolution(4x128x56x56, 128x128x3x3) 2025-09-07T09:53:20.2986451Z strides: [401408, 1, 7168, 128], [1152, 1, 384, 128] 2025-09-07T09:53:20.2986821Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.2987374Z convolution 0.0164 ms 100.0% 2025-09-07T09:53:20.2988262Z triton_convolution2d_179 0.0389 ms 42.1% 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 2025-09-07T09:53:20.2989759Z triton_convolution2d_180 0.0420 ms 39.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.2991263Z triton_convolution2d_178 0.0553 ms 29.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.2992761Z triton_convolution2d_175 0.0573 ms 28.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:20.2994263Z triton_convolution2d_181 0.0573 ms 28.6% 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 2025-09-07T09:53:20.2995931Z triton_convolution2d_176 0.0727 ms 22.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:20.2997434Z triton_convolution2d_177 0.1280 ms 12.8% 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 2025-09-07T09:53:20.2998617Z SingleProcess AUTOTUNE benchmarking takes 0.1508 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:20.4165845Z Autotune Choices Stats: 2025-09-07T09:53:20.4167481Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.016383999958634377, "best_triton_kernel": "triton_convolution2d_204", "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"} 2025-09-07T09:53:20.4188844Z AUTOTUNE convolution(4x256x56x56, 512x256x1x1) 2025-09-07T09:53:20.4189281Z strides: [802816, 1, 14336, 256], [256, 1, 256, 256] 2025-09-07T09:53:20.4189653Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.4189956Z convolution 0.0143 ms 100.0% 2025-09-07T09:53:20.4190841Z triton_convolution2d_204 0.0164 ms 87.5% 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 2025-09-07T09:53:20.4192338Z triton_convolution2d_203 0.0195 ms 73.7% 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 2025-09-07T09:53:20.4193843Z triton_convolution2d_205 0.0195 ms 73.7% 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 2025-09-07T09:53:20.4195336Z triton_convolution2d_206 0.0195 ms 73.7% 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 2025-09-07T09:53:20.4196830Z triton_convolution2d_200 0.0225 ms 63.6% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:20.4198320Z triton_convolution2d_201 0.0236 ms 60.9% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:20.4200045Z triton_convolution2d_202 0.0502 ms 28.6% 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 2025-09-07T09:53:20.4201208Z SingleProcess AUTOTUNE benchmarking takes 0.1191 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:20.5643032Z Autotune Choices Stats: 2025-09-07T09:53:20.5645223Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.03788800165057182, "best_triton_kernel": "triton_convolution2d_229", "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"} 2025-09-07T09:53:20.5666450Z AUTOTUNE convolution(4x128x28x28, 128x128x3x3) 2025-09-07T09:53:20.5667130Z strides: [100352, 1, 3584, 128], [1152, 1, 384, 128] 2025-09-07T09:53:20.5667786Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.5668348Z convolution 0.0154 ms 100.0% 2025-09-07T09:53:20.5670338Z triton_convolution2d_229 0.0379 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 2025-09-07T09:53:20.5673130Z triton_convolution2d_230 0.0410 ms 37.5% 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 2025-09-07T09:53:20.5675920Z triton_convolution2d_228 0.0532 ms 28.8% 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 2025-09-07T09:53:20.5678718Z triton_convolution2d_225 0.0563 ms 27.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:20.5681602Z triton_convolution2d_231 0.0573 ms 26.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.5684488Z triton_convolution2d_226 0.0655 ms 23.4% 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 2025-09-07T09:53:20.5687390Z triton_convolution2d_227 0.1198 ms 12.8% 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 2025-09-07T09:53:20.5689664Z SingleProcess AUTOTUNE benchmarking takes 0.1466 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:20.7669622Z Autotune Choices Stats: 2025-09-07T09:53:20.7672844Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.06656000018119812, "best_triton_kernel": "triton_convolution2d_530", "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"} 2025-09-07T09:53:20.7691927Z AUTOTUNE convolution(4x256x28x28, 256x256x3x3) 2025-09-07T09:53:20.7692634Z strides: [200704, 1, 7168, 256], [2304, 1, 768, 256] 2025-09-07T09:53:20.7693642Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.7694187Z convolution 0.0195 ms 100.0% 2025-09-07T09:53:20.7695927Z triton_convolution2d_530 0.0666 ms 29.2% 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 2025-09-07T09:53:20.7699257Z triton_convolution2d_529 0.1014 ms 19.2% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.7702217Z triton_convolution2d_532 0.1055 ms 18.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:20.7705213Z triton_convolution2d_531 0.1065 ms 18.3% 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 2025-09-07T09:53:20.7708181Z triton_convolution2d_527 0.1341 ms 14.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:20.7711316Z triton_convolution2d_526 0.1362 ms 14.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:20.7714297Z triton_convolution2d_528 0.2222 ms 8.8% 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 2025-09-07T09:53:20.7716616Z SingleProcess AUTOTUNE benchmarking takes 0.1941 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:20.8924898Z Autotune Choices Stats: 2025-09-07T09:53:20.8928115Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_convolution2d_555", "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"} 2025-09-07T09:53:20.8947587Z AUTOTUNE convolution(4x512x28x28, 1024x512x1x1) 2025-09-07T09:53:20.8948089Z strides: [401408, 1, 14336, 512], [512, 1, 512, 512] 2025-09-07T09:53:20.8948456Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:20.8948763Z convolution 0.0143 ms 100.0% 2025-09-07T09:53:20.8949654Z triton_convolution2d_555 0.0215 ms 66.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:20.8951161Z triton_convolution2d_554 0.0266 ms 53.8% 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 2025-09-07T09:53:20.8952681Z triton_convolution2d_556 0.0276 ms 51.9% 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 2025-09-07T09:53:20.8954183Z triton_convolution2d_557 0.0287 ms 50.0% 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 2025-09-07T09:53:20.8955672Z triton_convolution2d_551 0.0328 ms 43.8% 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 2025-09-07T09:53:20.8957165Z triton_convolution2d_552 0.0358 ms 40.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:20.8958963Z triton_convolution2d_553 0.0563 ms 25.5% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:53:20.8960134Z SingleProcess AUTOTUNE benchmarking takes 0.1245 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:21.0887260Z Autotune Choices Stats: 2025-09-07T09:53:21.0888917Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.06656000018119812, "best_triton_kernel": "triton_convolution2d_580", "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"} 2025-09-07T09:53:21.0912577Z AUTOTUNE convolution(4x256x14x14, 256x256x3x3) 2025-09-07T09:53:21.0912982Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T09:53:21.0913369Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:21.0913679Z convolution 0.0195 ms 100.0% 2025-09-07T09:53:21.0914876Z triton_convolution2d_580 0.0666 ms 29.2% 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 2025-09-07T09:53:21.0916373Z triton_convolution2d_579 0.0983 ms 19.8% 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 2025-09-07T09:53:21.0917880Z triton_convolution2d_581 0.1055 ms 18.4% 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 2025-09-07T09:53:21.0919366Z triton_convolution2d_582 0.1065 ms 18.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:21.0920874Z triton_convolution2d_577 0.1260 ms 15.4% 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 2025-09-07T09:53:21.0922377Z triton_convolution2d_576 0.1341 ms 14.5% 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 2025-09-07T09:53:21.0923879Z triton_convolution2d_578 0.2140 ms 9.1% 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 2025-09-07T09:53:21.0925050Z SingleProcess AUTOTUNE benchmarking takes 0.1954 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:21.3994557Z Autotune Choices Stats: 2025-09-07T09:53:21.3997792Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.12800000607967377, "best_triton_kernel": "triton_convolution2d_2085", "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"} 2025-09-07T09:53:21.4017568Z AUTOTUNE convolution(4x512x14x14, 512x512x3x3) 2025-09-07T09:53:21.4018043Z strides: [100352, 1, 7168, 512], [4608, 1, 1536, 512] 2025-09-07T09:53:21.4018417Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:21.4018723Z convolution 0.0276 ms 100.0% 2025-09-07T09:53:21.4019616Z triton_convolution2d_2085 0.1280 ms 21.6% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:21.4021408Z triton_convolution2d_2084 0.1925 ms 14.4% 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 2025-09-07T09:53:21.4022925Z triton_convolution2d_2087 0.1976 ms 14.0% 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 2025-09-07T09:53:21.4024424Z triton_convolution2d_2086 0.2048 ms 13.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:21.4026013Z triton_convolution2d_2082 0.2632 ms 10.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:21.4027518Z triton_convolution2d_2081 0.2796 ms 9.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:21.4029160Z triton_convolution2d_2083 0.3308 ms 8.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:53:21.4030331Z SingleProcess AUTOTUNE benchmarking takes 0.2636 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:21.5481611Z Autotune Choices Stats: 2025-09-07T09:53:21.5484858Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "best_triton_kernel": "triton_convolution2d_2110", "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"} 2025-09-07T09:53:21.5506331Z AUTOTUNE convolution(4x1024x14x14, 2048x1024x1x1) 2025-09-07T09:53:21.5506783Z strides: [200704, 1, 14336, 1024], [1024, 1, 1024, 1024] 2025-09-07T09:53:21.5507174Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:21.5507480Z convolution 0.0184 ms 100.0% 2025-09-07T09:53:21.5508369Z triton_convolution2d_2110 0.0348 ms 52.9% 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 2025-09-07T09:53:21.5509882Z triton_convolution2d_2109 0.0461 ms 40.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:21.5511388Z triton_convolution2d_2111 0.0461 ms 40.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:21.5512901Z triton_convolution2d_2112 0.0481 ms 38.3% 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 2025-09-07T09:53:21.5514400Z triton_convolution2d_2106 0.0573 ms 32.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:21.5515903Z triton_convolution2d_2107 0.0625 ms 29.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:21.5517424Z triton_convolution2d_2108 0.1382 ms 13.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:53:21.5518869Z SingleProcess AUTOTUNE benchmarking takes 0.1469 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:21.8056162Z Autotune Choices Stats: 2025-09-07T09:53:21.8057836Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.130048006772995, "best_triton_kernel": "triton_convolution2d_2135", "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"} 2025-09-07T09:53:21.8079699Z AUTOTUNE convolution(4x512x7x7, 512x512x3x3) 2025-09-07T09:53:21.8080115Z strides: [25088, 1, 3584, 512], [4608, 1, 1536, 512] 2025-09-07T09:53:21.8080466Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:21.8080794Z convolution 0.0266 ms 100.0% 2025-09-07T09:53:21.8081691Z triton_convolution2d_2135 0.1300 ms 20.5% 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 2025-09-07T09:53:21.8083531Z triton_convolution2d_2134 0.1935 ms 13.8% 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 2025-09-07T09:53:21.8085055Z triton_convolution2d_2136 0.2048 ms 13.0% 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 2025-09-07T09:53:21.8086556Z triton_convolution2d_2137 0.2089 ms 12.7% 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 2025-09-07T09:53:21.8088062Z triton_convolution2d_2133 0.2130 ms 12.5% 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 2025-09-07T09:53:21.8089555Z triton_convolution2d_2132 0.2580 ms 10.3% 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 2025-09-07T09:53:21.8091058Z triton_convolution2d_2131 0.2836 ms 9.4% 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 2025-09-07T09:53:21.8092230Z SingleProcess AUTOTUNE benchmarking takes 0.2559 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:22.1101210Z Autotune Choices Stats: 2025-09-07T09:53:22.1102406Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_2203", "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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T09:53:22.1126901Z AUTOTUNE addmm(4x1000, 4x2048, 2048x1000) 2025-09-07T09:53:22.1127321Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T09:53:22.1127671Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:53:22.1128500Z triton_mm_2203 0.0133 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 2025-09-07T09:53:22.1129709Z triton_mm_2207 0.0143 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:22.1130909Z triton_mm_2211 0.0174 ms 76.5% 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 2025-09-07T09:53:22.1131914Z bias_addmm 0.0184 ms 72.2% 2025-09-07T09:53:22.1132629Z triton_mm_2215 0.0184 ms 72.2% 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 2025-09-07T09:53:22.1133557Z addmm 0.0205 ms 65.0% 2025-09-07T09:53:22.1134266Z triton_mm_2202 0.0205 ms 65.0% 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 2025-09-07T09:53:22.1135442Z triton_mm_2201 0.0215 ms 61.9% 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 2025-09-07T09:53:22.1136624Z triton_mm_2206 0.0215 ms 61.9% 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 2025-09-07T09:53:22.1137812Z triton_mm_2200 0.0225 ms 59.1% 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 2025-09-07T09:53:22.1143880Z SingleProcess AUTOTUNE benchmarking takes 0.3005 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:53:43.6587407Z Autotune Choices Stats: 2025-09-07T09:53:43.6588643Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_2235", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:53:43.6615118Z AUTOTUNE mm(1000x4, 4x2048) 2025-09-07T09:53:43.6615424Z strides: [1, 1000], [2048, 1] 2025-09-07T09:53:43.6615728Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:43.6616508Z triton_mm_2235 0.0092 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 2025-09-07T09:53:43.6617748Z triton_mm_2238 0.0092 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 2025-09-07T09:53:43.6618955Z triton_mm_2239 0.0092 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 2025-09-07T09:53:43.6620164Z triton_mm_2240 0.0092 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 2025-09-07T09:53:43.6621381Z triton_mm_2241 0.0092 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 2025-09-07T09:53:43.6622599Z triton_mm_2242 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:43.6623824Z triton_mm_2243 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:43.6625118Z triton_mm_2244 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:53:43.6626330Z triton_mm_2245 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:53:43.6627555Z triton_mm_2246 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:53:43.6628916Z SingleProcess AUTOTUNE benchmarking takes 0.2117 seconds and 0.0004 seconds precompiling for 17 choices 2025-09-07T09:53:44.3948267Z Autotune Choices Stats: 2025-09-07T09:53:44.3949536Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_2224", "best_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", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:53:44.3975461Z AUTOTUNE mm(4x1000, 1000x2048) 2025-09-07T09:53:44.3975781Z strides: [1000, 1], [2048, 1] 2025-09-07T09:53:44.3976078Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:44.3976856Z triton_mm_2224 0.0123 ms 100.0% 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 2025-09-07T09:53:44.3978083Z triton_mm_2220 0.0133 ms 92.3% 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 2025-09-07T09:53:44.3979696Z triton_mm_2228 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:44.3980920Z triton_mm_2232 0.0133 ms 92.3% 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 2025-09-07T09:53:44.3981670Z mm 0.0143 ms 85.7% 2025-09-07T09:53:44.3982344Z triton_mm_2218 0.0143 ms 85.7% 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 2025-09-07T09:53:44.3983531Z triton_mm_2223 0.0143 ms 85.7% 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 2025-09-07T09:53:44.3984826Z triton_mm_2219 0.0154 ms 80.0% 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 2025-09-07T09:53:44.3986030Z triton_mm_2227 0.0154 ms 80.0% 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 2025-09-07T09:53:44.3987229Z triton_mm_2230 0.0154 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:53:44.3988259Z SingleProcess AUTOTUNE benchmarking takes 0.2498 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:53:59.0181624Z W0907 09:53:59.017000 26683 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:55:24.9053153Z pass 2025-09-07T09:55:33.4601144Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:55:33.4603742Z import pynvml # type: ignore[import] 2025-09-07T09:55:36.1380665Z 2025-09-07T09:55:38.2394186Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:38.2394570Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:55:38.2394889Z cuda train resnet18 2025-09-07T09:55:48.3107785Z Autotune Choices Stats: 2025-09-07T09:55:48.3109626Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "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=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:48.3134648Z AUTOTUNE convolution(4x64x56x56, 128x64x3x3) 2025-09-07T09:55:48.3136798Z strides: [200704, 1, 3584, 64], [576, 1, 192, 64] 2025-09-07T09:55:48.3137286Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:48.3137751Z convolution 0.0133 ms 100.0% 2025-09-07T09:55:48.3139107Z triton_convolution2d_38 0.0215 ms 61.9% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:48.3140633Z triton_convolution2d_39 0.0256 ms 52.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:48.3142122Z triton_convolution2d_34 0.0297 ms 44.8% 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 2025-09-07T09:55:48.3143968Z triton_convolution2d_37 0.0307 ms 43.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:48.3145561Z triton_convolution2d_40 0.0328 ms 40.6% 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 2025-09-07T09:55:48.3147070Z triton_convolution2d_35 0.0399 ms 33.3% 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 2025-09-07T09:55:48.3148559Z triton_convolution2d_36 0.0666 ms 20.0% 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:48.3149759Z SingleProcess AUTOTUNE benchmarking takes 0.1696 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:48.4322686Z Autotune Choices Stats: 2025-09-07T09:55:48.4324074Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_52", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:55:48.4351773Z AUTOTUNE convolution(4x64x56x56, 128x64x1x1) 2025-09-07T09:55:48.4352153Z strides: [200704, 1, 3584, 64], [64, 1, 64, 64] 2025-09-07T09:55:48.4352511Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:48.4353413Z triton_convolution2d_52 0.0092 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 2025-09-07T09:55:48.4354933Z triton_convolution2d_53 0.0092 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:48.4355853Z convolution 0.0102 ms 90.0% 2025-09-07T09:55:48.4356726Z triton_convolution2d_48 0.0102 ms 90.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:48.4358207Z triton_convolution2d_54 0.0102 ms 90.0% 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 2025-09-07T09:55:48.4359695Z triton_convolution2d_49 0.0113 ms 81.8% 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 2025-09-07T09:55:48.4361504Z triton_convolution2d_51 0.0113 ms 81.8% 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 2025-09-07T09:55:48.4362987Z triton_convolution2d_50 0.0154 ms 60.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:55:48.4364166Z SingleProcess AUTOTUNE benchmarking takes 0.1194 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:48.5924276Z Autotune Choices Stats: 2025-09-07T09:55:48.5925977Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.035840000957250595, "best_triton_kernel": "triton_convolution2d_73", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:48.5949758Z AUTOTUNE convolution(4x128x28x28, 256x128x3x3) 2025-09-07T09:55:48.5950559Z strides: [100352, 1, 3584, 128], [1152, 1, 384, 128] 2025-09-07T09:55:48.5950930Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:48.5951250Z convolution 0.0143 ms 100.0% 2025-09-07T09:55:48.5952130Z triton_convolution2d_73 0.0358 ms 40.0% 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 2025-09-07T09:55:48.5953619Z triton_convolution2d_72 0.0543 ms 26.4% 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 2025-09-07T09:55:48.5955107Z triton_convolution2d_74 0.0563 ms 25.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:48.5956595Z triton_convolution2d_75 0.0563 ms 25.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:48.5958083Z triton_convolution2d_70 0.0696 ms 20.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:48.5959560Z triton_convolution2d_69 0.0717 ms 20.0% 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 2025-09-07T09:55:48.5961046Z triton_convolution2d_71 0.1157 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:48.5962228Z SingleProcess AUTOTUNE benchmarking takes 0.1571 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:55:48.7060982Z Autotune Choices Stats: 2025-09-07T09:55:48.7062676Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009216000325977802, "best_triton_pos": 1, "best_triton_time": 0.010239999741315842, "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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:55:48.7086158Z AUTOTUNE convolution(4x128x28x28, 256x128x1x1) 2025-09-07T09:55:48.7086553Z strides: [100352, 1, 3584, 128], [128, 1, 128, 128] 2025-09-07T09:55:48.7087157Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:48.7087463Z convolution 0.0092 ms 100.0% 2025-09-07T09:55:48.7088348Z triton_convolution2d_87 0.0102 ms 90.0% 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 2025-09-07T09:55:48.7089842Z triton_convolution2d_86 0.0123 ms 75.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:48.7091328Z triton_convolution2d_88 0.0123 ms 75.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:48.7093041Z triton_convolution2d_89 0.0123 ms 75.0% 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 2025-09-07T09:55:48.7094541Z triton_convolution2d_83 0.0133 ms 69.2% 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 2025-09-07T09:55:48.7096195Z triton_convolution2d_84 0.0143 ms 64.3% 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 2025-09-07T09:55:48.7097680Z triton_convolution2d_85 0.0195 ms 47.4% 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 2025-09-07T09:55:48.7098843Z SingleProcess AUTOTUNE benchmarking takes 0.1117 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:48.8997115Z Autotune Choices Stats: 2025-09-07T09:55:48.8998767Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 1, "best_triton_time": 0.06656000018119812, "best_triton_kernel": "triton_convolution2d_108", "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"} 2025-09-07T09:55:48.9023072Z AUTOTUNE convolution(4x256x14x14, 512x256x3x3) 2025-09-07T09:55:48.9023485Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T09:55:48.9023844Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:48.9024150Z convolution 0.0184 ms 100.0% 2025-09-07T09:55:48.9025096Z triton_convolution2d_108 0.0666 ms 27.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:48.9026607Z triton_convolution2d_107 0.1024 ms 18.0% 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 2025-09-07T09:55:48.9028122Z triton_convolution2d_109 0.1055 ms 17.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:48.9029622Z triton_convolution2d_110 0.1075 ms 17.1% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:48.9031110Z triton_convolution2d_104 0.1352 ms 13.6% 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 2025-09-07T09:55:48.9032598Z triton_convolution2d_105 0.1362 ms 13.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:48.9034336Z triton_convolution2d_106 0.1751 ms 10.5% 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 2025-09-07T09:55:48.9035506Z SingleProcess AUTOTUNE benchmarking takes 0.1908 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:49.0159058Z Autotune Choices Stats: 2025-09-07T09:55:49.0160694Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010239999741315842, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:55:49.0190365Z AUTOTUNE convolution(4x256x14x14, 512x256x1x1) 2025-09-07T09:55:49.0190793Z strides: [50176, 1, 3584, 256], [256, 1, 256, 256] 2025-09-07T09:55:49.0191158Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.0191769Z convolution 0.0102 ms 100.0% 2025-09-07T09:55:49.0192668Z triton_convolution2d_122 0.0133 ms 76.9% 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 2025-09-07T09:55:49.0194180Z triton_convolution2d_121 0.0164 ms 62.5% 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 2025-09-07T09:55:49.0195682Z triton_convolution2d_123 0.0174 ms 58.8% 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 2025-09-07T09:55:49.0197181Z triton_convolution2d_124 0.0174 ms 58.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:49.0198674Z triton_convolution2d_118 0.0195 ms 52.6% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:49.0200164Z triton_convolution2d_119 0.0205 ms 50.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:49.0201640Z triton_convolution2d_120 0.0246 ms 41.7% 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 2025-09-07T09:55:49.0202819Z SingleProcess AUTOTUNE benchmarking takes 0.1149 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:49.2814558Z Autotune Choices Stats: 2025-09-07T09:55:49.2815767Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_143", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:55:49.2841909Z AUTOTUNE addmm(4x1000, 4x512, 512x1000) 2025-09-07T09:55:49.2842264Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T09:55:49.2842619Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:49.2843435Z triton_mm_143 0.0092 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 2025-09-07T09:55:49.2844631Z triton_mm_142 0.0102 ms 90.0% 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 2025-09-07T09:55:49.2846046Z triton_mm_147 0.0102 ms 90.0% 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 2025-09-07T09:55:49.2847227Z triton_mm_140 0.0113 ms 81.8% 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 2025-09-07T09:55:49.2848405Z triton_mm_141 0.0113 ms 81.8% 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 2025-09-07T09:55:49.2849600Z triton_mm_146 0.0113 ms 81.8% 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 2025-09-07T09:55:49.2850784Z triton_mm_150 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:49.2852117Z triton_mm_151 0.0113 ms 81.8% 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 2025-09-07T09:55:49.2853538Z triton_mm_153 0.0113 ms 81.8% 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=4, num_warps=4 2025-09-07T09:55:49.2854705Z triton_mm_155 0.0113 ms 81.8% 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 2025-09-07T09:55:49.2855738Z SingleProcess AUTOTUNE benchmarking takes 0.2622 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:55:55.5828436Z Autotune Choices Stats: 2025-09-07T09:55:55.5829722Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_175", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:55:55.5857235Z AUTOTUNE mm(1000x4, 4x512) 2025-09-07T09:55:55.5857533Z strides: [1, 1000], [512, 1] 2025-09-07T09:55:55.5857816Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:55.5858602Z triton_mm_175 0.0072 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 2025-09-07T09:55:55.5859803Z triton_mm_173 0.0082 ms 87.5% 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 2025-09-07T09:55:55.5860992Z triton_mm_174 0.0082 ms 87.5% 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=2, num_warps=4 2025-09-07T09:55:55.5862188Z triton_mm_176 0.0082 ms 87.5% 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=8 2025-09-07T09:55:55.5863373Z triton_mm_177 0.0082 ms 87.5% 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 2025-09-07T09:55:55.5864558Z triton_mm_178 0.0082 ms 87.5% 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 2025-09-07T09:55:55.5865788Z triton_mm_179 0.0082 ms 87.5% 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 2025-09-07T09:55:55.5866970Z triton_mm_180 0.0082 ms 87.5% 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 2025-09-07T09:55:55.5868502Z triton_mm_181 0.0082 ms 87.5% 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=3, num_warps=4 2025-09-07T09:55:55.5869698Z triton_mm_182 0.0082 ms 87.5% 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 2025-09-07T09:55:55.5870724Z SingleProcess AUTOTUNE benchmarking takes 0.2112 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:55:56.3418602Z Autotune Choices Stats: 2025-09-07T09:55:56.3419838Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_160", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:55:56.3446532Z AUTOTUNE mm(4x1000, 1000x512) 2025-09-07T09:55:56.3446852Z strides: [1000, 1], [512, 1] 2025-09-07T09:55:56.3447153Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:56.3448309Z triton_mm_160 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:55:56.3449538Z triton_mm_164 0.0102 ms 100.0% 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 2025-09-07T09:55:56.3450295Z mm 0.0123 ms 83.3% 2025-09-07T09:55:56.3450996Z triton_mm_168 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:56.3452188Z triton_mm_158 0.0133 ms 76.9% 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 2025-09-07T09:55:56.3453635Z triton_mm_159 0.0133 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 2025-09-07T09:55:56.3454809Z triton_mm_172 0.0133 ms 76.9% 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 2025-09-07T09:55:56.3455996Z triton_mm_163 0.0143 ms 71.4% 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 2025-09-07T09:55:56.3457183Z triton_mm_157 0.0154 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:55:56.3458374Z triton_mm_167 0.0154 ms 66.7% 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 2025-09-07T09:55:56.3459409Z SingleProcess AUTOTUNE benchmarking takes 0.2413 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:56:00.8879737Z pass 2025-09-07T09:56:04.3311258Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:56:04.3312706Z import pynvml # type: ignore[import] 2025-09-07T09:56:07.0541253Z 2025-09-07T09:56:09.2223303Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:56:09.2223695Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:56:09.2224027Z cuda train resnet50 2025-09-07T09:56:45.0120766Z W0907 09:56:45.011000 35418 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:57:09.0044896Z pass 2025-09-07T09:57:13.6027701Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:57:13.6029128Z import pynvml # type: ignore[import] 2025-09-07T09:57:16.2622813Z 2025-09-07T09:57:18.6468750Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:57:18.6469385Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:57:18.6469966Z cuda train resnet50_quantized_qat 2025-09-07T09:57:18.6470615Z Traceback (most recent call last): 2025-09-07T09:57:18.6471610Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:57:18.6472711Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:57:18.6473929Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:57:18.6475106Z pred = mod(*cloned_inputs) 2025-09-07T09:57:18.6476699Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 837, in call_wrapped 2025-09-07T09:57:18.6477930Z return self._wrapped_call(self, *args, **kwargs) 2025-09-07T09:57:18.6479092Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 413, in __call__ 2025-09-07T09:57:18.6480161Z raise e 2025-09-07T09:57:18.6481064Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/graph_module.py", line 400, in __call__ 2025-09-07T09:57:18.6482395Z return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc] 2025-09-07T09:57:18.6483853Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:57:18.6485170Z return self._call_impl(*args, **kwargs) 2025-09-07T09:57:18.6486321Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:57:18.6487485Z return forward_call(*args, **kwargs) 2025-09-07T09:57:18.6488103Z File ".3", line 167, in forward 2025-09-07T09:57:18.6488973Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T09:57:18.6490466Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:57:18.6491723Z return self._call_impl(*args, **kwargs) 2025-09-07T09:57:18.6493207Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:57:18.6494381Z return forward_call(*args, **kwargs) 2025-09-07T09:57:18.6495606Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T09:57:18.6496929Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T09:57:18.6497679Z RuntimeError: expected scalar type Float but found Half 2025-09-07T09:57:18.6498186Z 2025-09-07T09:57:18.6498581Z The above exception was the direct cause of the following exception: 2025-09-07T09:57:18.6499198Z 2025-09-07T09:57:18.6499381Z Traceback (most recent call last): 2025-09-07T09:57:18.6500263Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:57:18.6501179Z ) = runner.load_model( 2025-09-07T09:57:18.6502084Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:57:18.6503164Z self.validate_model(model, example_inputs) 2025-09-07T09:57:18.6504210Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:57:18.6505386Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:57:18.6506370Z RuntimeError: Eager run failed 2025-09-07T09:57:18.6506712Z 2025-09-07T09:57:18.6506861Z eager_fail_to_run 2025-09-07T09:57:20.3236532Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:57:20.3238070Z import pynvml # type: ignore[import] 2025-09-07T09:57:23.0203941Z 2025-09-07T09:57:25.6552229Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:57:25.6552618Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:57:25.6552933Z cuda train resnext50_32x4d 2025-09-07T09:57:43.3899600Z Autotune Choices Stats: 2025-09-07T09:57:43.3900981Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "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", "best_time": 0.048128001391887665, "best_triton_pos": 0} 2025-09-07T09:57:43.3929143Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T09:57:43.3929518Z strides: [150528, 50176, 224, 1], [147, 49, 7, 1] 2025-09-07T09:57:43.3930270Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:43.3931184Z triton_convolution2d_5 0.0481 ms 100.0% 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 2025-09-07T09:57:43.3932677Z triton_convolution2d_1 0.0512 ms 94.0% 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 2025-09-07T09:57:43.3933804Z convolution 0.0645 ms 74.6% 2025-09-07T09:57:43.3934674Z triton_convolution2d_0 0.0717 ms 67.1% 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 2025-09-07T09:57:43.3936162Z triton_convolution2d_3 0.0727 ms 66.2% 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 2025-09-07T09:57:43.3937622Z triton_convolution2d_4 0.0809 ms 59.5% 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 2025-09-07T09:57:43.3939096Z triton_convolution2d_2 0.1157 ms 41.6% 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 2025-09-07T09:57:43.3940247Z SingleProcess AUTOTUNE benchmarking takes 0.1490 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T09:57:43.8828254Z Autotune Choices Stats: 2025-09-07T09:57:43.8829631Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_23", "best_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", "best_time": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T09:57:43.8857140Z AUTOTUNE convolution(4x64x56x56, 256x64x1x1) 2025-09-07T09:57:43.8857506Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:57:43.8857849Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:43.8858773Z triton_convolution2d_23 0.0143 ms 100.0% 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 2025-09-07T09:57:43.8860261Z triton_convolution2d_25 0.0143 ms 100.0% 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 2025-09-07T09:57:43.8862061Z triton_convolution2d_26 0.0143 ms 100.0% 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 2025-09-07T09:57:43.8863549Z triton_convolution2d_21 0.0154 ms 93.3% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:43.8865110Z triton_convolution2d_24 0.0154 ms 93.3% 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 2025-09-07T09:57:43.8866594Z triton_convolution2d_20 0.0164 ms 87.5% 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 2025-09-07T09:57:43.8868269Z triton_convolution2d_22 0.0195 ms 73.7% 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 2025-09-07T09:57:43.8869184Z convolution 0.0215 ms 66.7% 2025-09-07T09:57:43.8869462Z conv1x1_via_mm 0.0737 ms 19.4% 2025-09-07T09:57:43.8870035Z SingleProcess AUTOTUNE benchmarking takes 0.1486 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:57:44.4617171Z Autotune Choices Stats: 2025-09-07T09:57:44.4618530Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_39", "best_kernel_desc": "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", "best_time": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T09:57:44.4646491Z AUTOTUNE convolution(4x128x56x56, 256x128x1x1) 2025-09-07T09:57:44.4646874Z strides: [401408, 3136, 56, 1], [128, 1, 1, 1] 2025-09-07T09:57:44.4647204Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:44.4648283Z triton_convolution2d_39 0.0164 ms 100.0% 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 2025-09-07T09:57:44.4649789Z triton_convolution2d_37 0.0174 ms 94.1% 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 2025-09-07T09:57:44.4651282Z triton_convolution2d_40 0.0174 ms 94.1% 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 2025-09-07T09:57:44.4652759Z triton_convolution2d_38 0.0184 ms 88.9% 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 2025-09-07T09:57:44.4654506Z triton_convolution2d_35 0.0195 ms 84.2% 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 2025-09-07T09:57:44.4655992Z triton_convolution2d_34 0.0205 ms 80.0% 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 2025-09-07T09:57:44.4657475Z triton_convolution2d_36 0.0246 ms 66.7% 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 2025-09-07T09:57:44.4658373Z convolution 0.0307 ms 53.3% 2025-09-07T09:57:44.4658659Z conv1x1_via_mm 0.0819 ms 20.0% 2025-09-07T09:57:44.4664704Z SingleProcess AUTOTUNE benchmarking takes 0.1515 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:44.9509668Z Autotune Choices Stats: 2025-09-07T09:57:44.9511051Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_58", "best_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", "best_time": 0.023552000522613525, "best_triton_pos": 0} 2025-09-07T09:57:44.9539257Z AUTOTUNE convolution(4x256x56x56, 256x256x1x1) 2025-09-07T09:57:44.9539642Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:57:44.9539984Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:44.9540900Z triton_convolution2d_58 0.0236 ms 100.0% 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 2025-09-07T09:57:44.9542431Z triton_convolution2d_61 0.0236 ms 100.0% 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 2025-09-07T09:57:44.9544253Z triton_convolution2d_56 0.0266 ms 88.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:44.9545829Z triton_convolution2d_59 0.0266 ms 88.5% 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 2025-09-07T09:57:44.9547312Z triton_convolution2d_55 0.0276 ms 85.2% 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 2025-09-07T09:57:44.9548790Z triton_convolution2d_60 0.0317 ms 74.2% 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 2025-09-07T09:57:44.9550281Z triton_convolution2d_57 0.0389 ms 60.5% 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 2025-09-07T09:57:44.9551188Z convolution 0.0430 ms 54.8% 2025-09-07T09:57:44.9551477Z conv1x1_via_mm 0.1044 ms 22.5% 2025-09-07T09:57:44.9552052Z SingleProcess AUTOTUNE benchmarking takes 0.1585 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:57:46.4882029Z Autotune Choices Stats: 2025-09-07T09:57:46.4883407Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_10", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T09:57:46.4911831Z AUTOTUNE convolution(4x64x56x56, 128x64x1x1) 2025-09-07T09:57:46.4912198Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:57:46.4912559Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:46.4913455Z triton_convolution2d_10 0.0113 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 2025-09-07T09:57:46.4914947Z triton_convolution2d_11 0.0113 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 2025-09-07T09:57:46.4915866Z convolution 0.0123 ms 91.7% 2025-09-07T09:57:46.4916731Z triton_convolution2d_6 0.0123 ms 91.7% 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 2025-09-07T09:57:46.4918559Z triton_convolution2d_9 0.0123 ms 91.7% 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 2025-09-07T09:57:46.4920039Z triton_convolution2d_12 0.0123 ms 91.7% 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 2025-09-07T09:57:46.4921506Z triton_convolution2d_7 0.0133 ms 84.6% 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 2025-09-07T09:57:46.4922982Z triton_convolution2d_8 0.0143 ms 78.6% 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 2025-09-07T09:57:46.4923894Z conv1x1_via_mm 0.0512 ms 22.0% 2025-09-07T09:57:46.4924463Z SingleProcess AUTOTUNE benchmarking takes 0.1442 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:46.9517428Z Autotune Choices Stats: 2025-09-07T09:57:46.9518972Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_31", "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": 0.01945599913597107, "best_triton_pos": 0} 2025-09-07T09:57:46.9541821Z AUTOTUNE convolution(4x256x56x56, 128x256x1x1) 2025-09-07T09:57:46.9542205Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:57:46.9542555Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:46.9543469Z triton_convolution2d_31 0.0195 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 2025-09-07T09:57:46.9545069Z triton_convolution2d_32 0.0195 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 2025-09-07T09:57:46.9546570Z triton_convolution2d_30 0.0205 ms 95.0% 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 2025-09-07T09:57:46.9548062Z triton_convolution2d_33 0.0215 ms 90.5% 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 2025-09-07T09:57:46.9549550Z triton_convolution2d_27 0.0236 ms 82.6% 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 2025-09-07T09:57:46.9551040Z triton_convolution2d_28 0.0256 ms 76.0% 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 2025-09-07T09:57:46.9552521Z triton_convolution2d_29 0.0328 ms 59.4% 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=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:57:46.9553428Z convolution 0.0358 ms 54.3% 2025-09-07T09:57:46.9553703Z conv1x1_via_mm 0.0829 ms 23.5% 2025-09-07T09:57:46.9554270Z SingleProcess AUTOTUNE benchmarking takes 0.1550 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:47.1419573Z Autotune Choices Stats: 2025-09-07T09:57:47.1420936Z {"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": 0.020479999482631683, "best_triton_pos": 0} 2025-09-07T09:57:47.1450537Z AUTOTUNE convolution(4x256x56x56, 512x256x1x1) 2025-09-07T09:57:47.1450956Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:57:47.1451289Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:47.1452197Z triton_convolution2d_73 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 2025-09-07T09:57:47.1453919Z triton_convolution2d_72 0.0215 ms 95.2% 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 2025-09-07T09:57:47.1455421Z triton_convolution2d_74 0.0215 ms 95.2% 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 2025-09-07T09:57:47.1457150Z triton_convolution2d_75 0.0276 ms 74.1% 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 2025-09-07T09:57:47.1458637Z triton_convolution2d_69 0.0287 ms 71.4% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:47.1460119Z triton_convolution2d_70 0.0307 ms 66.7% 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 2025-09-07T09:57:47.1461017Z convolution 0.0358 ms 57.1% 2025-09-07T09:57:47.1461898Z triton_convolution2d_71 0.0881 ms 23.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:57:47.1463080Z SingleProcess AUTOTUNE benchmarking takes 0.1299 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:57:47.7231595Z Autotune Choices Stats: 2025-09-07T09:57:47.7232955Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_87", "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": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T09:57:47.7262465Z AUTOTUNE convolution(4x256x28x28, 512x256x1x1) 2025-09-07T09:57:47.7262842Z strides: [200704, 784, 28, 1], [256, 1, 1, 1] 2025-09-07T09:57:47.7263209Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:47.7264113Z triton_convolution2d_87 0.0174 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 2025-09-07T09:57:47.7265692Z triton_convolution2d_86 0.0205 ms 85.0% 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 2025-09-07T09:57:47.7267176Z triton_convolution2d_88 0.0205 ms 85.0% 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 2025-09-07T09:57:47.7268654Z triton_convolution2d_89 0.0205 ms 85.0% 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 2025-09-07T09:57:47.7270446Z triton_convolution2d_84 0.0236 ms 73.9% 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 2025-09-07T09:57:47.7271943Z triton_convolution2d_83 0.0256 ms 68.0% 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 2025-09-07T09:57:47.7272848Z convolution 0.0276 ms 63.0% 2025-09-07T09:57:47.7273726Z triton_convolution2d_85 0.0440 ms 39.5% 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 2025-09-07T09:57:47.7274635Z conv1x1_via_mm 0.0614 ms 28.3% 2025-09-07T09:57:47.7275186Z SingleProcess AUTOTUNE benchmarking takes 0.1570 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:48.2491670Z Autotune Choices Stats: 2025-09-07T09:57:48.2493917Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.025599999353289604, "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"} 2025-09-07T09:57:48.2522403Z AUTOTUNE convolution(4x512x28x28, 512x512x1x1) 2025-09-07T09:57:48.2522824Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:57:48.2523173Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:48.2523493Z convolution 0.0215 ms 100.0% 2025-09-07T09:57:48.2524374Z triton_convolution2d_122 0.0256 ms 84.0% 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 2025-09-07T09:57:48.2525884Z triton_convolution2d_121 0.0317 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 2025-09-07T09:57:48.2527367Z triton_convolution2d_124 0.0317 ms 67.7% 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 2025-09-07T09:57:48.2528851Z triton_convolution2d_123 0.0328 ms 65.6% 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 2025-09-07T09:57:48.2530335Z triton_convolution2d_119 0.0379 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 2025-09-07T09:57:48.2531817Z triton_convolution2d_118 0.0420 ms 51.2% 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 2025-09-07T09:57:48.2533439Z triton_convolution2d_120 0.0788 ms 27.3% 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 2025-09-07T09:57:48.2534352Z conv1x1_via_mm 0.0809 ms 26.6% 2025-09-07T09:57:48.2534920Z SingleProcess AUTOTUNE benchmarking takes 0.1667 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:57:48.8581328Z Autotune Choices Stats: 2025-09-07T09:57:48.8583019Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "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"} 2025-09-07T09:57:48.8613729Z AUTOTUNE convolution(4x512x28x28, 256x512x1x1) 2025-09-07T09:57:48.8614134Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:57:48.8614500Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:48.8614805Z convolution 0.0174 ms 100.0% 2025-09-07T09:57:48.8615687Z triton_convolution2d_80 0.0225 ms 77.3% 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 2025-09-07T09:57:48.8617183Z triton_convolution2d_79 0.0307 ms 56.7% 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 2025-09-07T09:57:48.8618676Z triton_convolution2d_82 0.0307 ms 56.7% 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 2025-09-07T09:57:48.8620416Z triton_convolution2d_81 0.0328 ms 53.1% 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 2025-09-07T09:57:48.8621907Z triton_convolution2d_77 0.0379 ms 45.9% 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 2025-09-07T09:57:48.8623393Z triton_convolution2d_76 0.0420 ms 41.5% 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 2025-09-07T09:57:48.8624956Z triton_convolution2d_78 0.0532 ms 32.7% 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 2025-09-07T09:57:48.8625868Z conv1x1_via_mm 0.0645 ms 27.0% 2025-09-07T09:57:48.8626438Z SingleProcess AUTOTUNE benchmarking takes 0.1662 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:49.3438115Z Autotune Choices Stats: 2025-09-07T09:57:49.3439467Z {"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": 0.025599999353289604, "best_triton_pos": 0} 2025-09-07T09:57:49.3468882Z AUTOTUNE convolution(4x512x28x28, 1024x512x1x1) 2025-09-07T09:57:49.3469319Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:57:49.3469665Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:49.3470579Z triton_convolution2d_136 0.0256 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 2025-09-07T09:57:49.3471517Z convolution 0.0297 ms 86.2% 2025-09-07T09:57:49.3472393Z triton_convolution2d_137 0.0317 ms 80.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:57:49.3473883Z triton_convolution2d_135 0.0338 ms 75.8% 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 2025-09-07T09:57:49.3475368Z triton_convolution2d_132 0.0440 ms 58.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:49.3477218Z triton_convolution2d_138 0.0451 ms 56.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:57:49.3478710Z triton_convolution2d_133 0.0502 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:49.3480198Z triton_convolution2d_134 0.0881 ms 29.1% 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 2025-09-07T09:57:49.3481372Z SingleProcess AUTOTUNE benchmarking takes 0.1359 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:57:49.9386477Z Autotune Choices Stats: 2025-09-07T09:57:49.9387836Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_150", "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": 0.02252800017595291, "best_triton_pos": 0} 2025-09-07T09:57:49.9418382Z AUTOTUNE convolution(4x512x14x14, 1024x512x1x1) 2025-09-07T09:57:49.9418774Z strides: [100352, 196, 14, 1], [512, 1, 1, 1] 2025-09-07T09:57:49.9419121Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:49.9420021Z triton_convolution2d_150 0.0225 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 2025-09-07T09:57:49.9420927Z convolution 0.0246 ms 91.7% 2025-09-07T09:57:49.9421812Z triton_convolution2d_151 0.0287 ms 78.6% 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 2025-09-07T09:57:49.9423324Z triton_convolution2d_149 0.0317 ms 71.0% 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 2025-09-07T09:57:49.9424899Z triton_convolution2d_152 0.0317 ms 71.0% 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 2025-09-07T09:57:49.9426392Z triton_convolution2d_146 0.0420 ms 53.7% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:49.9427890Z triton_convolution2d_147 0.0420 ms 53.7% 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 2025-09-07T09:57:49.9429376Z triton_convolution2d_148 0.0522 ms 43.1% 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 2025-09-07T09:57:49.9430289Z conv1x1_via_mm 0.0573 ms 39.3% 2025-09-07T09:57:49.9430863Z SingleProcess AUTOTUNE benchmarking takes 0.1687 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:50.5328195Z Autotune Choices Stats: 2025-09-07T09:57:50.5329884Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02969600073993206, "best_triton_pos": 1, "best_triton_time": 0.03788800165057182, "best_triton_kernel": "triton_convolution2d_213", "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"} 2025-09-07T09:57:50.5360774Z AUTOTUNE convolution(4x1024x14x14, 1024x1024x1x1) 2025-09-07T09:57:50.5361593Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:57:50.5361943Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:50.5362262Z convolution 0.0297 ms 100.0% 2025-09-07T09:57:50.5363172Z triton_convolution2d_213 0.0379 ms 78.4% 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 2025-09-07T09:57:50.5364667Z triton_convolution2d_214 0.0471 ms 63.0% 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 2025-09-07T09:57:50.5366152Z triton_convolution2d_212 0.0522 ms 56.9% 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 2025-09-07T09:57:50.5367650Z triton_convolution2d_215 0.0543 ms 54.7% 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 2025-09-07T09:57:50.5369315Z triton_convolution2d_209 0.0737 ms 40.3% 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 2025-09-07T09:57:50.5370809Z triton_convolution2d_210 0.0768 ms 38.7% 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 2025-09-07T09:57:50.5371717Z conv1x1_via_mm 0.0778 ms 38.2% 2025-09-07T09:57:50.5372609Z triton_convolution2d_211 0.0952 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 2025-09-07T09:57:50.5374023Z SingleProcess AUTOTUNE benchmarking takes 0.1863 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:51.0665952Z Autotune Choices Stats: 2025-09-07T09:57:51.0667673Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "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"} 2025-09-07T09:57:51.0699000Z AUTOTUNE convolution(4x1024x14x14, 512x1024x1x1) 2025-09-07T09:57:51.0699387Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:57:51.0699733Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:51.0700039Z convolution 0.0266 ms 100.0% 2025-09-07T09:57:51.0700928Z triton_convolution2d_143 0.0348 ms 76.5% 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 2025-09-07T09:57:51.0702444Z triton_convolution2d_144 0.0481 ms 55.3% 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 2025-09-07T09:57:51.0703937Z triton_convolution2d_142 0.0532 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 2025-09-07T09:57:51.0705525Z triton_convolution2d_145 0.0543 ms 49.1% 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 2025-09-07T09:57:51.0706434Z conv1x1_via_mm 0.0563 ms 47.3% 2025-09-07T09:57:51.0707308Z triton_convolution2d_139 0.0748 ms 35.6% 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 2025-09-07T09:57:51.0709147Z triton_convolution2d_140 0.0768 ms 34.7% 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 2025-09-07T09:57:51.0710648Z triton_convolution2d_141 0.0932 ms 28.6% 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 2025-09-07T09:57:51.0711837Z SingleProcess AUTOTUNE benchmarking takes 0.1850 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:51.5616065Z Autotune Choices Stats: 2025-09-07T09:57:51.5617763Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02969600073993206, "best_triton_pos": 1, "best_triton_time": 0.04198399931192398, "best_triton_kernel": "triton_convolution2d_227", "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"} 2025-09-07T09:57:51.5648685Z AUTOTUNE convolution(4x1024x14x14, 2048x1024x1x1) 2025-09-07T09:57:51.5649075Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:57:51.5649409Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:51.5649725Z convolution 0.0297 ms 100.0% 2025-09-07T09:57:51.5650605Z triton_convolution2d_227 0.0420 ms 70.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:51.5652109Z triton_convolution2d_228 0.0532 ms 55.8% 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 2025-09-07T09:57:51.5653830Z triton_convolution2d_226 0.0584 ms 50.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:57:51.5655324Z triton_convolution2d_223 0.0748 ms 39.7% 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 2025-09-07T09:57:51.5656800Z triton_convolution2d_229 0.0758 ms 39.2% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:57:51.5658288Z triton_convolution2d_224 0.0911 ms 32.6% 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 2025-09-07T09:57:51.5659781Z triton_convolution2d_225 0.2109 ms 14.1% 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 2025-09-07T09:57:51.5660959Z SingleProcess AUTOTUNE benchmarking takes 0.1659 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:57:52.1422338Z Autotune Choices Stats: 2025-09-07T09:57:52.1424026Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.03788800165057182, "best_triton_kernel": "triton_convolution2d_241", "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"} 2025-09-07T09:57:52.1454864Z AUTOTUNE convolution(4x1024x7x7, 2048x1024x1x1) 2025-09-07T09:57:52.1455579Z strides: [50176, 49, 7, 1], [1024, 1, 1, 1] 2025-09-07T09:57:52.1455918Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:52.1456240Z convolution 0.0266 ms 100.0% 2025-09-07T09:57:52.1457134Z triton_convolution2d_241 0.0379 ms 70.3% 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 2025-09-07T09:57:52.1458632Z triton_convolution2d_242 0.0502 ms 53.1% 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 2025-09-07T09:57:52.1460127Z triton_convolution2d_240 0.0522 ms 51.0% 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 2025-09-07T09:57:52.1461605Z triton_convolution2d_243 0.0645 ms 41.3% 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 2025-09-07T09:57:52.1462514Z conv1x1_via_mm 0.0655 ms 40.6% 2025-09-07T09:57:52.1463583Z triton_convolution2d_237 0.0707 ms 37.7% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:52.1465151Z triton_convolution2d_239 0.0717 ms 37.1% 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 2025-09-07T09:57:52.1466636Z triton_convolution2d_238 0.0850 ms 31.3% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:52.1467809Z SingleProcess AUTOTUNE benchmarking takes 0.1835 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:57:52.6697155Z Autotune Choices Stats: 2025-09-07T09:57:52.6698895Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027648000046610832, "best_triton_pos": 2, "best_triton_time": 0.06348799914121628, "best_triton_kernel": "triton_convolution2d_234", "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"} 2025-09-07T09:57:52.6729578Z AUTOTUNE convolution(4x2048x7x7, 1024x2048x1x1) 2025-09-07T09:57:52.6729962Z strides: [100352, 49, 7, 1], [2048, 1, 1, 1] 2025-09-07T09:57:52.6730305Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:52.6730613Z convolution 0.0276 ms 100.0% 2025-09-07T09:57:52.6730915Z conv1x1_via_mm 0.0635 ms 43.5% 2025-09-07T09:57:52.6731809Z triton_convolution2d_234 0.0635 ms 43.5% 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 2025-09-07T09:57:52.6733557Z triton_convolution2d_235 0.0901 ms 30.7% 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 2025-09-07T09:57:52.6735064Z triton_convolution2d_233 0.0942 ms 29.3% 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 2025-09-07T09:57:52.6736557Z triton_convolution2d_236 0.1198 ms 23.1% 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 2025-09-07T09:57:52.6738041Z triton_convolution2d_232 0.1300 ms 21.3% 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 2025-09-07T09:57:52.6739861Z triton_convolution2d_230 0.1321 ms 20.9% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:57:52.6741348Z triton_convolution2d_231 0.1505 ms 18.4% 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 2025-09-07T09:57:52.6742526Z SingleProcess AUTOTUNE benchmarking takes 0.2219 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:58:09.4168884Z W0907 09:58:09.416000 35586 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:58:33.3357678Z pass 2025-09-07T09:58:37.9091097Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:58:37.9093207Z import pynvml # type: ignore[import] 2025-09-07T09:58:40.6827890Z 2025-09-07T09:58:48.5461701Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:58:48.5462071Z loading model: 0it [00:07, ?it/s] 2025-09-07T09:58:48.5462394Z cuda train sam 2025-09-07T09:58:48.5473458Z Traceback (most recent call last): 2025-09-07T09:58:48.5474110Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:58:48.5474719Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:58:48.5475377Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 493, in forward_and_backward_pass 2025-09-07T09:58:48.5476049Z self.grad_scaler.scale(loss).backward() 2025-09-07T09:58:48.5476650Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py", line 625, in backward 2025-09-07T09:58:48.5484253Z torch.autograd.backward( 2025-09-07T09:58:48.5484886Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/__init__.py", line 354, in backward 2025-09-07T09:58:48.5485514Z _engine_run_backward( 2025-09-07T09:58:48.5486119Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward 2025-09-07T09:58:48.5487034Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-09-07T09:58:48.5487780Z RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn 2025-09-07T09:58:48.5488188Z 2025-09-07T09:58:48.5488408Z The above exception was the direct cause of the following exception: 2025-09-07T09:58:48.5488742Z 2025-09-07T09:58:48.5488866Z Traceback (most recent call last): 2025-09-07T09:58:48.5489364Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:58:48.5489873Z ) = runner.load_model( 2025-09-07T09:58:48.5490385Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:58:48.5490985Z self.validate_model(model, example_inputs) 2025-09-07T09:58:48.5491569Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:58:48.5492158Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:58:48.5492517Z RuntimeError: Eager run failed 2025-09-07T09:58:48.5492706Z 2025-09-07T09:58:48.5493091Z eager_fail_to_run 2025-09-07T09:58:50.3598583Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:58:50.3601304Z import pynvml # type: ignore[import] 2025-09-07T09:58:53.1023045Z 2025-09-07T09:58:54.7194082Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:58:54.7194463Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:58:54.7194791Z cuda train shufflenet_v2_x1_0 2025-09-07T09:59:14.0348884Z Autotune Choices Stats: 2025-09-07T09:59:14.0350106Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_28", "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=2, num_warps=4", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:59:14.0382387Z AUTOTUNE mm(12544x24, 24x58) 2025-09-07T09:59:14.0382703Z strides: [24, 1], [1, 24] 2025-09-07T09:59:14.0382993Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:14.0383761Z triton_mm_28 0.0082 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=2, num_warps=4 2025-09-07T09:59:14.0385063Z triton_mm_31 0.0082 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 2025-09-07T09:59:14.0386642Z triton_mm_33 0.0082 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=4 2025-09-07T09:59:14.0387840Z triton_mm_22 0.0092 ms 88.9% 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 2025-09-07T09:59:14.0389014Z triton_mm_23 0.0092 ms 88.9% 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=2, num_warps=4 2025-09-07T09:59:14.0390196Z triton_mm_24 0.0092 ms 88.9% 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 2025-09-07T09:59:14.0391367Z triton_mm_25 0.0092 ms 88.9% 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 2025-09-07T09:59:14.0392544Z triton_mm_26 0.0092 ms 88.9% 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=4 2025-09-07T09:59:14.0393725Z triton_mm_29 0.0092 ms 88.9% 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 2025-09-07T09:59:14.0394898Z triton_mm_30 0.0092 ms 88.9% 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=5, num_warps=4 2025-09-07T09:59:14.0395919Z SingleProcess AUTOTUNE benchmarking takes 0.2263 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:59:14.6220335Z Autotune Choices Stats: 2025-09-07T09:59:14.6221601Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_190", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:59:14.6253562Z AUTOTUNE mm(3136x116, 116x116) 2025-09-07T09:59:14.6253875Z strides: [116, 1], [1, 116] 2025-09-07T09:59:14.6254186Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:14.6254958Z triton_mm_190 0.0092 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 2025-09-07T09:59:14.6256186Z triton_mm_183 0.0102 ms 90.0% 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=2, num_warps=4 2025-09-07T09:59:14.6257738Z triton_mm_186 0.0102 ms 90.0% 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 2025-09-07T09:59:14.6258937Z triton_mm_188 0.0102 ms 90.0% 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=2, num_warps=4 2025-09-07T09:59:14.6260127Z triton_mm_189 0.0102 ms 90.0% 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 2025-09-07T09:59:14.6261322Z triton_mm_191 0.0102 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=3, num_warps=4 2025-09-07T09:59:14.6262517Z triton_mm_192 0.0102 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 2025-09-07T09:59:14.6263701Z triton_mm_193 0.0102 ms 90.0% 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 2025-09-07T09:59:14.6265164Z triton_mm_194 0.0102 ms 90.0% 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 2025-09-07T09:59:14.6265928Z mm 0.0113 ms 81.8% 2025-09-07T09:59:14.6266463Z SingleProcess AUTOTUNE benchmarking takes 0.2480 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:59:15.1720826Z Autotune Choices Stats: 2025-09-07T09:59:15.1722038Z {"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": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:59:15.1755402Z AUTOTUNE mm(3136x58, 58x58) 2025-09-07T09:59:15.1755702Z strides: [58, 1], [1, 58] 2025-09-07T09:59:15.1755992Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:15.1756774Z triton_mm_57 0.0082 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 2025-09-07T09:59:15.1757975Z triton_mm_58 0.0082 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 2025-09-07T09:59:15.1759147Z triton_mm_59 0.0082 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 2025-09-07T09:59:15.1760323Z triton_mm_60 0.0082 ms 100.0% 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 2025-09-07T09:59:15.1761512Z triton_mm_62 0.0082 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=2, num_warps=4 2025-09-07T09:59:15.1762692Z triton_mm_63 0.0082 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 2025-09-07T09:59:15.1763867Z triton_mm_64 0.0082 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=5, num_warps=4 2025-09-07T09:59:15.1765050Z triton_mm_65 0.0082 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 2025-09-07T09:59:15.1766231Z triton_mm_67 0.0082 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 2025-09-07T09:59:15.1767724Z triton_mm_68 0.0082 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=4, num_warps=4 2025-09-07T09:59:15.1768771Z SingleProcess AUTOTUNE benchmarking takes 0.2461 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:59:15.7792621Z Autotune Choices Stats: 2025-09-07T09:59:15.7793843Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_490", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:59:15.7826800Z AUTOTUNE mm(784x232, 232x232) 2025-09-07T09:59:15.7827238Z strides: [232, 1], [1, 232] 2025-09-07T09:59:15.7827627Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:15.7828659Z triton_mm_490 0.0102 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 2025-09-07T09:59:15.7830756Z triton_mm_491 0.0102 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 2025-09-07T09:59:15.7832396Z triton_mm_492 0.0102 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 2025-09-07T09:59:15.7833981Z triton_mm_495 0.0102 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 2025-09-07T09:59:15.7835163Z triton_mm_496 0.0102 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 2025-09-07T09:59:15.7835925Z mm 0.0113 ms 90.9% 2025-09-07T09:59:15.7836614Z triton_mm_489 0.0113 ms 90.9% 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 2025-09-07T09:59:15.7837818Z triton_mm_497 0.0113 ms 90.9% 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=3, num_warps=4 2025-09-07T09:59:15.7839007Z triton_mm_498 0.0113 ms 90.9% 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 2025-09-07T09:59:15.7840198Z triton_mm_499 0.0113 ms 90.9% 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 2025-09-07T09:59:15.7841231Z SingleProcess AUTOTUNE benchmarking takes 0.2487 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:59:16.3247882Z Autotune Choices Stats: 2025-09-07T09:59:16.3249118Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_219", "best_kernel_desc": "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", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:59:16.3282884Z AUTOTUNE mm(784x116, 116x116) 2025-09-07T09:59:16.3283193Z strides: [116, 1], [1, 116] 2025-09-07T09:59:16.3283483Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:16.3284244Z triton_mm_219 0.0082 ms 100.0% 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=2, num_warps=4 2025-09-07T09:59:16.3285454Z triton_mm_220 0.0082 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 2025-09-07T09:59:16.3286937Z triton_mm_221 0.0082 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 2025-09-07T09:59:16.3288144Z triton_mm_222 0.0082 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 2025-09-07T09:59:16.3289345Z triton_mm_225 0.0082 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 2025-09-07T09:59:16.3290535Z triton_mm_224 0.0092 ms 88.9% 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 2025-09-07T09:59:16.3291710Z triton_mm_226 0.0092 ms 88.9% 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 2025-09-07T09:59:16.3293168Z triton_mm_227 0.0092 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=3, num_warps=4 2025-09-07T09:59:16.3294540Z triton_mm_229 0.0092 ms 88.9% 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 2025-09-07T09:59:16.3295742Z triton_mm_228 0.0102 ms 80.0% 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 2025-09-07T09:59:16.3296776Z SingleProcess AUTOTUNE benchmarking takes 0.2514 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:59:17.0297693Z Autotune Choices Stats: 2025-09-07T09:59:17.0299234Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.009216000325977802, "best_triton_pos": 1, "best_triton_time": 0.009216000325977802, "best_triton_kernel": "triton_mm_525", "best_triton_kernel_desc": "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"} 2025-09-07T09:59:17.0331181Z AUTOTUNE mm(196x232, 232x232) 2025-09-07T09:59:17.0331509Z strides: [232, 1], [1, 232] 2025-09-07T09:59:17.0331800Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:17.0332094Z mm 0.0092 ms 100.0% 2025-09-07T09:59:17.0333087Z triton_mm_525 0.0092 ms 100.0% 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=2, num_warps=4 2025-09-07T09:59:17.0334319Z triton_mm_526 0.0092 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 2025-09-07T09:59:17.0335514Z triton_mm_527 0.0092 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 2025-09-07T09:59:17.0336729Z triton_mm_528 0.0092 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 2025-09-07T09:59:17.0337931Z triton_mm_531 0.0092 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 2025-09-07T09:59:17.0339117Z triton_mm_532 0.0102 ms 90.0% 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 2025-09-07T09:59:17.0340315Z triton_mm_535 0.0102 ms 90.0% 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 2025-09-07T09:59:17.0341504Z triton_mm_533 0.0113 ms 81.8% 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 2025-09-07T09:59:17.0343057Z triton_mm_534 0.0113 ms 81.8% 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 2025-09-07T09:59:17.0344095Z SingleProcess AUTOTUNE benchmarking takes 0.2610 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:59:17.8370221Z Autotune Choices Stats: 2025-09-07T09:59:17.8371949Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_convolution2d_2", "best_triton_kernel_desc": "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"} 2025-09-07T09:59:17.8407551Z AUTOTUNE convolution(4x3x224x224, 24x3x3x3) 2025-09-07T09:59:17.8407943Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T09:59:17.8408284Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:17.8408597Z convolution 0.0164 ms 100.0% 2025-09-07T09:59:17.8409868Z triton_convolution2d_2 0.0215 ms 76.2% 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 2025-09-07T09:59:17.8411361Z triton_convolution2d_4 0.0215 ms 76.2% 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 2025-09-07T09:59:17.8412915Z triton_convolution2d_0 0.0256 ms 64.0% 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=4 2025-09-07T09:59:17.8414392Z triton_convolution2d_3 0.0256 ms 64.0% 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 2025-09-07T09:59:17.8415898Z triton_convolution2d_1 0.0266 ms 61.5% 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 2025-09-07T09:59:17.8417378Z triton_convolution2d_5 0.0287 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:17.8418547Z SingleProcess AUTOTUNE benchmarking takes 0.1160 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:59:18.0619803Z Autotune Choices Stats: 2025-09-07T09:59:18.0621022Z {"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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:59:18.0656745Z AUTOTUNE mm(3136x24, 24x58) 2025-09-07T09:59:18.0657053Z strides: [24, 1], [1, 24] 2025-09-07T09:59:18.0657384Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:18.0658130Z triton_mm_7 0.0072 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 2025-09-07T09:59:18.0659323Z triton_mm_8 0.0072 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 2025-09-07T09:59:18.0660515Z triton_mm_9 0.0072 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 2025-09-07T09:59:18.0661702Z triton_mm_10 0.0072 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 2025-09-07T09:59:18.0663234Z triton_mm_12 0.0072 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=2, num_warps=4 2025-09-07T09:59:18.0664423Z triton_mm_13 0.0072 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=8 2025-09-07T09:59:18.0665690Z triton_mm_14 0.0072 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=5, num_warps=4 2025-09-07T09:59:18.0666872Z triton_mm_15 0.0072 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 2025-09-07T09:59:18.0668070Z triton_mm_16 0.0072 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 2025-09-07T09:59:18.0669408Z triton_mm_17 0.0072 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=4 2025-09-07T09:59:18.0670440Z SingleProcess AUTOTUNE benchmarking takes 0.2238 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:59:18.3458518Z Autotune Choices Stats: 2025-09-07T09:59:18.3459986Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.011264000087976456, "best_triton_pos": 1, "best_triton_time": 0.011264000087976456, "best_triton_kernel": "triton_mm_640", "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"} 2025-09-07T09:59:18.3497248Z AUTOTUNE mm(196x464, 464x1024) 2025-09-07T09:59:18.3497556Z strides: [464, 1], [1, 464] 2025-09-07T09:59:18.3497839Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:18.3498148Z mm 0.0113 ms 100.0% 2025-09-07T09:59:18.3498877Z triton_mm_640 0.0113 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 2025-09-07T09:59:18.3500083Z triton_mm_639 0.0123 ms 91.7% 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 2025-09-07T09:59:18.3501286Z triton_mm_633 0.0133 ms 84.6% 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 2025-09-07T09:59:18.3502460Z triton_mm_634 0.0133 ms 84.6% 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 2025-09-07T09:59:18.3503660Z triton_mm_642 0.0133 ms 84.6% 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 2025-09-07T09:59:18.3504911Z triton_mm_643 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:18.3506106Z triton_mm_645 0.0133 ms 84.6% 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 2025-09-07T09:59:18.3507296Z triton_mm_635 0.0143 ms 78.6% 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 2025-09-07T09:59:18.3508628Z triton_mm_636 0.0143 ms 78.6% 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 2025-09-07T09:59:18.3509911Z SingleProcess AUTOTUNE benchmarking takes 0.2622 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:59:18.6304284Z Autotune Choices Stats: 2025-09-07T09:59:18.6305543Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_654", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T09:59:18.6343478Z AUTOTUNE addmm(4x1000, 4x1024, 1024x1000) 2025-09-07T09:59:18.6343841Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T09:59:18.6344204Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:59:18.6345099Z triton_mm_654 0.0113 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 2025-09-07T09:59:18.6346312Z triton_mm_658 0.0113 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 2025-09-07T09:59:18.6347743Z triton_mm_662 0.0123 ms 91.7% 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 2025-09-07T09:59:18.6348936Z triton_mm_666 0.0133 ms 84.6% 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 2025-09-07T09:59:18.6349688Z bias_addmm 0.0143 ms 78.6% 2025-09-07T09:59:18.6350409Z triton_mm_652 0.0143 ms 78.6% 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 2025-09-07T09:59:18.6351588Z triton_mm_653 0.0143 ms 78.6% 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 2025-09-07T09:59:18.6352756Z triton_mm_657 0.0143 ms 78.6% 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 2025-09-07T09:59:18.6353945Z triton_mm_651 0.0154 ms 73.3% 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 2025-09-07T09:59:18.6355138Z triton_mm_661 0.0154 ms 73.3% 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 2025-09-07T09:59:18.6356162Z SingleProcess AUTOTUNE benchmarking takes 0.2834 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:59:34.2126785Z Autotune Choices Stats: 2025-09-07T09:59:34.2128017Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_684", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:59:34.2164930Z AUTOTUNE mm(1000x4, 4x1024) 2025-09-07T09:59:34.2165252Z strides: [1, 1000], [1024, 1] 2025-09-07T09:59:34.2165562Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:34.2166314Z triton_mm_684 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:59:34.2167510Z triton_mm_685 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:59:34.2168708Z triton_mm_686 0.0082 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 2025-09-07T09:59:34.2170231Z triton_mm_687 0.0082 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=8 2025-09-07T09:59:34.2171434Z triton_mm_688 0.0082 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 2025-09-07T09:59:34.2172620Z triton_mm_689 0.0082 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 2025-09-07T09:59:34.2174047Z triton_mm_690 0.0082 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 2025-09-07T09:59:34.2175235Z triton_mm_691 0.0082 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 2025-09-07T09:59:34.2176423Z triton_mm_692 0.0082 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 2025-09-07T09:59:34.2177832Z triton_mm_693 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:59:34.2178875Z SingleProcess AUTOTUNE benchmarking takes 0.2114 seconds and 0.0005 seconds precompiling for 17 choices 2025-09-07T09:59:34.9775918Z Autotune Choices Stats: 2025-09-07T09:59:34.9777165Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_671", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T09:59:34.9814904Z AUTOTUNE mm(4x1000, 1000x1024) 2025-09-07T09:59:34.9815191Z strides: [1000, 1], [1024, 1] 2025-09-07T09:59:34.9815493Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:34.9816284Z triton_mm_671 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:59:34.9817502Z triton_mm_675 0.0113 ms 100.0% 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 2025-09-07T09:59:34.9818717Z triton_mm_679 0.0123 ms 91.7% 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 2025-09-07T09:59:34.9819466Z mm 0.0133 ms 84.6% 2025-09-07T09:59:34.9820142Z triton_mm_669 0.0133 ms 84.6% 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 2025-09-07T09:59:34.9821343Z triton_mm_683 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:34.9822539Z triton_mm_670 0.0143 ms 78.6% 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 2025-09-07T09:59:34.9823721Z triton_mm_674 0.0143 ms 78.6% 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 2025-09-07T09:59:34.9824960Z triton_mm_668 0.0154 ms 73.3% 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=2, num_warps=2 2025-09-07T09:59:34.9826155Z triton_mm_678 0.0154 ms 73.3% 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 2025-09-07T09:59:34.9830808Z SingleProcess AUTOTUNE benchmarking takes 0.2418 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:59:45.8298149Z pass 2025-09-07T09:59:49.5447578Z accuracy pass_rate=72.73% 2025-09-07T09:59:49.5455704Z calls_captured gmean=0.00x mean=561.818x 2025-09-07T09:59:49.5459931Z unique_graphs gmean=0.00x mean=2.091x 2025-09-07T09:59:49.5464269Z graph_breaks gmean=0.00x mean=5.364x 2025-09-07T09:59:49.5468702Z unique_graph_breaks gmean=0.00x mean=4.091x 2025-09-07T09:59:49.5473029Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:59:49.5477140Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:59:49.5481352Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:59:49.5482550Z compilation_latency mean=43.274 seconds 2025-09-07T09:59:50.4553217Z + [[ 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* ]] 2025-09-07T09:59:50.4555852Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:59:50.4556370Z + for target in "${targets[@]}" 2025-09-07T09:59:50.4557420Z + target_flag=('--performance') 2025-09-07T09:59:50.4557946Z + local target_flag 2025-09-07T09:59:50.4558402Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:59:50.4559006Z + target_flag+=(--cold-start-latency) 2025-09-07T09:59:50.4561485Z + [[ 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* ]] 2025-09-07T09:59:50.4565441Z + [[ 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* ]] 2025-09-07T09:59:50.4570100Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.csv 2025-09-07T09:59:51.0474248Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:59:51.0476713Z import pynvml # type: ignore[import] 2025-09-07T09:59:54.8294424Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:59:54.8295904Z import pynvml # type: ignore[import] 2025-09-07T09:59:57.5675562Z 2025-09-07T09:59:58.5264370Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:59:58.5264812Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:59:58.5265183Z cuda train phlippe_resnet 2025-09-07T10:00:15.6899258Z 2025-09-07T10:00:15.8003680Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:00:56.5405837Z 2025-09-07T10:00:56.6483126Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:02:10.1637858Z 2025-09-07T10:02:10.3278168Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:05:19.5902573Z 2025-09-07T10:05:19.7663779Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:07:08.5179468Z 2025-09-07T10:07:08.6504324Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:07:20.8110403Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:07:20.8111223Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:07:20.8111896Z return self._call_impl(*args, **kwargs) 2025-09-07T10:07:20.8112531Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:07:20.8113169Z return forward_call(*args, **kwargs) 2025-09-07T10:07:20.8113841Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:07:20.8114551Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:07:20.8114958Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:07:20.8115255Z 2025-09-07T10:07:20.8115472Z The above exception was the direct cause of the following exception: 2025-09-07T10:07:20.8115817Z 2025-09-07T10:07:20.8115925Z Traceback (most recent call last): 2025-09-07T10:07:20.8116427Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:07:20.8116920Z ) = runner.load_model( 2025-09-07T10:07:20.8117429Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:07:20.8118020Z self.validate_model(model, example_inputs) 2025-09-07T10:07:20.8118601Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:07:20.8119200Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:07:20.8119544Z RuntimeError: Eager run failed 2025-09-07T10:07:20.8119740Z 2025-09-07T10:07:20.8119826Z eager_fail_to_run 2025-09-07T10:07:22.6109401Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:07:22.6111266Z import pynvml # type: ignore[import] 2025-09-07T10:07:25.4294221Z 2025-09-07T10:07:27.8147348Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:07:27.8147743Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:07:27.8148077Z cuda train resnext50_32x4d 2025-09-07T10:08:04.0858446Z W0907 10:08:04.084000 55861 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:08:27.9619482Z 2025-09-07T10:08:28.0874662Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:10:50.3720822Z 2025-09-07T10:10:50.4789278Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:12:04.6820120Z 2025-09-07T10:12:04.8593728Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:15:23.0923762Z 2025-09-07T10:15:23.3388027Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:17:12.5229080Z 2025-09-07T10:17:12.6440920Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:17:24.4697303Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:17:24.4698765Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:17:24.4700027Z return self._call_impl(*args, **kwargs) 2025-09-07T10:17:24.4701149Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:17:24.4702271Z return forward_call(*args, **kwargs) 2025-09-07T10:17:24.4703507Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:17:24.4704825Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:17:24.4705728Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:17:24.4706265Z 2025-09-07T10:17:24.4706671Z The above exception was the direct cause of the following exception: 2025-09-07T10:17:24.4707288Z 2025-09-07T10:17:24.4707487Z Traceback (most recent call last): 2025-09-07T10:17:24.4708429Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:17:24.4709399Z ) = runner.load_model( 2025-09-07T10:17:24.4710334Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:17:24.4711441Z self.validate_model(model, example_inputs) 2025-09-07T10:17:24.4712542Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:17:24.4713671Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:17:24.4714303Z RuntimeError: Eager run failed 2025-09-07T10:17:24.4714643Z 2025-09-07T10:17:24.4714810Z eager_fail_to_run 2025-09-07T10:17:26.1526538Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:17:26.1528069Z import pynvml # type: ignore[import] 2025-09-07T10:17:28.9761689Z 2025-09-07T10:17:31.2799613Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:17:31.2799991Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:17:31.2800322Z cuda train resnext50_32x4d 2025-09-07T10:18:14.6579906Z W0907 10:18:14.657000 73359 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:18:41.4254433Z 2025-09-07T10:18:41.5884580Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:21:19.4875115Z 2025-09-07T10:21:19.5947838Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:22:50.6344291Z 2025-09-07T10:22:50.8638391Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:26:21.7544910Z 2025-09-07T10:26:22.5593941Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:28:37.5993756Z 2025-09-07T10:28:38.1599536Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:28:49.9560435Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:28:49.9561259Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:28:49.9561948Z return self._call_impl(*args, **kwargs) 2025-09-07T10:28:49.9562590Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:28:49.9563219Z return forward_call(*args, **kwargs) 2025-09-07T10:28:49.9563898Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:28:49.9564608Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:28:49.9565045Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:28:49.9565333Z 2025-09-07T10:28:49.9565563Z The above exception was the direct cause of the following exception: 2025-09-07T10:28:49.9565897Z 2025-09-07T10:28:49.9566007Z Traceback (most recent call last): 2025-09-07T10:28:49.9566510Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:28:49.9567023Z ) = runner.load_model( 2025-09-07T10:28:49.9567530Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:28:49.9568124Z self.validate_model(model, example_inputs) 2025-09-07T10:28:49.9568693Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:28:49.9569294Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:28:49.9569652Z RuntimeError: Eager run failed 2025-09-07T10:28:49.9569840Z 2025-09-07T10:28:49.9569943Z eager_fail_to_run 2025-09-07T10:28:52.3222264Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:28:52.3224073Z import pynvml # type: ignore[import] 2025-09-07T10:28:55.0125645Z 2025-09-07T10:28:57.2669939Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:28:57.2670541Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:28:57.2671088Z cuda train resnext50_32x4d 2025-09-07T10:29:38.9804574Z W0907 10:29:38.979000 91296 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:30:06.3407822Z 2025-09-07T10:30:06.4641082Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:33:14.8360323Z 2025-09-07T10:33:14.9362601Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:35:10.1096711Z 2025-09-07T10:35:10.2759163Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:41:23.5937140Z 2025-09-07T10:41:23.7526477Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:44:18.9135431Z 2025-09-07T10:44:19.0498999Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:44:31.6001642Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:44:31.6002456Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:44:31.6003149Z return self._call_impl(*args, **kwargs) 2025-09-07T10:44:31.6003803Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:44:31.6004445Z return forward_call(*args, **kwargs) 2025-09-07T10:44:31.6005119Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:44:31.6005815Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:44:31.6006244Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:44:31.6006538Z 2025-09-07T10:44:31.6006752Z The above exception was the direct cause of the following exception: 2025-09-07T10:44:31.6007083Z 2025-09-07T10:44:31.6007208Z Traceback (most recent call last): 2025-09-07T10:44:31.6007705Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:44:31.6008198Z ) = runner.load_model( 2025-09-07T10:44:31.6008704Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:44:31.6009291Z self.validate_model(model, example_inputs) 2025-09-07T10:44:31.6009880Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:44:31.6010460Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:44:31.6010816Z RuntimeError: Eager run failed 2025-09-07T10:44:31.6011016Z 2025-09-07T10:44:31.6011290Z eager_fail_to_run 2025-09-07T10:44:33.3307890Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:44:33.3310231Z import pynvml # type: ignore[import] 2025-09-07T10:44:36.0548292Z 2025-09-07T10:44:38.3947845Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:44:38.3948231Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:44:38.3948541Z cuda train resnext50_32x4d 2025-09-07T10:45:45.9810938Z W0907 10:45:45.980000 110805 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:46:23.7512853Z 2025-09-07T10:46:23.8785254Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:49:43.0236871Z 2025-09-07T10:49:43.1362672Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:51:17.3532209Z 2025-09-07T10:51:17.5276626Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:55:04.2613958Z 2025-09-07T10:55:04.5002307Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:57:12.5620650Z 2025-09-07T10:57:12.6786810Z running benchmark: 0% 0/30 [00:00.3", line 167, in forward 2025-09-07T10:57:23.6270489Z activation_post_process_73 = self.activation_post_process_73(fc); fc = None 2025-09-07T10:57:23.6271529Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:57:23.6272225Z return self._call_impl(*args, **kwargs) 2025-09-07T10:57:23.6272863Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:57:23.6273526Z return forward_call(*args, **kwargs) 2025-09-07T10:57:23.6274223Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fake_quantize.py", line 411, in forward 2025-09-07T10:57:23.6274935Z return torch.fused_moving_avg_obs_fake_quant( 2025-09-07T10:57:23.6275362Z RuntimeError: expected scalar type Float but found Half 2025-09-07T10:57:23.6275652Z 2025-09-07T10:57:23.6275884Z The above exception was the direct cause of the following exception: 2025-09-07T10:57:23.6276218Z 2025-09-07T10:57:23.6276328Z Traceback (most recent call last): 2025-09-07T10:57:23.6276831Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:57:23.6277337Z ) = runner.load_model( 2025-09-07T10:57:23.6277850Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:57:23.6278426Z self.validate_model(model, example_inputs) 2025-09-07T10:57:23.6279009Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:57:23.6279612Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:57:23.6279969Z RuntimeError: Eager run failed 2025-09-07T10:57:23.6280154Z 2025-09-07T10:57:23.6280252Z eager_fail_to_run 2025-09-07T10:57:25.3391796Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:57:25.3393270Z import pynvml # type: ignore[import] 2025-09-07T10:57:28.3406617Z 2025-09-07T10:57:30.7630991Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:57:30.7631357Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:57:30.7631690Z cuda train resnext50_32x4d 2025-09-07T10:57:51.8324367Z Autotune Choices Stats: 2025-09-07T10:57:51.8326705Z {"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": 0.09011200070381165, "best_triton_pos": 0} 2025-09-07T10:57:51.8375053Z AUTOTUNE convolution(8x3x224x224, 64x3x7x7) 2025-09-07T10:57:51.8376359Z strides: [150528, 50176, 224, 1], [147, 49, 7, 1] 2025-09-07T10:57:51.8376992Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:51.8378628Z triton_convolution2d_5 0.0901 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 2025-09-07T10:57:51.8381239Z triton_convolution2d_1 0.0932 ms 96.7% 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 2025-09-07T10:57:51.8382812Z convolution 0.0973 ms 92.6% 2025-09-07T10:57:51.8384325Z triton_convolution2d_0 0.1208 ms 74.6% 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 2025-09-07T10:57:51.8387033Z triton_convolution2d_3 0.1208 ms 74.6% 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 2025-09-07T10:57:51.8390041Z triton_convolution2d_4 0.1403 ms 64.2% 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 2025-09-07T10:57:51.8392600Z triton_convolution2d_2 0.2243 ms 40.2% 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 2025-09-07T10:57:51.8394612Z SingleProcess AUTOTUNE benchmarking takes 0.2084 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T10:57:52.0521498Z Autotune Choices Stats: 2025-09-07T10:57:52.0524615Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.016383999958634377, "best_triton_kernel": "triton_convolution2d_9", "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"} 2025-09-07T10:57:52.0585795Z AUTOTUNE convolution(8x64x56x56, 128x64x1x1) 2025-09-07T10:57:52.0586497Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T10:57:52.0587066Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:52.0587590Z convolution 0.0154 ms 100.0% 2025-09-07T10:57:52.0589148Z triton_convolution2d_9 0.0164 ms 93.7% 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 2025-09-07T10:57:52.0591864Z triton_convolution2d_10 0.0164 ms 93.7% 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 2025-09-07T10:57:52.0594677Z triton_convolution2d_11 0.0174 ms 88.2% 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 2025-09-07T10:57:52.0597480Z triton_convolution2d_12 0.0236 ms 65.2% 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 2025-09-07T10:57:52.0600309Z triton_convolution2d_8 0.0266 ms 57.7% 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 2025-09-07T10:57:52.0603024Z triton_convolution2d_6 0.0287 ms 53.6% 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 2025-09-07T10:57:52.0605812Z triton_convolution2d_7 0.0328 ms 46.9% 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 2025-09-07T10:57:52.0607385Z conv1x1_via_mm 0.4393 ms 3.5% 2025-09-07T10:57:52.0608355Z SingleProcess AUTOTUNE benchmarking takes 0.2201 seconds and 0.0004 seconds precompiling for 9 choices 2025-09-07T10:57:52.2632456Z Autotune Choices Stats: 2025-09-07T10:57:52.2633833Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_16", "best_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", "best_time": 0.027648000046610832, "best_triton_pos": 0} 2025-09-07T10:57:52.2665542Z AUTOTUNE convolution(8x128x56x56, 256x128x1x1) 2025-09-07T10:57:52.2665972Z strides: [401408, 3136, 56, 1], [128, 1, 1, 1] 2025-09-07T10:57:52.2666342Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:52.2667617Z triton_convolution2d_16 0.0276 ms 100.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:52.2669127Z triton_convolution2d_19 0.0276 ms 100.0% 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 2025-09-07T10:57:52.2670612Z triton_convolution2d_18 0.0297 ms 93.1% 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 2025-09-07T10:57:52.2672088Z triton_convolution2d_17 0.0307 ms 90.0% 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 2025-09-07T10:57:52.2673559Z triton_convolution2d_14 0.0317 ms 87.1% 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 2025-09-07T10:57:52.2675029Z triton_convolution2d_13 0.0379 ms 73.0% 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 2025-09-07T10:57:52.2676492Z triton_convolution2d_15 0.0399 ms 69.2% 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 2025-09-07T10:57:52.2677397Z convolution 0.1137 ms 24.3% 2025-09-07T10:57:52.2677690Z conv1x1_via_mm 0.4250 ms 6.5% 2025-09-07T10:57:52.2678252Z SingleProcess AUTOTUNE benchmarking takes 0.2055 seconds and 0.0005 seconds precompiling for 9 choices 2025-09-07T10:57:52.4265617Z Autotune Choices Stats: 2025-09-07T10:57:52.4267034Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_23", "best_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", "best_time": 0.021503999829292297, "best_triton_pos": 0} 2025-09-07T10:57:52.4297826Z AUTOTUNE convolution(8x64x56x56, 256x64x1x1) 2025-09-07T10:57:52.4298199Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T10:57:52.4298552Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:52.4299467Z triton_convolution2d_23 0.0215 ms 100.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:52.4300967Z triton_convolution2d_26 0.0215 ms 100.0% 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 2025-09-07T10:57:52.4302755Z triton_convolution2d_21 0.0225 ms 95.5% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:52.4304226Z triton_convolution2d_25 0.0225 ms 95.5% 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 2025-09-07T10:57:52.4305764Z triton_convolution2d_24 0.0236 ms 91.3% 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 2025-09-07T10:57:52.4307224Z triton_convolution2d_20 0.0266 ms 80.8% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:52.4308888Z triton_convolution2d_22 0.0317 ms 67.7% 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 2025-09-07T10:57:52.4309810Z convolution 0.0338 ms 63.6% 2025-09-07T10:57:52.4310109Z conv1x1_via_mm 0.1239 ms 17.4% 2025-09-07T10:57:52.5947058Z SingleProcess AUTOTUNE benchmarking takes 0.1626 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:52.5948250Z Autotune Choices Stats: 2025-09-07T10:57:52.5950658Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_30", "best_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", "best_time": 0.026623999699950218, "best_triton_pos": 0} 2025-09-07T10:57:52.5980207Z AUTOTUNE convolution(8x256x56x56, 128x256x1x1) 2025-09-07T10:57:52.5980959Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T10:57:52.5981595Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:52.5983333Z triton_convolution2d_30 0.0266 ms 100.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:52.5986316Z triton_convolution2d_33 0.0287 ms 92.9% 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 2025-09-07T10:57:52.5989203Z triton_convolution2d_28 0.0307 ms 86.7% 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 2025-09-07T10:57:52.5992098Z triton_convolution2d_32 0.0317 ms 83.9% 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 2025-09-07T10:57:52.5994992Z triton_convolution2d_31 0.0328 ms 81.2% 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 2025-09-07T10:57:52.5997853Z triton_convolution2d_27 0.0389 ms 68.4% 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 2025-09-07T10:57:52.6000737Z triton_convolution2d_29 0.0410 ms 65.0% 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 2025-09-07T10:57:52.6002420Z convolution 0.0563 ms 47.3% 2025-09-07T10:57:52.6003340Z conv1x1_via_mm 0.1352 ms 19.7% 2025-09-07T10:57:52.6004356Z SingleProcess AUTOTUNE benchmarking takes 0.1675 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:52.7785263Z Autotune Choices Stats: 2025-09-07T10:57:52.7786615Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_58", "best_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", "best_time": 0.04095999896526337, "best_triton_pos": 0} 2025-09-07T10:57:52.7818386Z AUTOTUNE convolution(8x256x56x56, 256x256x1x1) 2025-09-07T10:57:52.7818778Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T10:57:52.7819128Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:52.7820040Z triton_convolution2d_58 0.0410 ms 100.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:52.7821521Z triton_convolution2d_61 0.0430 ms 95.2% 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 2025-09-07T10:57:52.7823282Z triton_convolution2d_56 0.0471 ms 87.0% 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 2025-09-07T10:57:52.7824751Z triton_convolution2d_59 0.0471 ms 87.0% 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 2025-09-07T10:57:52.7826312Z triton_convolution2d_60 0.0563 ms 72.7% 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 2025-09-07T10:57:52.7827779Z triton_convolution2d_55 0.0614 ms 66.7% 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 2025-09-07T10:57:52.7829244Z triton_convolution2d_57 0.0686 ms 59.7% 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 2025-09-07T10:57:52.7830142Z convolution 0.0737 ms 55.6% 2025-09-07T10:57:52.7830431Z conv1x1_via_mm 0.1823 ms 22.5% 2025-09-07T10:57:52.7830983Z SingleProcess AUTOTUNE benchmarking takes 0.1803 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:57:52.9437786Z Autotune Choices Stats: 2025-09-07T10:57:52.9439157Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_65", "best_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", "best_time": 0.023552000522613525, "best_triton_pos": 0} 2025-09-07T10:57:52.9470619Z AUTOTUNE convolution(8x256x28x28, 512x256x1x1) 2025-09-07T10:57:52.9471042Z strides: [200704, 784, 28, 1], [256, 1, 1, 1] 2025-09-07T10:57:52.9471392Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:52.9472308Z triton_convolution2d_65 0.0236 ms 100.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:52.9473793Z triton_convolution2d_68 0.0236 ms 100.0% 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 2025-09-07T10:57:52.9475271Z triton_convolution2d_67 0.0246 ms 95.8% 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 2025-09-07T10:57:52.9477051Z triton_convolution2d_63 0.0266 ms 88.5% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:52.9478522Z triton_convolution2d_62 0.0276 ms 85.2% 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 2025-09-07T10:57:52.9479987Z triton_convolution2d_66 0.0276 ms 85.2% 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 2025-09-07T10:57:52.9480874Z convolution 0.0379 ms 62.2% 2025-09-07T10:57:52.9481757Z triton_convolution2d_64 0.0655 ms 35.9% 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 2025-09-07T10:57:52.9482663Z conv1x1_via_mm 0.0983 ms 24.0% 2025-09-07T10:57:52.9483391Z SingleProcess AUTOTUNE benchmarking takes 0.1646 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:53.0874350Z Autotune Choices Stats: 2025-09-07T10:57:53.0875644Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_72", "best_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", "best_time": 0.028672000393271446, "best_triton_pos": 0} 2025-09-07T10:57:53.0907244Z AUTOTUNE convolution(8x256x56x56, 512x256x1x1) 2025-09-07T10:57:53.0907633Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T10:57:53.0907965Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:53.0908876Z triton_convolution2d_72 0.0287 ms 100.0% 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 2025-09-07T10:57:53.0910382Z triton_convolution2d_69 0.0317 ms 90.3% 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 2025-09-07T10:57:53.0911845Z triton_convolution2d_75 0.0348 ms 82.4% 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 2025-09-07T10:57:53.0913310Z triton_convolution2d_70 0.0358 ms 80.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:53.0914772Z triton_convolution2d_74 0.0369 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:53.0916236Z triton_convolution2d_73 0.0379 ms 75.7% 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 2025-09-07T10:57:53.0917125Z convolution 0.0543 ms 52.8% 2025-09-07T10:57:53.0917977Z triton_convolution2d_71 0.1495 ms 19.2% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:57:53.0919141Z SingleProcess AUTOTUNE benchmarking takes 0.1430 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T10:57:53.2566581Z Autotune Choices Stats: 2025-09-07T10:57:53.2568205Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023552000522613525, "best_triton_pos": 1, "best_triton_time": 0.026623999699950218, "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"} 2025-09-07T10:57:53.2599291Z AUTOTUNE convolution(8x512x28x28, 256x512x1x1) 2025-09-07T10:57:53.2599696Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T10:57:53.2600030Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:53.2600347Z convolution 0.0236 ms 100.0% 2025-09-07T10:57:53.2601223Z triton_convolution2d_80 0.0266 ms 88.5% 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 2025-09-07T10:57:53.2602708Z triton_convolution2d_79 0.0328 ms 71.9% 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 2025-09-07T10:57:53.2604549Z triton_convolution2d_81 0.0328 ms 71.9% 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 2025-09-07T10:57:53.2606023Z triton_convolution2d_82 0.0328 ms 71.9% 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 2025-09-07T10:57:53.2607511Z triton_convolution2d_77 0.0399 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 2025-09-07T10:57:53.2608984Z triton_convolution2d_76 0.0420 ms 56.1% 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 2025-09-07T10:57:53.2610486Z triton_convolution2d_78 0.0829 ms 28.4% 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 2025-09-07T10:57:53.2611408Z conv1x1_via_mm 0.0891 ms 26.4% 2025-09-07T10:57:53.2611980Z SingleProcess AUTOTUNE benchmarking takes 0.1686 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:57:53.4435812Z Autotune Choices Stats: 2025-09-07T10:57:53.4437509Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03276799991726875, "best_triton_pos": 1, "best_triton_time": 0.035840000957250595, "best_triton_kernel": "triton_convolution2d_121", "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"} 2025-09-07T10:57:53.4476776Z AUTOTUNE convolution(8x512x28x28, 512x512x1x1) 2025-09-07T10:57:53.4477214Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T10:57:53.4477562Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:53.4477891Z convolution 0.0328 ms 100.0% 2025-09-07T10:57:53.4478815Z triton_convolution2d_121 0.0358 ms 91.4% 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 2025-09-07T10:57:53.4480320Z triton_convolution2d_124 0.0369 ms 88.9% 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 2025-09-07T10:57:53.4481826Z triton_convolution2d_123 0.0379 ms 86.5% 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 2025-09-07T10:57:53.4483608Z triton_convolution2d_119 0.0430 ms 76.2% 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 2025-09-07T10:57:53.4485089Z triton_convolution2d_118 0.0440 ms 74.4% 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 2025-09-07T10:57:53.4486573Z triton_convolution2d_122 0.0440 ms 74.4% 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 2025-09-07T10:57:53.4488054Z triton_convolution2d_120 0.1178 ms 27.8% 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 2025-09-07T10:57:53.4488970Z conv1x1_via_mm 0.1239 ms 26.4% 2025-09-07T10:57:53.4489542Z SingleProcess AUTOTUNE benchmarking takes 0.1792 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:57:53.6165492Z Autotune Choices Stats: 2025-09-07T10:57:53.6167219Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_129", "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": 0.026623999699950218, "best_triton_pos": 0} 2025-09-07T10:57:53.6199167Z AUTOTUNE convolution(8x512x14x14, 1024x512x1x1) 2025-09-07T10:57:53.6199564Z strides: [100352, 196, 14, 1], [512, 1, 1, 1] 2025-09-07T10:57:53.6199915Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:53.6200840Z triton_convolution2d_129 0.0266 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 2025-09-07T10:57:53.6201770Z convolution 0.0307 ms 86.7% 2025-09-07T10:57:53.6202662Z triton_convolution2d_130 0.0307 ms 86.7% 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 2025-09-07T10:57:53.6204162Z triton_convolution2d_128 0.0328 ms 81.2% 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 2025-09-07T10:57:53.6205642Z triton_convolution2d_125 0.0420 ms 63.4% 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 2025-09-07T10:57:53.6207122Z triton_convolution2d_126 0.0451 ms 59.1% 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 2025-09-07T10:57:53.6208621Z triton_convolution2d_131 0.0532 ms 50.0% 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 2025-09-07T10:57:53.6209523Z conv1x1_via_mm 0.0819 ms 32.5% 2025-09-07T10:57:53.6210407Z triton_convolution2d_127 0.0881 ms 30.2% 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 2025-09-07T10:57:53.6211584Z SingleProcess AUTOTUNE benchmarking takes 0.1715 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:53.7688784Z Autotune Choices Stats: 2025-09-07T10:57:53.7690133Z {"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": 0.03276799991726875, "best_triton_pos": 0} 2025-09-07T10:57:53.7724140Z AUTOTUNE convolution(8x512x28x28, 1024x512x1x1) 2025-09-07T10:57:53.7724523Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T10:57:53.7724887Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:53.7725804Z triton_convolution2d_136 0.0328 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 2025-09-07T10:57:53.7727297Z triton_convolution2d_137 0.0338 ms 97.0% 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 2025-09-07T10:57:53.7728770Z triton_convolution2d_135 0.0348 ms 94.1% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:53.7729683Z convolution 0.0379 ms 86.5% 2025-09-07T10:57:53.7730766Z triton_convolution2d_132 0.0451 ms 72.7% 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 2025-09-07T10:57:53.7732255Z triton_convolution2d_133 0.0543 ms 60.4% 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 2025-09-07T10:57:53.7733998Z triton_convolution2d_138 0.0543 ms 60.4% 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 2025-09-07T10:57:53.7735495Z triton_convolution2d_134 0.1628 ms 20.1% 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 2025-09-07T10:57:53.7736686Z SingleProcess AUTOTUNE benchmarking takes 0.1518 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T10:57:53.9592993Z Autotune Choices Stats: 2025-09-07T10:57:53.9594657Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03276799991726875, "best_triton_pos": 1, "best_triton_time": 0.03788800165057182, "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"} 2025-09-07T10:57:53.9626322Z AUTOTUNE convolution(8x1024x14x14, 512x1024x1x1) 2025-09-07T10:57:53.9626725Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T10:57:53.9627076Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:53.9627395Z convolution 0.0328 ms 100.0% 2025-09-07T10:57:53.9628278Z triton_convolution2d_143 0.0379 ms 86.5% 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 2025-09-07T10:57:53.9629771Z triton_convolution2d_144 0.0492 ms 66.7% 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 2025-09-07T10:57:53.9631263Z triton_convolution2d_142 0.0532 ms 61.5% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:53.9632745Z triton_convolution2d_145 0.0563 ms 58.2% 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 2025-09-07T10:57:53.9634524Z triton_convolution2d_139 0.0737 ms 44.4% 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 2025-09-07T10:57:53.9636015Z triton_convolution2d_140 0.0748 ms 43.8% 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 2025-09-07T10:57:53.9636925Z conv1x1_via_mm 0.0860 ms 38.1% 2025-09-07T10:57:53.9637813Z triton_convolution2d_141 0.1004 ms 32.7% 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 2025-09-07T10:57:53.9638974Z SingleProcess AUTOTUNE benchmarking takes 0.1896 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:54.1729627Z Autotune Choices Stats: 2025-09-07T10:57:54.1731669Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03993599861860275, "best_triton_pos": 1, "best_triton_time": 0.043007999658584595, "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"} 2025-09-07T10:57:54.1762826Z AUTOTUNE convolution(8x1024x14x14, 1024x1024x1x1) 2025-09-07T10:57:54.1763255Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T10:57:54.1763620Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:54.1763925Z convolution 0.0399 ms 100.0% 2025-09-07T10:57:54.1764800Z triton_convolution2d_213 0.0430 ms 92.9% 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 2025-09-07T10:57:54.1766281Z triton_convolution2d_214 0.0502 ms 79.6% 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 2025-09-07T10:57:54.1767791Z triton_convolution2d_212 0.0532 ms 75.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:54.1769270Z triton_convolution2d_209 0.0758 ms 52.7% 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 2025-09-07T10:57:54.1770744Z triton_convolution2d_210 0.0799 ms 50.0% 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 2025-09-07T10:57:54.1772223Z triton_convolution2d_215 0.0952 ms 41.9% 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 2025-09-07T10:57:54.1773211Z conv1x1_via_mm 0.1208 ms 33.1% 2025-09-07T10:57:54.1774106Z triton_convolution2d_211 0.1659 ms 24.1% 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 2025-09-07T10:57:54.1775278Z SingleProcess AUTOTUNE benchmarking takes 0.2003 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T10:57:54.3692202Z Autotune Choices Stats: 2025-09-07T10:57:54.3694100Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03481600061058998, "best_triton_pos": 1, "best_triton_time": 0.03993599861860275, "best_triton_kernel": "triton_convolution2d_220", "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"} 2025-09-07T10:57:54.3726711Z AUTOTUNE convolution(8x1024x7x7, 2048x1024x1x1) 2025-09-07T10:57:54.3727113Z strides: [50176, 49, 7, 1], [1024, 1, 1, 1] 2025-09-07T10:57:54.3727434Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:54.3727768Z convolution 0.0348 ms 100.0% 2025-09-07T10:57:54.3728637Z triton_convolution2d_220 0.0399 ms 87.2% 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 2025-09-07T10:57:54.3730111Z triton_convolution2d_221 0.0512 ms 68.0% 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 2025-09-07T10:57:54.3731590Z triton_convolution2d_219 0.0532 ms 65.4% 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 2025-09-07T10:57:54.3733465Z triton_convolution2d_222 0.0676 ms 51.5% 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 2025-09-07T10:57:54.3734934Z triton_convolution2d_216 0.0727 ms 47.9% 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 2025-09-07T10:57:54.3736412Z triton_convolution2d_217 0.0911 ms 38.2% 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 2025-09-07T10:57:54.3737313Z conv1x1_via_mm 0.1024 ms 34.0% 2025-09-07T10:57:54.3738191Z triton_convolution2d_218 0.1167 ms 29.8% 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 2025-09-07T10:57:54.3739366Z SingleProcess AUTOTUNE benchmarking takes 0.1948 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:54.5463878Z Autotune Choices Stats: 2025-09-07T10:57:54.5465635Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03788800165057182, "best_triton_pos": 1, "best_triton_time": 0.04608000069856644, "best_triton_kernel": "triton_convolution2d_227", "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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:57:54.5498225Z AUTOTUNE convolution(8x1024x14x14, 2048x1024x1x1) 2025-09-07T10:57:54.5498598Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T10:57:54.5498955Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:54.5499292Z convolution 0.0379 ms 100.0% 2025-09-07T10:57:54.5500166Z triton_convolution2d_227 0.0461 ms 82.2% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:54.5501655Z triton_convolution2d_228 0.0553 ms 68.5% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:54.5503136Z triton_convolution2d_226 0.0604 ms 62.7% 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 2025-09-07T10:57:54.5504623Z triton_convolution2d_223 0.0788 ms 48.1% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:54.5506505Z triton_convolution2d_229 0.0819 ms 46.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:54.5507998Z triton_convolution2d_224 0.0973 ms 38.9% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:54.5509484Z triton_convolution2d_225 0.2365 ms 16.0% 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 2025-09-07T10:57:54.5510657Z SingleProcess AUTOTUNE benchmarking takes 0.1756 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T10:57:54.7801518Z Autotune Choices Stats: 2025-09-07T10:57:54.7803393Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03686400130391121, "best_triton_pos": 1, "best_triton_time": 0.0655359998345375, "best_triton_kernel": "triton_convolution2d_234", "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"} 2025-09-07T10:57:54.7836698Z AUTOTUNE convolution(8x2048x7x7, 1024x2048x1x1) 2025-09-07T10:57:54.7837110Z strides: [100352, 49, 7, 1], [2048, 1, 1, 1] 2025-09-07T10:57:54.7837451Z dtypes: torch.float16, torch.float16 2025-09-07T10:57:54.7837772Z convolution 0.0369 ms 100.0% 2025-09-07T10:57:54.7838658Z triton_convolution2d_234 0.0655 ms 56.3% 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 2025-09-07T10:57:54.7840146Z triton_convolution2d_235 0.0911 ms 40.4% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:57:54.7841656Z triton_convolution2d_233 0.0942 ms 39.1% 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 2025-09-07T10:57:54.7842569Z conv1x1_via_mm 0.0952 ms 38.7% 2025-09-07T10:57:54.7843455Z triton_convolution2d_236 0.1219 ms 30.3% 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 2025-09-07T10:57:54.7844938Z triton_convolution2d_230 0.1331 ms 27.7% 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 2025-09-07T10:57:54.7846413Z triton_convolution2d_231 0.1567 ms 23.5% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:57:54.7847903Z triton_convolution2d_232 0.1700 ms 21.7% 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 2025-09-07T10:57:54.7849087Z SingleProcess AUTOTUNE benchmarking takes 0.2322 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T10:57:55.0909199Z Autotune Choices Stats: 2025-09-07T10:57:55.0910408Z {"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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T10:57:55.0946838Z AUTOTUNE addmm(8x1000, 8x2048, 2048x1000) 2025-09-07T10:57:55.0947487Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T10:57:55.0947844Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:57:55.0948656Z triton_mm_262 0.0133 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 2025-09-07T10:57:55.0949864Z triton_mm_266 0.0133 ms 100.0% 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 2025-09-07T10:57:55.0950622Z bias_addmm 0.0184 ms 72.2% 2025-09-07T10:57:55.0951339Z triton_mm_270 0.0184 ms 72.2% 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 2025-09-07T10:57:55.0952082Z addmm 0.0195 ms 68.4% 2025-09-07T10:57:55.0952761Z triton_mm_274 0.0195 ms 68.4% 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 2025-09-07T10:57:55.0953936Z triton_mm_261 0.0205 ms 65.0% 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 2025-09-07T10:57:55.0961614Z triton_mm_260 0.0215 ms 61.9% 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 2025-09-07T10:57:55.0962982Z triton_mm_265 0.0215 ms 61.9% 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 2025-09-07T10:57:55.0964161Z triton_mm_259 0.0225 ms 59.1% 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 2025-09-07T10:57:55.0965185Z SingleProcess AUTOTUNE benchmarking takes 0.3037 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:58:09.0451926Z Autotune Choices Stats: 2025-09-07T10:58:09.0453404Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_294", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, 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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T10:58:09.0487914Z AUTOTUNE mm(1000x8, 8x2048) 2025-09-07T10:58:09.0488225Z strides: [1, 1000], [2048, 1] 2025-09-07T10:58:09.0488511Z dtypes: torch.float16, torch.float16 2025-09-07T10:58:09.0489275Z triton_mm_294 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T10:58:09.0490464Z triton_mm_297 0.0092 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 2025-09-07T10:58:09.0491669Z triton_mm_298 0.0092 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=3, num_warps=8 2025-09-07T10:58:09.0492955Z triton_mm_299 0.0092 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=5, num_warps=4 2025-09-07T10:58:09.0494143Z triton_mm_303 0.0092 ms 100.0% 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 2025-09-07T10:58:09.0495339Z triton_mm_304 0.0092 ms 100.0% 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 2025-09-07T10:58:09.0496537Z triton_mm_305 0.0092 ms 100.0% 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=2, num_warps=8 2025-09-07T10:58:09.0498121Z triton_mm_306 0.0092 ms 100.0% 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 2025-09-07T10:58:09.0499331Z triton_mm_307 0.0092 ms 100.0% 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 2025-09-07T10:58:09.0500519Z triton_mm_292 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T10:58:09.0501541Z SingleProcess AUTOTUNE benchmarking takes 0.2070 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T10:58:09.6133463Z Autotune Choices Stats: 2025-09-07T10:58:09.6134691Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_283", "best_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", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T10:58:09.6169609Z AUTOTUNE mm(8x1000, 1000x2048) 2025-09-07T10:58:09.6169928Z strides: [1000, 1], [2048, 1] 2025-09-07T10:58:09.6170559Z dtypes: torch.float16, torch.float16 2025-09-07T10:58:09.6171322Z triton_mm_283 0.0123 ms 100.0% 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 2025-09-07T10:58:09.6172530Z triton_mm_279 0.0133 ms 92.3% 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 2025-09-07T10:58:09.6173841Z triton_mm_287 0.0133 ms 92.3% 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 2025-09-07T10:58:09.6175029Z triton_mm_291 0.0133 ms 92.3% 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 2025-09-07T10:58:09.6175781Z mm 0.0143 ms 85.7% 2025-09-07T10:58:09.6176469Z triton_mm_277 0.0143 ms 85.7% 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 2025-09-07T10:58:09.6177626Z triton_mm_282 0.0143 ms 85.7% 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 2025-09-07T10:58:09.6178790Z triton_mm_278 0.0154 ms 80.0% 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 2025-09-07T10:58:09.6179960Z triton_mm_286 0.0154 ms 80.0% 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 2025-09-07T10:58:09.6181136Z triton_mm_289 0.0154 ms 80.0% 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 2025-09-07T10:58:09.6182177Z SingleProcess AUTOTUNE benchmarking takes 0.2562 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T10:58:18.3834679Z W0907 10:58:18.382000 144435 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:58:44.5173650Z 2025-09-07T10:58:44.6480512Z running benchmark: 0% 0/30 [00:00 2025-09-07T11:20:07.4626807Z torchbench_main() 2025-09-07T11:20:07.4627725Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T11:20:07.4628366Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T11:20:07.4628908Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T11:20:07.4632313Z process_entry(0, runner, original_dir, args) 2025-09-07T11:20:07.4632914Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T11:20:07.4636202Z result = run(runner, args, original_dir) 2025-09-07T11:20:07.4636712Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4251, in run 2025-09-07T11:20:07.4641013Z assert marked, f"nothing in example_inputs had a dim with {batch_size}" 2025-09-07T11:20:07.4641562Z AssertionError: nothing in example_inputs had a dim with 4 2025-09-07T11:20:09.8661834Z Run failed with return code: 1 2025-09-07T11:20:09.8662200Z Output: None 2025-09-07T11:20:09.8662449Z Error: None 2025-09-07T11:20:10.4363504Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:20:10.4364975Z import pynvml # type: ignore[import] 2025-09-07T11:20:13.1542486Z 2025-09-07T11:20:14.2190624Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:20:14.2191013Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:20:14.2260596Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:20:20.5640725Z pass 2025-09-07T11:20:22.8576479Z accuracy pass_rate=92.86% 2025-09-07T11:20:22.8584578Z calls_captured gmean=0.00x mean=420.357x 2025-09-07T11:20:22.8589765Z unique_graphs gmean=0.00x mean=0.929x 2025-09-07T11:20:22.8595483Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:20:22.8600786Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:20:22.8606978Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:20:22.8612932Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:20:22.8619198Z cudagraph_skips gmean=0.00x mean=0.071x 2025-09-07T11:20:22.8621175Z compilation_latency mean=4.962 seconds 2025-09-07T11:20:23.8472578Z + [[ 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* ]] 2025-09-07T11:20:23.8474061Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T11:20:23.8475633Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:20:24.4485170Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:20:24.4486574Z import pynvml # type: ignore[import] 2025-09-07T11:20:28.4681392Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:20:28.4683978Z import pynvml # type: ignore[import] 2025-09-07T11:20:31.1341037Z 2025-09-07T11:20:32.0066964Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:20:32.0067358Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:20:32.0092218Z cuda eval phlippe_resnet 2025-09-07T11:20:45.3368550Z pass 2025-09-07T11:20:48.3309786Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:20:48.3311470Z import pynvml # type: ignore[import] 2025-09-07T11:20:51.2104930Z 2025-09-07T11:20:51.6498032Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:20:51.6498400Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:20:51.6499068Z cuda eval pyhpc_equation_of_state 2025-09-07T11:21:04.8192201Z pass 2025-09-07T11:21:07.6163094Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:21:07.6165676Z import pynvml # type: ignore[import] 2025-09-07T11:21:10.4549024Z 2025-09-07T11:21:10.8652978Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:21:10.8653387Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:21:10.8658475Z cuda eval pyhpc_isoneutral_mixing 2025-09-07T11:21:29.6687662Z pass 2025-09-07T11:21:32.7293409Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:21:32.7295736Z import pynvml # type: ignore[import] 2025-09-07T11:21:35.3963022Z 2025-09-07T11:21:36.2520248Z loading model: 0it [00:00, ?it/s]WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:21:36.4083992Z 2025-09-07T11:21:36.4084319Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:21:36.4084928Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:21:36.4085579Z cuda eval pyhpc_turbulent_kinetic_energy 2025-09-07T11:21:36.4291610Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:22:03.7643176Z pass 2025-09-07T11:22:07.4085369Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:22:07.4087988Z import pynvml # type: ignore[import] 2025-09-07T11:22:10.1424548Z 2025-09-07T11:22:10.9913447Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:22:10.9914747Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:22:10.9926251Z cuda eval pytorch_CycleGAN_and_pix2pix 2025-09-07T11:22:28.0747207Z pass 2025-09-07T11:22:31.0038892Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:22:31.0040328Z import pynvml # type: ignore[import] 2025-09-07T11:22:33.6598594Z 2025-09-07T11:22:35.0434127Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:22:35.0434496Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:22:35.0456929Z cuda eval pytorch_stargan 2025-09-07T11:22:52.1866507Z pass 2025-09-07T11:22:55.3811139Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:22:55.3812605Z import pynvml # type: ignore[import] 2025-09-07T11:22:58.2036527Z 2025-09-07T11:22:59.1701614Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:22:59.1702928Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:22:59.1725687Z cuda eval pytorch_unet 2025-09-07T11:23:19.0621249Z pass 2025-09-07T11:23:22.1305774Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:23:22.1309238Z import pynvml # type: ignore[import] 2025-09-07T11:23:24.9383181Z 2025-09-07T11:23:27.2471377Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:23:27.2471777Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:23:27.2652497Z cuda eval resnet152 2025-09-07T11:24:11.3053609Z pass 2025-09-07T11:24:14.9388892Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:24:14.9390334Z import pynvml # type: ignore[import] 2025-09-07T11:24:17.8879059Z 2025-09-07T11:24:19.2413371Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:24:19.2413761Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:24:19.2442749Z cuda eval resnet18 2025-09-07T11:24:33.3363980Z pass 2025-09-07T11:24:36.3534598Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:24:36.3536078Z import pynvml # type: ignore[import] 2025-09-07T11:24:39.1777081Z 2025-09-07T11:24:40.7370739Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:24:40.7371121Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:24:40.7436727Z cuda eval resnet50 2025-09-07T11:25:01.2082018Z pass 2025-09-07T11:25:04.6421898Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:25:04.6423336Z import pynvml # type: ignore[import] 2025-09-07T11:25:07.3849728Z 2025-09-07T11:25:07.5443607Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:25:07.5444208Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:25:07.5444752Z cuda eval resnet50_quantized_qat 2025-09-07T11:25:07.5450425Z Traceback (most recent call last): 2025-09-07T11:25:07.5451401Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:25:07.5452286Z ) = runner.load_model( 2025-09-07T11:25:07.5453550Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:25:07.5454555Z benchmark = benchmark_cls( 2025-09-07T11:25:07.5455296Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:25:07.5456089Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:25:07.5457123Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:25:07.5458348Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:25:07.5459219Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:25:07.5459719Z 2025-09-07T11:25:07.5459896Z model_fail_to_load 2025-09-07T11:25:09.0086660Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:25:09.0089616Z import pynvml # type: ignore[import] 2025-09-07T11:25:12.3365357Z 2025-09-07T11:25:14.1892008Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:25:14.1892388Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:25:14.1955451Z cuda eval resnext50_32x4d 2025-09-07T11:25:35.5193322Z pass 2025-09-07T11:25:38.6322627Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:25:38.6325189Z import pynvml # type: ignore[import] 2025-09-07T11:25:41.6216264Z 2025-09-07T11:25:49.4863389Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:25:49.4864023Z loading model: 0it [00:07, ?it/s] 2025-09-07T11:25:49.4986011Z cuda eval sam 2025-09-07T11:27:28.3823142Z pass 2025-09-07T11:27:32.7231577Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:27:32.7233011Z import pynvml # type: ignore[import] 2025-09-07T11:27:35.5017756Z 2025-09-07T11:27:48.0578266Z loading model: 0it [00:00, ?it/s]skipping cudagraphs due to cpp wrapper enabled 2025-09-07T11:28:21.7245568Z Autotune Choices Stats: 2025-09-07T11:28:21.7247082Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.22015999257564545, "best_triton_pos": 1, "best_triton_time": 0.26009601354599, "best_triton_kernel": "triton_mm_91", "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"} 2025-09-07T11:28:21.7292603Z AUTOTUNE mm(4096x1280, 1280x5120) 2025-09-07T11:28:21.7293148Z strides: [1280, 1], [1, 1280] 2025-09-07T11:28:21.7293473Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:21.7293785Z mm 0.2202 ms 100.0% 2025-09-07T11:28:21.7294473Z triton_mm_91 0.2601 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 2025-09-07T11:28:21.7295670Z triton_mm_90 0.2877 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:28:21.7296856Z triton_mm_84 0.3123 ms 70.5% 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 2025-09-07T11:28:21.7298420Z triton_mm_86 0.3133 ms 70.3% 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 2025-09-07T11:28:21.7299614Z triton_mm_87 0.3174 ms 69.4% 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 2025-09-07T11:28:21.7300796Z triton_mm_92 0.3594 ms 61.3% 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 2025-09-07T11:28:21.7301971Z triton_mm_85 0.3697 ms 59.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:28:21.7303155Z triton_mm_89 0.3809 ms 57.8% 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 2025-09-07T11:28:21.7304347Z triton_mm_88 0.3963 ms 55.6% 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 2025-09-07T11:28:21.7305664Z SingleProcess AUTOTUNE benchmarking takes 1.0543 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:28:23.2877821Z Autotune Choices Stats: 2025-09-07T11:28:23.2879324Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.2017280012369156, "best_triton_pos": 1, "best_triton_time": 0.26316800713539124, "best_triton_kernel": "triton_mm_3349", "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"} 2025-09-07T11:28:23.2924030Z AUTOTUNE mm(4096x5120, 5120x1280) 2025-09-07T11:28:23.2924347Z strides: [5120, 1], [1, 5120] 2025-09-07T11:28:23.2924650Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:23.2924983Z mm 0.2017 ms 100.0% 2025-09-07T11:28:23.2925698Z triton_mm_3349 0.2632 ms 76.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:28:23.2926930Z triton_mm_3348 0.2806 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 2025-09-07T11:28:23.2928119Z triton_mm_3345 0.3154 ms 64.0% 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 2025-09-07T11:28:23.2929321Z triton_mm_3344 0.3246 ms 62.1% 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 2025-09-07T11:28:23.2930508Z triton_mm_3342 0.3348 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=3, num_warps=4 2025-09-07T11:28:23.2931716Z triton_mm_3350 0.3348 ms 60.2% 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 2025-09-07T11:28:23.2933118Z triton_mm_3339 0.3676 ms 54.9% 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 2025-09-07T11:28:23.2934306Z triton_mm_3341 0.3676 ms 54.9% 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 2025-09-07T11:28:23.2935496Z triton_mm_3340 0.3717 ms 54.3% 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 2025-09-07T11:28:23.2936512Z SingleProcess AUTOTUNE benchmarking takes 0.7346 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:28:23.7907104Z Autotune Choices Stats: 2025-09-07T11:28:23.7908623Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.06656000018119812, "best_triton_pos": 1, "best_triton_time": 0.06656000018119812, "best_triton_kernel": "triton_mm_805", "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"} 2025-09-07T11:28:23.7954254Z AUTOTUNE mm(4096x1280, 1280x1280) 2025-09-07T11:28:23.7954598Z strides: [1280, 1], [1, 1280] 2025-09-07T11:28:23.7954882Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:23.7955188Z mm 0.0666 ms 100.0% 2025-09-07T11:28:23.7955906Z triton_mm_805 0.0666 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 2025-09-07T11:28:23.7957115Z triton_mm_804 0.0748 ms 89.0% 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 2025-09-07T11:28:23.7958628Z triton_mm_800 0.0768 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 2025-09-07T11:28:23.7959820Z triton_mm_801 0.0778 ms 85.5% 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 2025-09-07T11:28:23.7960995Z triton_mm_798 0.0829 ms 80.2% 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 2025-09-07T11:28:23.7962189Z triton_mm_806 0.0850 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 2025-09-07T11:28:23.7963383Z triton_mm_799 0.0891 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=4, num_warps=8 2025-09-07T11:28:23.7964565Z triton_mm_802 0.0891 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 2025-09-07T11:28:23.7965737Z triton_mm_796 0.1044 ms 63.7% 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 2025-09-07T11:28:23.7966761Z SingleProcess AUTOTUNE benchmarking takes 0.4838 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:28:25.2649930Z Autotune Choices Stats: 2025-09-07T11:28:25.2651307Z {"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": 0.45772799849510193, "best_triton_pos": 0} 2025-09-07T11:28:25.2697298Z AUTOTUNE convolution(1x3x1024x1024, 1280x3x16x16) 2025-09-07T11:28:25.2697763Z strides: [3145728, 1048576, 1024, 1], [768, 256, 16, 1] 2025-09-07T11:28:25.2698134Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:25.2699049Z triton_convolution2d_6 0.4577 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 2025-09-07T11:28:25.2700572Z triton_convolution2d_1 0.4751 ms 96.3% 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 2025-09-07T11:28:25.2702085Z triton_convolution2d_3 0.5202 ms 88.0% 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 2025-09-07T11:28:25.2703359Z convolution 0.5468 ms 83.7% 2025-09-07T11:28:25.2704259Z triton_convolution2d_5 0.8059 ms 56.8% 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=8 2025-09-07T11:28:25.2705838Z triton_convolution2d_4 0.8724 ms 52.5% 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 2025-09-07T11:28:25.2707334Z triton_convolution2d_0 0.9021 ms 50.7% 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=4 2025-09-07T11:28:25.2708841Z triton_convolution2d_2 2.1494 ms 21.3% 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 2025-09-07T11:28:25.2710019Z SingleProcess AUTOTUNE benchmarking takes 0.4099 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:28:25.9923426Z Autotune Choices Stats: 2025-09-07T11:28:25.9924897Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.19865599274635315, "best_triton_pos": 1, "best_triton_time": 0.2529279887676239, "best_triton_kernel": "triton_mm_23", "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"} 2025-09-07T11:28:25.9974371Z AUTOTUNE mm(4900x1280, 1280x3840) 2025-09-07T11:28:25.9974684Z strides: [1280, 1], [1, 1280] 2025-09-07T11:28:25.9974981Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:25.9975289Z mm 0.1987 ms 100.0% 2025-09-07T11:28:25.9975989Z triton_mm_23 0.2529 ms 78.5% 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 2025-09-07T11:28:25.9977182Z triton_mm_22 0.2591 ms 76.7% 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 2025-09-07T11:28:25.9978362Z triton_mm_19 0.2877 ms 69.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:28:25.9979533Z triton_mm_18 0.2918 ms 68.1% 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 2025-09-07T11:28:25.9980701Z triton_mm_16 0.2929 ms 67.8% 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 2025-09-07T11:28:25.9981883Z triton_mm_24 0.3451 ms 57.6% 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 2025-09-07T11:28:25.9983065Z triton_mm_13 0.3492 ms 56.9% 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 2025-09-07T11:28:25.9984218Z triton_mm_20 0.3492 ms 56.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:28:25.9985479Z triton_mm_17 0.3523 ms 56.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:28:25.9986502Z SingleProcess AUTOTUNE benchmarking takes 0.7271 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:28:26.2450267Z Autotune Choices Stats: 2025-09-07T11:28:26.2451430Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_30", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.023552000522613525, "best_triton_pos": 0} 2025-09-07T11:28:26.2497344Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T11:28:26.2497665Z strides: [448000, 80, 1], [1152, 1, 80] 2025-09-07T11:28:26.2497993Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:26.2498754Z triton_bmm_30 0.0236 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:28:26.2499948Z triton_bmm_33 0.0236 ms 100.0% 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=3, num_warps=4 2025-09-07T11:28:26.2501141Z triton_bmm_34 0.0236 ms 100.0% 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 2025-09-07T11:28:26.2502561Z triton_bmm_36 0.0236 ms 100.0% 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 2025-09-07T11:28:26.2503765Z triton_bmm_37 0.0236 ms 100.0% 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 2025-09-07T11:28:26.2504972Z triton_bmm_39 0.0236 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 2025-09-07T11:28:26.2506245Z triton_bmm_25 0.0246 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:28:26.2507429Z triton_bmm_27 0.0246 ms 95.8% 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 2025-09-07T11:28:26.2508620Z triton_bmm_28 0.0246 ms 95.8% 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=5, num_warps=4 2025-09-07T11:28:26.2509809Z triton_bmm_29 0.0246 ms 95.8% 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 2025-09-07T11:28:26.2510843Z SingleProcess AUTOTUNE benchmarking takes 0.2508 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:28:26.4963623Z Autotune Choices Stats: 2025-09-07T11:28:26.4964813Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_50", "best_kernel_desc": "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", "best_time": 0.02457600086927414, "best_triton_pos": 0} 2025-09-07T11:28:26.5010430Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T11:28:26.5010766Z strides: [80, 1120, 1], [1152, 1, 80] 2025-09-07T11:28:26.5011091Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:26.5011857Z triton_bmm_50 0.0246 ms 100.0% 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 2025-09-07T11:28:26.5013279Z triton_bmm_53 0.0246 ms 100.0% 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 2025-09-07T11:28:26.5014481Z triton_bmm_41 0.0256 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:28:26.5015670Z triton_bmm_43 0.0256 ms 96.0% 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 2025-09-07T11:28:26.5017136Z triton_bmm_44 0.0256 ms 96.0% 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 2025-09-07T11:28:26.5018316Z triton_bmm_46 0.0256 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:28:26.5019473Z triton_bmm_49 0.0256 ms 96.0% 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=3, num_warps=4 2025-09-07T11:28:26.5020657Z triton_bmm_52 0.0256 ms 96.0% 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 2025-09-07T11:28:26.5021854Z triton_bmm_45 0.0266 ms 92.3% 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 2025-09-07T11:28:26.5023192Z triton_bmm_48 0.0266 ms 92.3% 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 2025-09-07T11:28:26.5024223Z SingleProcess AUTOTUNE benchmarking takes 0.2507 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:28:27.0163126Z Autotune Choices Stats: 2025-09-07T11:28:27.0164583Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.07782399654388428, "best_triton_pos": 1, "best_triton_time": 0.08806400001049042, "best_triton_kernel": "triton_mm_73", "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"} 2025-09-07T11:28:27.0210350Z AUTOTUNE mm(4900x1280, 1280x1280) 2025-09-07T11:28:27.0210697Z strides: [1280, 1], [1, 1280] 2025-09-07T11:28:27.0210994Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:27.0211285Z mm 0.0778 ms 100.0% 2025-09-07T11:28:27.0211994Z triton_mm_73 0.0881 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=3, num_warps=4 2025-09-07T11:28:27.0213382Z triton_mm_68 0.0942 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 2025-09-07T11:28:27.0214574Z triton_mm_72 0.0973 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:28:27.0215750Z triton_mm_69 0.0983 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:28:27.0216927Z triton_mm_66 0.1075 ms 72.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:28:27.0218092Z triton_mm_74 0.1116 ms 69.7% 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 2025-09-07T11:28:27.0219272Z triton_mm_67 0.1147 ms 67.9% 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 2025-09-07T11:28:27.0220444Z triton_mm_70 0.1157 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=4, num_warps=8 2025-09-07T11:28:27.0221619Z triton_mm_71 0.1239 ms 62.8% 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 2025-09-07T11:28:27.0222880Z SingleProcess AUTOTUNE benchmarking takes 0.5195 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:28:27.7875737Z Autotune Choices Stats: 2025-09-07T11:28:27.7876966Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_751", "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": 0.20684799551963806, "best_triton_pos": 0} 2025-09-07T11:28:27.7924296Z AUTOTUNE addmm(4096x3840, 4096x1280, 1280x3840) 2025-09-07T11:28:27.7924674Z strides: [0, 1], [1280, 1], [1, 1280] 2025-09-07T11:28:27.7925036Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T11:28:27.7925854Z triton_mm_751 0.2068 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 2025-09-07T11:28:27.7927073Z triton_mm_750 0.2099 ms 98.5% 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 2025-09-07T11:28:27.7927826Z addmm 0.2140 ms 96.7% 2025-09-07T11:28:27.7928786Z triton_mm_747 0.2386 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=3, num_warps=4 2025-09-07T11:28:27.7929974Z triton_mm_746 0.2427 ms 85.2% 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 2025-09-07T11:28:27.7931154Z triton_mm_744 0.2540 ms 81.5% 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 2025-09-07T11:28:27.7932344Z triton_mm_752 0.2734 ms 75.7% 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 2025-09-07T11:28:27.7933835Z triton_mm_745 0.2929 ms 70.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:28:27.7935031Z triton_mm_748 0.3000 ms 68.9% 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 2025-09-07T11:28:27.7936214Z triton_mm_742 0.3205 ms 64.5% 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 2025-09-07T11:28:27.7937224Z SingleProcess AUTOTUNE benchmarking takes 0.7092 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:28:28.0775525Z Autotune Choices Stats: 2025-09-07T11:28:28.0776701Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_762", "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": 0.025599999353289604, "best_triton_pos": 0} 2025-09-07T11:28:28.0824814Z AUTOTUNE bmm(64x1024x80, 64x80x64) 2025-09-07T11:28:28.0825232Z strides: [81920, 80, 1], [5120, 1, 80] 2025-09-07T11:28:28.0825542Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:28.0826309Z triton_bmm_762 0.0256 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 2025-09-07T11:28:28.0827517Z triton_bmm_764 0.0256 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 2025-09-07T11:28:28.0828733Z triton_bmm_766 0.0256 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=3, num_warps=4 2025-09-07T11:28:28.0830181Z triton_bmm_767 0.0256 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 2025-09-07T11:28:28.0831402Z triton_bmm_759 0.0266 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 2025-09-07T11:28:28.0832579Z triton_bmm_763 0.0266 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=4, num_warps=8 2025-09-07T11:28:28.0833778Z triton_bmm_768 0.0266 ms 96.2% 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=2, num_warps=8 2025-09-07T11:28:28.0834995Z triton_bmm_769 0.0266 ms 96.2% 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 2025-09-07T11:28:28.0836196Z triton_bmm_758 0.0276 ms 92.6% 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=2, num_warps=4 2025-09-07T11:28:28.0837541Z triton_bmm_760 0.0276 ms 92.6% 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 2025-09-07T11:28:28.0838582Z SingleProcess AUTOTUNE benchmarking takes 0.2894 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:28:28.5369697Z Autotune Choices Stats: 2025-09-07T11:28:28.5371361Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.04710400104522705, "best_triton_kernel": "triton_convolution2d_3355", "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"} 2025-09-07T11:28:28.5419410Z AUTOTUNE convolution(1x1280x64x64, 256x1280x1x1) 2025-09-07T11:28:28.5419793Z strides: [5242880, 4096, 64, 1], [1280, 1, 1, 1] 2025-09-07T11:28:28.5420169Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:28.5420490Z convolution 0.0276 ms 100.0% 2025-09-07T11:28:28.5421374Z triton_convolution2d_3355 0.0471 ms 58.7% 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 2025-09-07T11:28:28.5422279Z conv1x1_via_mm 0.0492 ms 56.2% 2025-09-07T11:28:28.5423165Z triton_convolution2d_3357 0.0604 ms 45.8% 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 2025-09-07T11:28:28.5424678Z triton_convolution2d_3354 0.0635 ms 43.5% 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 2025-09-07T11:28:28.5426266Z triton_convolution2d_3356 0.0686 ms 40.3% 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 2025-09-07T11:28:28.5427762Z triton_convolution2d_3352 0.0758 ms 36.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:28:28.5429263Z triton_convolution2d_3351 0.0850 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 2025-09-07T11:28:28.5430762Z triton_convolution2d_3353 0.1270 ms 21.8% 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 2025-09-07T11:28:28.5432199Z SingleProcess AUTOTUNE benchmarking takes 0.1988 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T11:28:28.7952890Z Autotune Choices Stats: 2025-09-07T11:28:28.7954509Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.06143999844789505, "best_triton_pos": 1, "best_triton_time": 0.1372160017490387, "best_triton_kernel": "triton_convolution2d_3364", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:28:28.8000593Z AUTOTUNE convolution(1x256x64x64, 256x256x3x3) 2025-09-07T11:28:28.8000981Z strides: [1048576, 4096, 64, 1], [2304, 9, 3, 1] 2025-09-07T11:28:28.8001334Z dtypes: torch.float16, torch.float16 2025-09-07T11:28:28.8001661Z convolution 0.0614 ms 100.0% 2025-09-07T11:28:28.8002566Z triton_convolution2d_3364 0.1372 ms 44.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:28:28.8004277Z triton_convolution2d_3362 0.1597 ms 38.5% 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 2025-09-07T11:28:28.8005786Z triton_convolution2d_3361 0.1720 ms 35.7% 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 2025-09-07T11:28:28.8007301Z triton_convolution2d_3359 0.1761 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=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:28:28.8008811Z triton_convolution2d_3363 0.2488 ms 24.7% 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 2025-09-07T11:28:28.8010309Z triton_convolution2d_3358 0.2806 ms 21.9% 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 2025-09-07T11:28:28.8011812Z triton_convolution2d_3360 0.3656 ms 16.8% 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 2025-09-07T11:28:28.8013181Z SingleProcess AUTOTUNE benchmarking takes 0.2561 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:29:32.9293531Z Loading best configs from file /opt/conda/envs/py_3.10/lib/python3.10/site-packages/segment_anything_fast/configs/flash_4_configs_a100.p 2025-09-07T11:29:33.1219569Z 2025-09-07T11:29:33.1219830Z loading model: 0it [01:57, ?it/s] 2025-09-07T11:29:33.1271979Z cuda eval sam_fast 2025-09-07T11:29:37.1513675Z skipping cudagraphs due to cpp wrapper enabled 2025-09-07T11:32:46.9485425Z pass 2025-09-07T11:32:55.3246927Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:32:55.3249458Z import pynvml # type: ignore[import] 2025-09-07T11:32:58.1417213Z 2025-09-07T11:32:59.2092245Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:32:59.2093201Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:32:59.2163475Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:33:22.1727130Z pass 2025-09-07T11:33:24.8804206Z accuracy pass_rate=93.33% 2025-09-07T11:33:24.8815761Z calls_captured gmean=0.00x mean=409.467x 2025-09-07T11:33:24.8823092Z unique_graphs gmean=0.00x mean=0.867x 2025-09-07T11:33:24.8829881Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:33:24.8837499Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:33:24.8844258Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:33:24.8851193Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:33:24.8858677Z cudagraph_skips gmean=nanx mean=-0.067x 2025-09-07T11:33:24.8860768Z compilation_latency mean=28.134 seconds 2025-09-07T11:33:25.9015880Z + [[ 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* ]] 2025-09-07T11:33:25.9017408Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T11:33:25.9019005Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 6 --partition-id 4 --freezing --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:33:26.5078692Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:33:26.5080215Z import pynvml # type: ignore[import] 2025-09-07T11:33:30.7855300Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:33:30.7858039Z import pynvml # type: ignore[import] 2025-09-07T11:33:33.7445286Z 2025-09-07T11:33:34.6048927Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:33:34.6049325Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:33:34.6076163Z cuda eval phlippe_resnet 2025-09-07T11:33:43.1579118Z pass 2025-09-07T11:33:46.5928138Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:33:46.5930836Z import pynvml # type: ignore[import] 2025-09-07T11:33:49.7197743Z 2025-09-07T11:33:50.3397146Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:33:50.3397533Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:33:50.3397985Z cuda eval pyhpc_equation_of_state 2025-09-07T11:33:57.9620854Z pass 2025-09-07T11:34:00.8360206Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:34:00.8361675Z import pynvml # type: ignore[import] 2025-09-07T11:34:03.8168282Z 2025-09-07T11:34:04.2301866Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:34:04.2302252Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:34:04.2305936Z cuda eval pyhpc_isoneutral_mixing 2025-09-07T11:34:16.7212595Z skipping cudagraphs due to mutated inputs (7 instances). Found from : 2025-09-07T11:34:16.7214356Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:34:16.7215417Z return mod(*inputs) 2025-09-07T11:34:16.7216363Z File "/torchbench/torchbenchmark/models/pyhpc_isoneutral_mixing/__init__.py", line 100, in forward 2025-09-07T11:34:16.7217559Z return isoneutral_pytorch.isoneutral_diffusion_pre( 2025-09-07T11:34:16.7219639Z File "/torchbench/torchbenchmark/models/pyhpc_isoneutral_mixing/isoneutral_pytorch.py", line 164, in isoneutral_diffusion_pre 2025-09-07T11:34:16.7221065Z Ai_ez[1:-2, 2:-2, ki:, ip, kr] = taper * sxe * maskU[1:-2, 2:-2, ki:] 2025-09-07T11:34:16.7221610Z 2025-09-07T11:34:16.7555248Z pass 2025-09-07T11:34:19.7301471Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:34:19.7302903Z import pynvml # type: ignore[import] 2025-09-07T11:34:22.5576084Z 2025-09-07T11:34:23.4376865Z loading model: 0it [00:00, ?it/s]WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:34:23.5908161Z 2025-09-07T11:34:23.5908502Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:34:23.5909169Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:34:23.5909808Z cuda eval pyhpc_turbulent_kinetic_energy 2025-09-07T11:34:23.6118291Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:34:44.5345882Z pass 2025-09-07T11:34:47.7843326Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:34:47.7846952Z import pynvml # type: ignore[import] 2025-09-07T11:34:50.6441148Z 2025-09-07T11:34:51.5579654Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:34:51.5580254Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:34:51.5595090Z cuda eval pytorch_CycleGAN_and_pix2pix 2025-09-07T11:35:01.7903790Z pass 2025-09-07T11:35:04.6773170Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:35:04.6774606Z import pynvml # type: ignore[import] 2025-09-07T11:35:07.3965584Z 2025-09-07T11:35:08.5942281Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:08.5943079Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:35:08.5964721Z cuda eval pytorch_stargan 2025-09-07T11:35:20.4032495Z pass 2025-09-07T11:35:23.3778112Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:35:23.3779574Z import pynvml # type: ignore[import] 2025-09-07T11:35:26.2395710Z 2025-09-07T11:35:27.2162899Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:27.2163276Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:27.2187503Z cuda eval pytorch_unet 2025-09-07T11:35:40.2657246Z pass 2025-09-07T11:35:43.2684796Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:35:43.2686239Z import pynvml # type: ignore[import] 2025-09-07T11:35:46.2181362Z 2025-09-07T11:35:48.2764673Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:48.2765057Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:35:48.2949630Z cuda eval resnet152 2025-09-07T11:36:16.7443830Z pass 2025-09-07T11:36:19.9008617Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:19.9016546Z import pynvml # type: ignore[import] 2025-09-07T11:36:22.6512307Z 2025-09-07T11:36:23.8087522Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:36:23.8087915Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:36:23.8115097Z cuda eval resnet18 2025-09-07T11:36:32.6697339Z pass 2025-09-07T11:36:35.7890997Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:35.7892449Z import pynvml # type: ignore[import] 2025-09-07T11:36:38.6191430Z 2025-09-07T11:36:40.0746470Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:36:40.0747114Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:36:40.0811294Z cuda eval resnet50 2025-09-07T11:36:53.7511671Z pass 2025-09-07T11:36:56.7604128Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:56.7605606Z import pynvml # type: ignore[import] 2025-09-07T11:36:59.4883672Z 2025-09-07T11:36:59.6524224Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:36:59.6524608Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:36:59.6524946Z cuda eval resnet50_quantized_qat 2025-09-07T11:36:59.6530964Z Traceback (most recent call last): 2025-09-07T11:36:59.6531552Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:36:59.6532099Z ) = runner.load_model( 2025-09-07T11:36:59.6532618Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:36:59.6533404Z benchmark = benchmark_cls( 2025-09-07T11:36:59.6533847Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:36:59.6534319Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:36:59.6534908Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:36:59.6535599Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:36:59.6536079Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:36:59.6536373Z 2025-09-07T11:36:59.6536463Z model_fail_to_load 2025-09-07T11:37:01.2875217Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:37:01.2876684Z import pynvml # type: ignore[import] 2025-09-07T11:37:04.1699097Z 2025-09-07T11:37:05.7023679Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:37:05.7024055Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:37:05.7086324Z cuda eval resnext50_32x4d 2025-09-07T11:37:19.3114340Z pass 2025-09-07T11:37:22.4904074Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:37:22.4905580Z import pynvml # type: ignore[import] 2025-09-07T11:37:25.3908589Z 2025-09-07T11:37:33.6433293Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:37:33.6433655Z loading model: 0it [00:08, ?it/s] 2025-09-07T11:37:33.6560223Z cuda eval sam 2025-09-07T11:38:31.9611713Z pass 2025-09-07T11:38:36.3965180Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:38:36.3966628Z import pynvml # type: ignore[import] 2025-09-07T11:38:39.2791859Z 2025-09-07T11:40:05.3927398Z loading model: 0it [00:00, ?it/s]Loading best configs from file /opt/conda/envs/py_3.10/lib/python3.10/site-packages/segment_anything_fast/configs/flash_4_configs_a100.p 2025-09-07T11:40:11.5511755Z 2025-09-07T11:40:11.5512188Z loading model: 0it [01:32, ?it/s] 2025-09-07T11:40:11.5563405Z cuda eval sam_fast 2025-09-07T11:42:58.7308234Z pass 2025-09-07T11:43:03.3436401Z accuracy pass_rate=92.86% 2025-09-07T11:43:03.3447519Z calls_captured gmean=0.00x mean=419.357x 2025-09-07T11:43:03.3454160Z unique_graphs gmean=0.00x mean=0.857x 2025-09-07T11:43:03.3460639Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:43:03.3466807Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:43:03.3472779Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:43:03.3479201Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:43:03.3485256Z cudagraph_skips gmean=0.00x mean=0.071x 2025-09-07T11:43:03.3487224Z compilation_latency mean=17.558 seconds 2025-09-07T11:43:04.3640040Z + [[ 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* ]] 2025-09-07T11:43:04.3641594Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T11:43:04.3641932Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T11:43:04.3643549Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 6 --partition-id 4 --freezing --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:43:04.9751181Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:43:04.9753782Z import pynvml # type: ignore[import] 2025-09-07T11:43:08.7080147Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:43:08.7081565Z import pynvml # type: ignore[import] 2025-09-07T11:43:11.3787468Z 2025-09-07T11:43:12.1924447Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:12.1924963Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:12.1950843Z cuda eval phlippe_resnet 2025-09-07T11:43:20.3144684Z Autotune Choices Stats: 2025-09-07T11:43:20.3146178Z {"num_choices": 6, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_0", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T11:43:20.3205813Z AUTOTUNE convolution(4x3x32x32, 16x3x3x3) 2025-09-07T11:43:20.3206234Z strides: [3072, 1, 96, 3], [27, 1, 9, 3] 2025-09-07T11:43:20.3206582Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:20.3207516Z triton_convolution2d_0 0.0082 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.3209443Z triton_convolution2d_3 0.0092 ms 88.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.3210939Z triton_convolution2d_4 0.0102 ms 80.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.3211853Z convolution 0.0113 ms 72.7% 2025-09-07T11:43:20.3212730Z triton_convolution2d_1 0.0113 ms 72.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.3214574Z triton_convolution2d_2 0.0184 ms 44.4% 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 2025-09-07T11:43:20.3215760Z SingleProcess AUTOTUNE benchmarking takes 0.0982 seconds and 0.0002 seconds precompiling for 6 choices 2025-09-07T11:43:20.4091491Z Autotune Choices Stats: 2025-09-07T11:43:20.4093735Z {"num_choices": 6, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:43:20.4142982Z AUTOTUNE convolution(4x16x32x32, 16x16x3x3) 2025-09-07T11:43:20.4143407Z strides: [16384, 1, 512, 16], [144, 1, 48, 16] 2025-09-07T11:43:20.4143767Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:20.4144692Z triton_convolution2d_5 0.0113 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.4146328Z triton_convolution2d_6 0.0123 ms 91.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.4147238Z convolution 0.0133 ms 84.6% 2025-09-07T11:43:20.4148113Z triton_convolution2d_8 0.0133 ms 84.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.4149597Z triton_convolution2d_9 0.0143 ms 78.6% 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=2, num_warps=8 2025-09-07T11:43:20.4151083Z triton_convolution2d_7 0.0184 ms 61.1% 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 2025-09-07T11:43:20.4152263Z SingleProcess AUTOTUNE benchmarking takes 0.0939 seconds and 0.0003 seconds precompiling for 6 choices 2025-09-07T11:43:20.5247089Z Autotune Choices Stats: 2025-09-07T11:43:20.5248934Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_35", "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=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:43:20.5298673Z AUTOTUNE convolution(4x16x32x32, 32x16x3x3) 2025-09-07T11:43:20.5299350Z strides: [16384, 1, 512, 16], [144, 1, 48, 16] 2025-09-07T11:43:20.5312002Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:20.5313532Z triton_convolution2d_35 0.0113 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=4 2025-09-07T11:43:20.5315439Z triton_convolution2d_39 0.0113 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 2025-09-07T11:43:20.5316943Z triton_convolution2d_38 0.0123 ms 91.7% 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 2025-09-07T11:43:20.5317868Z convolution 0.0133 ms 84.6% 2025-09-07T11:43:20.5318742Z triton_convolution2d_36 0.0133 ms 84.6% 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 2025-09-07T11:43:20.5320379Z triton_convolution2d_40 0.0143 ms 78.6% 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 2025-09-07T11:43:20.5322104Z triton_convolution2d_37 0.0205 ms 55.0% 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:43:20.5323399Z SingleProcess AUTOTUNE benchmarking takes 0.1079 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:43:20.6524460Z Autotune Choices Stats: 2025-09-07T11:43:20.6526182Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010239999741315842, "best_triton_pos": 1, "best_triton_time": 0.01228800043463707, "best_triton_kernel": "triton_convolution2d_45", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:43:20.6591961Z AUTOTUNE convolution(4x32x16x16, 32x32x3x3) 2025-09-07T11:43:20.6592402Z strides: [8192, 1, 512, 32], [288, 1, 96, 32] 2025-09-07T11:43:20.6592748Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:20.6593102Z convolution 0.0102 ms 100.0% 2025-09-07T11:43:20.6593998Z triton_convolution2d_45 0.0123 ms 83.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.6595485Z triton_convolution2d_46 0.0123 ms 83.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.6596970Z triton_convolution2d_44 0.0133 ms 76.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.6598464Z triton_convolution2d_41 0.0154 ms 66.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.6599943Z triton_convolution2d_47 0.0154 ms 66.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.6601424Z triton_convolution2d_42 0.0184 ms 55.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.6602904Z triton_convolution2d_43 0.0297 ms 34.5% 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 2025-09-07T11:43:20.6604439Z SingleProcess AUTOTUNE benchmarking takes 0.1285 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:43:20.7644393Z Autotune Choices Stats: 2025-09-07T11:43:20.7645799Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_48", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, 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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:43:20.7697491Z AUTOTUNE convolution(4x16x32x32, 32x16x1x1) 2025-09-07T11:43:20.7698001Z strides: [16384, 1, 512, 16], [16, 1, 1, 1] 2025-09-07T11:43:20.7698363Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:20.7699285Z triton_convolution2d_48 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, 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 2025-09-07T11:43:20.7700812Z triton_convolution2d_49 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, 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 2025-09-07T11:43:20.7702671Z triton_convolution2d_51 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, 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 2025-09-07T11:43:20.7704166Z triton_convolution2d_52 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, 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 2025-09-07T11:43:20.7705792Z triton_convolution2d_53 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, 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 2025-09-07T11:43:20.7707284Z triton_convolution2d_50 0.0092 ms 77.8% 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 2025-09-07T11:43:20.7708192Z convolution 0.0113 ms 63.6% 2025-09-07T11:43:20.7708740Z SingleProcess AUTOTUNE benchmarking takes 0.1076 seconds and 0.0004 seconds precompiling for 7 choices 2025-09-07T11:43:20.8986855Z Autotune Choices Stats: 2025-09-07T11:43:20.8988559Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011264000087976456, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "best_triton_kernel": "triton_convolution2d_86", "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"} 2025-09-07T11:43:20.9039820Z AUTOTUNE convolution(4x32x16x16, 64x32x3x3) 2025-09-07T11:43:20.9040228Z strides: [8192, 1, 512, 32], [288, 1, 96, 32] 2025-09-07T11:43:20.9040577Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:20.9040897Z convolution 0.0113 ms 100.0% 2025-09-07T11:43:20.9041795Z triton_convolution2d_86 0.0133 ms 84.6% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.9043275Z triton_convolution2d_87 0.0133 ms 84.6% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.9044739Z triton_convolution2d_85 0.0154 ms 73.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.9046212Z triton_convolution2d_82 0.0164 ms 68.8% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:43:20.9047937Z triton_convolution2d_88 0.0184 ms 61.1% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:20.9049410Z triton_convolution2d_83 0.0236 ms 47.8% 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 2025-09-07T11:43:20.9050888Z triton_convolution2d_84 0.0266 ms 42.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:43:20.9052058Z SingleProcess AUTOTUNE benchmarking takes 0.1264 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:43:21.0246563Z Autotune Choices Stats: 2025-09-07T11:43:21.0248650Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011264000087976456, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "best_triton_kernel": "triton_convolution2d_93", "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"} 2025-09-07T11:43:21.0297088Z AUTOTUNE convolution(4x64x8x8, 64x64x3x3) 2025-09-07T11:43:21.0297439Z strides: [4096, 1, 512, 64], [576, 1, 192, 64] 2025-09-07T11:43:21.0297794Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:21.0298118Z convolution 0.0113 ms 100.0% 2025-09-07T11:43:21.0298996Z triton_convolution2d_93 0.0195 ms 57.9% 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 2025-09-07T11:43:21.0300491Z triton_convolution2d_94 0.0205 ms 55.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:43:21.0301965Z triton_convolution2d_92 0.0225 ms 50.0% 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 2025-09-07T11:43:21.0303444Z triton_convolution2d_89 0.0256 ms 44.0% 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 2025-09-07T11:43:21.0304923Z triton_convolution2d_91 0.0287 ms 39.3% 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 2025-09-07T11:43:21.0306508Z triton_convolution2d_95 0.0317 ms 35.5% 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 2025-09-07T11:43:21.0307997Z triton_convolution2d_90 0.0379 ms 29.7% 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 2025-09-07T11:43:21.1366040Z SingleProcess AUTOTUNE benchmarking takes 0.1249 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:43:21.1366641Z Autotune Choices Stats: 2025-09-07T11:43:21.1367884Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_96", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:43:21.1416459Z AUTOTUNE convolution(4x32x16x16, 64x32x1x1) 2025-09-07T11:43:21.1416854Z strides: [8192, 1, 512, 32], [32, 1, 1, 1] 2025-09-07T11:43:21.1417189Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:43:21.1418115Z triton_convolution2d_96 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:43:21.1419594Z triton_convolution2d_99 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:43:21.1421065Z triton_convolution2d_100 0.0072 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 2025-09-07T11:43:21.1422546Z triton_convolution2d_101 0.0072 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:43:21.1424242Z triton_convolution2d_102 0.0082 ms 87.5% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:43:21.1425819Z triton_convolution2d_97 0.0092 ms 77.8% 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 2025-09-07T11:43:21.1427308Z triton_convolution2d_98 0.0092 ms 77.8% 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 2025-09-07T11:43:21.1428223Z convolution 0.0102 ms 70.0% 2025-09-07T11:43:21.1428786Z SingleProcess AUTOTUNE benchmarking takes 0.1110 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:43:21.3211254Z Autotune Choices Stats: 2025-09-07T11:43:21.3212393Z {"num_choices": 12, "num_triton_choices": 10, "best_kernel": "triton_mm_140", "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=4, num_warps=1", "best_time": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T11:43:21.3263939Z AUTOTUNE addmm(4x10, 4x64, 64x10) 2025-09-07T11:43:21.3264279Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:43:21.3264645Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:43:21.3265528Z triton_mm_140 0.0061 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=4, num_warps=1 2025-09-07T11:43:21.3266708Z triton_mm_131 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=1 2025-09-07T11:43:21.3267904Z triton_mm_132 0.0072 ms 85.7% 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=2, num_warps=1 2025-09-07T11:43:21.3269079Z triton_mm_133 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T11:43:21.3270244Z triton_mm_134 0.0072 ms 85.7% 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 2025-09-07T11:43:21.3271406Z triton_mm_136 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T11:43:21.3272799Z triton_mm_137 0.0072 ms 85.7% 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 2025-09-07T11:43:21.3273977Z triton_mm_138 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T11:43:21.3275150Z triton_mm_139 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T11:43:21.3275880Z bias_addmm 0.0082 ms 75.0% 2025-09-07T11:43:21.3276442Z SingleProcess AUTOTUNE benchmarking takes 0.1774 seconds and 0.0002 seconds precompiling for 12 choices 2025-09-07T11:43:22.6345789Z pass 2025-09-07T11:43:25.8842176Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:43:25.8843626Z import pynvml # type: ignore[import] 2025-09-07T11:43:28.7857158Z 2025-09-07T11:43:29.2441068Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:29.2441905Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:29.2442266Z cuda eval pyhpc_equation_of_state 2025-09-07T11:43:36.8154930Z pass 2025-09-07T11:43:39.8043656Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:43:39.8045097Z import pynvml # type: ignore[import] 2025-09-07T11:43:42.6191813Z 2025-09-07T11:43:43.0078745Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:43.0079093Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:43.0083372Z cuda eval pyhpc_isoneutral_mixing 2025-09-07T11:43:55.4501481Z skipping cudagraphs due to mutated inputs (7 instances). Found from : 2025-09-07T11:43:55.4502254Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:43:55.4502865Z return mod(*inputs) 2025-09-07T11:43:55.4503398Z File "/torchbench/torchbenchmark/models/pyhpc_isoneutral_mixing/__init__.py", line 100, in forward 2025-09-07T11:43:55.4504038Z return isoneutral_pytorch.isoneutral_diffusion_pre( 2025-09-07T11:43:55.4504813Z File "/torchbench/torchbenchmark/models/pyhpc_isoneutral_mixing/isoneutral_pytorch.py", line 164, in isoneutral_diffusion_pre 2025-09-07T11:43:55.4505677Z Ai_ez[1:-2, 2:-2, ki:, ip, kr] = taper * sxe * maskU[1:-2, 2:-2, ki:] 2025-09-07T11:43:55.4505964Z 2025-09-07T11:43:55.4852093Z pass 2025-09-07T11:43:58.5575411Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:43:58.5576886Z import pynvml # type: ignore[import] 2025-09-07T11:44:01.2299678Z 2025-09-07T11:44:02.0926004Z loading model: 0it [00:00, ?it/s]WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:44:02.2475831Z 2025-09-07T11:44:02.2476165Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:44:02.2476804Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:44:02.2477444Z cuda eval pyhpc_turbulent_kinetic_energy 2025-09-07T11:44:02.2689067Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:44:26.3067195Z pass 2025-09-07T11:44:29.7060319Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:29.7063868Z import pynvml # type: ignore[import] 2025-09-07T11:44:32.4586228Z 2025-09-07T11:44:33.3117221Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:44:33.3117583Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:44:33.3132457Z cuda eval pytorch_CycleGAN_and_pix2pix 2025-09-07T11:44:42.4758397Z Autotune Choices Stats: 2025-09-07T11:44:42.4760090Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.11878400295972824, "best_triton_pos": 1, "best_triton_time": 0.13414399325847626, "best_triton_kernel": "triton_convolution2d_151", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:44:42.4809757Z AUTOTUNE convolution(1x64x262x262, 3x64x7x7) 2025-09-07T11:44:42.4810178Z strides: [4393216, 1, 16768, 64], [3136, 1, 448, 64] 2025-09-07T11:44:42.4810533Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:44:42.4810862Z convolution 0.1188 ms 100.0% 2025-09-07T11:44:42.4812171Z triton_convolution2d_151 0.1341 ms 88.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:42.4813891Z triton_convolution2d_150 0.1526 ms 77.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:42.4815399Z triton_convolution2d_149 0.1618 ms 73.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:42.4816905Z triton_convolution2d_147 0.1997 ms 59.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:42.4818395Z triton_convolution2d_146 0.2324 ms 51.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:42.4819871Z triton_convolution2d_148 0.2908 ms 40.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:44:42.4821052Z SingleProcess AUTOTUNE benchmarking takes 0.2278 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T11:44:43.2085245Z Autotune Choices Stats: 2025-09-07T11:44:43.2086967Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.09830400347709656, "best_triton_pos": 1, "best_triton_time": 0.11776000261306763, "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=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:44:43.2151936Z AUTOTUNE convolution(1x3x262x262, 64x3x7x7) 2025-09-07T11:44:43.2152333Z strides: [205932, 1, 786, 3], [147, 1, 21, 3] 2025-09-07T11:44:43.2152681Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:44:43.2152991Z convolution 0.0983 ms 100.0% 2025-09-07T11:44:43.2153864Z triton_convolution2d_0 0.1178 ms 83.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.2155336Z triton_convolution2d_3 0.1219 ms 80.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.2157167Z triton_convolution2d_4 0.1260 ms 78.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.2158642Z triton_convolution2d_5 0.1556 ms 63.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.2160127Z triton_convolution2d_2 0.1864 ms 52.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:44:43.2161616Z triton_convolution2d_1 0.2447 ms 40.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.2162784Z SingleProcess AUTOTUNE benchmarking takes 0.2053 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:44:43.3579659Z Autotune Choices Stats: 2025-09-07T11:44:43.3581206Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_10", "best_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", "best_time": 0.03276799991726875, "best_triton_pos": 0} 2025-09-07T11:44:43.3630842Z AUTOTUNE convolution(1x64x256x256, 128x64x3x3) 2025-09-07T11:44:43.3631276Z strides: [4194304, 1, 16384, 64], [576, 1, 192, 64] 2025-09-07T11:44:43.3631638Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:44:43.3632574Z triton_convolution2d_10 0.0328 ms 100.0% 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 2025-09-07T11:44:43.3633528Z convolution 0.0338 ms 97.0% 2025-09-07T11:44:43.3634422Z triton_convolution2d_9 0.0369 ms 88.9% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.3635919Z triton_convolution2d_12 0.0389 ms 84.2% 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 2025-09-07T11:44:43.3637408Z triton_convolution2d_11 0.0451 ms 72.7% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.3638888Z triton_convolution2d_6 0.0461 ms 71.1% 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 2025-09-07T11:44:43.3640362Z triton_convolution2d_7 0.0471 ms 69.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.3641840Z triton_convolution2d_8 0.1270 ms 25.8% 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 2025-09-07T11:44:43.3643016Z SingleProcess AUTOTUNE benchmarking takes 0.1468 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:44:43.5166267Z Autotune Choices Stats: 2025-09-07T11:44:43.5167926Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.03891199827194214, "best_triton_kernel": "triton_convolution2d_17", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:44:43.5216354Z AUTOTUNE convolution(1x128x128x128, 256x128x3x3) 2025-09-07T11:44:43.5216788Z strides: [2097152, 1, 16384, 128], [1152, 1, 384, 128] 2025-09-07T11:44:43.5217153Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:44:43.5217481Z convolution 0.0266 ms 100.0% 2025-09-07T11:44:43.5218364Z triton_convolution2d_17 0.0389 ms 68.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.5219861Z triton_convolution2d_16 0.0563 ms 47.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.5221361Z triton_convolution2d_19 0.0584 ms 45.6% 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 2025-09-07T11:44:43.5223066Z triton_convolution2d_18 0.0625 ms 42.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.5224563Z triton_convolution2d_14 0.0748 ms 35.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.5226115Z triton_convolution2d_13 0.0778 ms 34.2% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.5227615Z triton_convolution2d_15 0.1270 ms 21.0% 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:44:43.5228797Z SingleProcess AUTOTUNE benchmarking takes 0.1580 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:44:43.7179506Z Autotune Choices Stats: 2025-09-07T11:44:43.7181165Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.04095999896526337, "best_triton_pos": 1, "best_triton_time": 0.06860800087451935, "best_triton_kernel": "triton_convolution2d_24", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:44:43.7229952Z AUTOTUNE convolution(1x256x66x66, 256x256x3x3) 2025-09-07T11:44:43.7230389Z strides: [1115136, 1, 16896, 256], [2304, 1, 768, 256] 2025-09-07T11:44:43.7230778Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:44:43.7231096Z convolution 0.0410 ms 100.0% 2025-09-07T11:44:43.7231979Z triton_convolution2d_24 0.0686 ms 59.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.7233471Z triton_convolution2d_26 0.1014 ms 40.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.7234968Z triton_convolution2d_23 0.1024 ms 40.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.7236458Z triton_convolution2d_25 0.1075 ms 38.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:44:43.7238175Z triton_convolution2d_21 0.1341 ms 30.5% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.7239657Z triton_convolution2d_20 0.1444 ms 28.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:44:43.7241143Z triton_convolution2d_22 0.2376 ms 17.2% 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=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:44:43.7242317Z SingleProcess AUTOTUNE benchmarking takes 0.2005 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:44:46.5251626Z pass 2025-09-07T11:44:49.7444625Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:49.7446102Z import pynvml # type: ignore[import] 2025-09-07T11:44:52.5027807Z 2025-09-07T11:44:53.7184820Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:44:53.7185273Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:44:53.7206226Z cuda eval pytorch_stargan 2025-09-07T11:45:04.7641922Z Autotune Choices Stats: 2025-09-07T11:45:04.7643603Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.374783992767334, "best_triton_pos": 1, "best_triton_time": 0.4362240135669708, "best_triton_kernel": "triton_convolution2d_108", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:45:04.7699819Z AUTOTUNE convolution(16x64x128x128, 3x64x7x7) 2025-09-07T11:45:04.7700200Z strides: [1048576, 1, 8192, 64], [3136, 1, 448, 64] 2025-09-07T11:45:04.7700572Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:04.7700898Z convolution 0.3748 ms 100.0% 2025-09-07T11:45:04.7701780Z triton_convolution2d_108 0.4362 ms 85.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:04.7703282Z triton_convolution2d_109 0.4577 ms 81.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:04.7704783Z triton_convolution2d_107 0.4639 ms 80.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:04.7706368Z triton_convolution2d_105 0.5898 ms 63.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:04.7707861Z triton_convolution2d_104 0.8356 ms 44.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:04.7709341Z triton_convolution2d_106 0.8745 ms 42.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:04.7710525Z SingleProcess AUTOTUNE benchmarking takes 0.2807 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:45:05.8767002Z Autotune Choices Stats: 2025-09-07T11:45:05.8768396Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.23244799673557281, "best_triton_pos": 0} 2025-09-07T11:45:05.8820220Z AUTOTUNE convolution(16x8x128x128, 64x8x7x7) 2025-09-07T11:45:05.8820636Z strides: [131072, 1, 1024, 8], [392, 1, 56, 8] 2025-09-07T11:45:05.8820980Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:05.8821908Z triton_convolution2d_5 0.2324 ms 100.0% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:05.8822829Z convolution 0.2406 ms 96.6% 2025-09-07T11:45:05.8823705Z triton_convolution2d_1 0.2570 ms 90.4% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:05.8825623Z triton_convolution2d_3 0.2591 ms 89.7% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:05.8827111Z triton_convolution2d_4 0.3891 ms 59.7% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:05.8828559Z triton_convolution2d_0 0.4096 ms 56.8% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:05.8830040Z triton_convolution2d_2 0.5161 ms 45.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:05.8831218Z SingleProcess AUTOTUNE benchmarking takes 0.2865 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:45:06.1232849Z Autotune Choices Stats: 2025-09-07T11:45:06.1234515Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.09728000313043594, "best_triton_pos": 1, "best_triton_time": 0.1454080045223236, "best_triton_kernel": "triton_convolution2d_9", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:45:06.1284649Z AUTOTUNE convolution(16x64x128x128, 128x64x4x4) 2025-09-07T11:45:06.1285073Z strides: [1048576, 1, 8192, 64], [1024, 1, 256, 64] 2025-09-07T11:45:06.1285429Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:06.1285773Z convolution 0.0973 ms 100.0% 2025-09-07T11:45:06.1286673Z triton_convolution2d_9 0.1454 ms 66.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.1288174Z triton_convolution2d_11 0.1516 ms 64.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.1289654Z triton_convolution2d_12 0.1669 ms 58.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.1291132Z triton_convolution2d_10 0.1751 ms 55.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.1293150Z triton_convolution2d_6 0.1997 ms 48.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.1294621Z triton_convolution2d_7 0.2171 ms 44.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.1296104Z triton_convolution2d_8 0.5837 ms 16.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:06.1297274Z SingleProcess AUTOTUNE benchmarking takes 0.2459 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:06.3818988Z Autotune Choices Stats: 2025-09-07T11:45:06.3820907Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.09523200243711472, "best_triton_pos": 1, "best_triton_time": 0.13926400244235992, "best_triton_kernel": "triton_convolution2d_17", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:45:06.3871692Z AUTOTUNE convolution(16x128x64x64, 256x128x4x4) 2025-09-07T11:45:06.3872431Z strides: [524288, 1, 8192, 128], [2048, 1, 512, 128] 2025-09-07T11:45:06.3873077Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:06.3873657Z convolution 0.0952 ms 100.0% 2025-09-07T11:45:06.3875310Z triton_convolution2d_17 0.1393 ms 68.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.3878156Z triton_convolution2d_16 0.1741 ms 54.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.3881045Z triton_convolution2d_19 0.1823 ms 52.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.3883895Z triton_convolution2d_18 0.1833 ms 52.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.3886733Z triton_convolution2d_14 0.2437 ms 39.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.3889603Z triton_convolution2d_13 0.2488 ms 38.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.3892492Z triton_convolution2d_15 0.6185 ms 15.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:06.3894991Z SingleProcess AUTOTUNE benchmarking takes 0.2577 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:06.6495733Z Autotune Choices Stats: 2025-09-07T11:45:06.6497423Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.09318400174379349, "best_triton_pos": 1, "best_triton_time": 0.16383999586105347, "best_triton_kernel": "triton_convolution2d_24", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:45:06.6548332Z AUTOTUNE convolution(16x256x32x32, 256x256x3x3) 2025-09-07T11:45:06.6548724Z strides: [262144, 1, 8192, 256], [2304, 1, 768, 256] 2025-09-07T11:45:06.6549095Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:06.6549423Z convolution 0.0932 ms 100.0% 2025-09-07T11:45:06.6550320Z triton_convolution2d_24 0.1638 ms 56.9% 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 2025-09-07T11:45:06.6551820Z triton_convolution2d_23 0.1853 ms 50.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.6553314Z triton_convolution2d_25 0.2007 ms 46.4% 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 2025-09-07T11:45:06.6554788Z triton_convolution2d_26 0.2017 ms 46.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:06.6556510Z triton_convolution2d_21 0.2591 ms 36.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.6558001Z triton_convolution2d_20 0.2826 ms 33.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:06.6559501Z triton_convolution2d_22 0.6820 ms 13.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:06.6560685Z SingleProcess AUTOTUNE benchmarking takes 0.2667 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:08.6106386Z pass 2025-09-07T11:45:11.6101894Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:45:11.6103339Z import pynvml # type: ignore[import] 2025-09-07T11:45:14.4694034Z 2025-09-07T11:45:15.4389851Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:45:15.4390241Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:45:15.4413166Z cuda eval pytorch_unet 2025-09-07T11:45:27.6082892Z Autotune Choices Stats: 2025-09-07T11:45:27.6084261Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_0", "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": 0.4505600035190582, "best_triton_pos": 0} 2025-09-07T11:45:27.6147782Z AUTOTUNE convolution(2x3x640x959, 64x3x3x3) 2025-09-07T11:45:27.6148237Z strides: [1841280, 1, 2877, 3], [27, 1, 9, 3] 2025-09-07T11:45:27.6148596Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:27.6149511Z triton_convolution2d_0 0.4506 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 2025-09-07T11:45:27.6151016Z triton_convolution2d_3 0.4680 ms 96.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:27.6151921Z convolution 0.4925 ms 91.5% 2025-09-07T11:45:27.6152783Z triton_convolution2d_4 0.5079 ms 88.7% 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=8 2025-09-07T11:45:27.6154612Z triton_convolution2d_5 0.6287 ms 71.7% 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=8 2025-09-07T11:45:27.6156096Z triton_convolution2d_2 0.6339 ms 71.1% 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 2025-09-07T11:45:27.6157590Z triton_convolution2d_1 0.7086 ms 63.6% 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 2025-09-07T11:45:27.6158747Z SingleProcess AUTOTUNE benchmarking takes 0.3465 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T11:45:27.9414944Z Autotune Choices Stats: 2025-09-07T11:45:27.9417437Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.4792320132255554, "best_triton_pos": 1, "best_triton_time": 0.7321599721908569, "best_triton_kernel": "triton_convolution2d_12", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:45:27.9475792Z AUTOTUNE convolution(2x64x640x959, 64x64x3x3) 2025-09-07T11:45:27.9476225Z strides: [39280640, 1, 61376, 64], [576, 1, 192, 64] 2025-09-07T11:45:27.9476600Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:27.9476914Z convolution 0.4792 ms 100.0% 2025-09-07T11:45:27.9477812Z triton_convolution2d_12 0.7322 ms 65.5% 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 2025-09-07T11:45:27.9479325Z triton_convolution2d_9 0.7854 ms 61.0% 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 2025-09-07T11:45:27.9480814Z triton_convolution2d_10 0.8714 ms 55.0% 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 2025-09-07T11:45:27.9482290Z triton_convolution2d_7 0.8765 ms 54.7% 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 2025-09-07T11:45:27.9483758Z triton_convolution2d_11 0.9728 ms 49.3% 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=8 2025-09-07T11:45:27.9485225Z triton_convolution2d_6 1.6835 ms 28.5% 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 2025-09-07T11:45:27.9486698Z triton_convolution2d_8 2.7894 ms 17.2% 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 2025-09-07T11:45:27.9487856Z SingleProcess AUTOTUNE benchmarking takes 0.3319 seconds and 0.0005 seconds precompiling for 8 choices 2025-09-07T11:45:28.2576400Z Autotune Choices Stats: 2025-09-07T11:45:28.2578105Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2467840015888214, "best_triton_pos": 1, "best_triton_time": 0.3031040132045746, "best_triton_kernel": "triton_convolution2d_16", "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"} 2025-09-07T11:45:28.2636517Z AUTOTUNE convolution(2x64x320x479, 128x64x3x3) 2025-09-07T11:45:28.2636961Z strides: [9809920, 1, 30656, 64], [576, 1, 192, 64] 2025-09-07T11:45:28.2637361Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:28.2637677Z convolution 0.2468 ms 100.0% 2025-09-07T11:45:28.2638582Z triton_convolution2d_16 0.3031 ms 81.4% 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 2025-09-07T11:45:28.2640084Z triton_convolution2d_18 0.3564 ms 69.3% 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 2025-09-07T11:45:28.2641778Z triton_convolution2d_19 0.3820 ms 64.6% 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 2025-09-07T11:45:28.2643675Z triton_convolution2d_17 0.4485 ms 55.0% 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 2025-09-07T11:45:28.2645248Z triton_convolution2d_14 0.4680 ms 52.7% 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 2025-09-07T11:45:28.2646812Z triton_convolution2d_13 0.5274 ms 46.8% 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 2025-09-07T11:45:28.2648379Z triton_convolution2d_15 1.4459 ms 17.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:28.2649629Z SingleProcess AUTOTUNE benchmarking takes 0.3149 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:45:28.5844764Z Autotune Choices Stats: 2025-09-07T11:45:28.5846505Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.39526399970054626, "best_triton_pos": 1, "best_triton_time": 0.6010879874229431, "best_triton_kernel": "triton_convolution2d_23", "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"} 2025-09-07T11:45:28.5901955Z AUTOTUNE convolution(2x128x320x479, 128x128x3x3) 2025-09-07T11:45:28.5902397Z strides: [19619840, 1, 61312, 128], [1152, 1, 384, 128] 2025-09-07T11:45:28.5902778Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:28.5903101Z convolution 0.3953 ms 100.0% 2025-09-07T11:45:28.5903989Z triton_convolution2d_23 0.6011 ms 65.8% 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 2025-09-07T11:45:28.5905556Z triton_convolution2d_26 0.7086 ms 55.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:28.5907037Z triton_convolution2d_24 0.7352 ms 53.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:28.5908515Z triton_convolution2d_25 0.7936 ms 49.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:28.5910326Z triton_convolution2d_21 0.9093 ms 43.5% 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 2025-09-07T11:45:28.5911820Z triton_convolution2d_20 1.0322 ms 38.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:28.5913291Z triton_convolution2d_22 2.9010 ms 13.6% 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 2025-09-07T11:45:28.5914463Z SingleProcess AUTOTUNE benchmarking takes 0.3257 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:45:28.8881454Z Autotune Choices Stats: 2025-09-07T11:45:28.8883424Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.21299199759960175, "best_triton_pos": 1, "best_triton_time": 0.32051199674606323, "best_triton_kernel": "triton_convolution2d_30", "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"} 2025-09-07T11:45:28.8936904Z AUTOTUNE convolution(2x128x160x239, 256x128x3x3) 2025-09-07T11:45:28.8937344Z strides: [4894720, 1, 30592, 128], [1152, 1, 384, 128] 2025-09-07T11:45:28.8937722Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:28.8938033Z convolution 0.2130 ms 100.0% 2025-09-07T11:45:28.8938932Z triton_convolution2d_30 0.3205 ms 66.5% 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 2025-09-07T11:45:28.8940435Z triton_convolution2d_32 0.3492 ms 61.0% 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 2025-09-07T11:45:28.8941939Z triton_convolution2d_33 0.3656 ms 58.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:28.8943419Z triton_convolution2d_31 0.4147 ms 51.4% 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 2025-09-07T11:45:28.8944892Z triton_convolution2d_28 0.4547 ms 46.8% 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 2025-09-07T11:45:28.8946428Z triton_convolution2d_27 0.4649 ms 45.8% 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 2025-09-07T11:45:28.8947926Z triton_convolution2d_29 1.4111 ms 15.1% 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 2025-09-07T11:45:28.8949084Z SingleProcess AUTOTUNE benchmarking takes 0.3025 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:45:29.2077990Z Autotune Choices Stats: 2025-09-07T11:45:29.2079631Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.37887999415397644, "best_triton_pos": 1, "best_triton_time": 0.6512640118598938, "best_triton_kernel": "triton_convolution2d_37", "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"} 2025-09-07T11:45:29.2133693Z AUTOTUNE convolution(2x256x160x239, 256x256x3x3) 2025-09-07T11:45:29.2134229Z strides: [9789440, 1, 61184, 256], [2304, 1, 768, 256] 2025-09-07T11:45:29.2134723Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:29.2135142Z convolution 0.3789 ms 100.0% 2025-09-07T11:45:29.2136365Z triton_convolution2d_37 0.6513 ms 58.2% 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 2025-09-07T11:45:29.2138320Z triton_convolution2d_39 0.6922 ms 54.7% 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 2025-09-07T11:45:29.2139792Z triton_convolution2d_38 0.7045 ms 53.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:29.2141269Z triton_convolution2d_40 0.7649 ms 49.5% 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 2025-09-07T11:45:29.2142962Z triton_convolution2d_34 0.8755 ms 43.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:29.2144444Z triton_convolution2d_35 0.9247 ms 41.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:29.2146019Z triton_convolution2d_36 3.6352 ms 10.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:29.2147192Z SingleProcess AUTOTUNE benchmarking takes 0.3188 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:29.5046034Z Autotune Choices Stats: 2025-09-07T11:45:29.5047705Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.1955839991569519, "best_triton_pos": 1, "best_triton_time": 0.3184640109539032, "best_triton_kernel": "triton_convolution2d_44", "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"} 2025-09-07T11:45:29.5104149Z AUTOTUNE convolution(2x256x80x119, 512x256x3x3) 2025-09-07T11:45:29.5104553Z strides: [2437120, 1, 30464, 256], [2304, 1, 768, 256] 2025-09-07T11:45:29.5104910Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:29.5105300Z convolution 0.1956 ms 100.0% 2025-09-07T11:45:29.5106182Z triton_convolution2d_44 0.3185 ms 61.4% 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 2025-09-07T11:45:29.5107692Z triton_convolution2d_45 0.3328 ms 58.8% 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 2025-09-07T11:45:29.5109173Z triton_convolution2d_46 0.3533 ms 55.4% 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 2025-09-07T11:45:29.5110657Z triton_convolution2d_47 0.3625 ms 54.0% 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 2025-09-07T11:45:29.5112138Z triton_convolution2d_42 0.4372 ms 44.7% 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 2025-09-07T11:45:29.5113854Z triton_convolution2d_41 0.4813 ms 40.6% 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 2025-09-07T11:45:29.5115355Z triton_convolution2d_43 1.3670 ms 14.3% 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 2025-09-07T11:45:29.5116524Z SingleProcess AUTOTUNE benchmarking takes 0.2962 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:29.8230175Z Autotune Choices Stats: 2025-09-07T11:45:29.8231794Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.36454400420188904, "best_triton_pos": 1, "best_triton_time": 0.6072319746017456, "best_triton_kernel": "triton_convolution2d_51", "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"} 2025-09-07T11:45:29.8290268Z AUTOTUNE convolution(2x512x80x119, 512x512x3x3) 2025-09-07T11:45:29.8290804Z strides: [4874240, 1, 60928, 512], [4608, 1, 1536, 512] 2025-09-07T11:45:29.8291289Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:29.8291722Z convolution 0.3645 ms 100.0% 2025-09-07T11:45:29.8293195Z triton_convolution2d_51 0.6072 ms 60.0% 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 2025-09-07T11:45:29.8295255Z triton_convolution2d_53 0.7025 ms 51.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:29.8297198Z triton_convolution2d_52 0.7045 ms 51.7% 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 2025-09-07T11:45:29.8298690Z triton_convolution2d_54 0.7332 ms 49.7% 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 2025-09-07T11:45:29.8300183Z triton_convolution2d_49 0.8622 ms 42.3% 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 2025-09-07T11:45:29.8301662Z triton_convolution2d_48 0.9677 ms 37.7% 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 2025-09-07T11:45:29.8303153Z triton_convolution2d_50 2.8109 ms 13.0% 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 2025-09-07T11:45:29.8304330Z SingleProcess AUTOTUNE benchmarking takes 0.3176 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:30.1109970Z Autotune Choices Stats: 2025-09-07T11:45:30.1111624Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.12390399724245071, "best_triton_pos": 1, "best_triton_time": 0.16486400365829468, "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=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:45:30.1168796Z AUTOTUNE convolution(2x512x40x59, 512x512x3x3) 2025-09-07T11:45:30.1169233Z strides: [1208320, 1, 30208, 512], [4608, 1, 1536, 512] 2025-09-07T11:45:30.1169876Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:30.1170204Z convolution 0.1239 ms 100.0% 2025-09-07T11:45:30.1171105Z triton_convolution2d_59 0.1649 ms 75.2% 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 2025-09-07T11:45:30.1172602Z triton_convolution2d_58 0.2017 ms 61.4% 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 2025-09-07T11:45:30.1174290Z triton_convolution2d_60 0.2130 ms 58.2% 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 2025-09-07T11:45:30.1175774Z triton_convolution2d_61 0.2181 ms 56.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:30.1177425Z triton_convolution2d_56 0.2816 ms 44.0% 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 2025-09-07T11:45:30.1178925Z triton_convolution2d_55 0.2908 ms 42.6% 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 2025-09-07T11:45:30.1180410Z triton_convolution2d_57 0.9114 ms 13.6% 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 2025-09-07T11:45:30.1181583Z SingleProcess AUTOTUNE benchmarking takes 0.2869 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:45:30.4797127Z Autotune Choices Stats: 2025-09-07T11:45:30.4798789Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.6850559711456299, "best_triton_pos": 1, "best_triton_time": 1.4120960235595703, "best_triton_kernel": "triton_convolution2d_72", "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"} 2025-09-07T11:45:30.4856637Z AUTOTUNE convolution(2x1024x80x119, 512x1024x3x3) 2025-09-07T11:45:30.4857051Z strides: [9748480, 1, 121856, 1024], [9216, 1, 3072, 1024] 2025-09-07T11:45:30.4857438Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:30.4857768Z convolution 0.6851 ms 100.0% 2025-09-07T11:45:30.4858663Z triton_convolution2d_72 1.4121 ms 48.5% 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 2025-09-07T11:45:30.4860176Z triton_convolution2d_74 1.4172 ms 48.3% 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 2025-09-07T11:45:30.4861668Z triton_convolution2d_75 1.7039 ms 40.2% 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 2025-09-07T11:45:30.4863139Z triton_convolution2d_69 1.8944 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 2025-09-07T11:45:30.4864627Z triton_convolution2d_70 1.9118 ms 35.8% 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 2025-09-07T11:45:30.4866427Z triton_convolution2d_73 1.9917 ms 34.4% 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 2025-09-07T11:45:30.4867940Z triton_convolution2d_71 6.2525 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 2025-09-07T11:45:30.4869129Z SingleProcess AUTOTUNE benchmarking takes 0.3658 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:30.7811940Z Autotune Choices Stats: 2025-09-07T11:45:30.7813781Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.21094399690628052, "best_triton_pos": 1, "best_triton_time": 0.35737600922584534, "best_triton_kernel": "triton_convolution2d_80", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:45:30.7871554Z AUTOTUNE convolution(2x512x80x119, 256x512x3x3) 2025-09-07T11:45:30.7871991Z strides: [4874240, 1, 60928, 512], [4608, 1, 1536, 512] 2025-09-07T11:45:30.7872651Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:30.7872980Z convolution 0.2109 ms 100.0% 2025-09-07T11:45:30.7873855Z triton_convolution2d_80 0.3574 ms 59.0% 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 2025-09-07T11:45:30.7875356Z triton_convolution2d_79 0.3912 ms 53.9% 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 2025-09-07T11:45:30.7876847Z triton_convolution2d_81 0.4352 ms 48.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:30.7878324Z triton_convolution2d_82 0.4547 ms 46.4% 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 2025-09-07T11:45:30.7879815Z triton_convolution2d_77 0.5663 ms 37.3% 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 2025-09-07T11:45:30.7881297Z triton_convolution2d_76 0.6154 ms 34.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:30.7882787Z triton_convolution2d_78 1.4152 ms 14.9% 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 2025-09-07T11:45:30.7883967Z SingleProcess AUTOTUNE benchmarking takes 0.3005 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:31.1912695Z Autotune Choices Stats: 2025-09-07T11:45:31.1914426Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.7055360078811646, "best_triton_pos": 1, "best_triton_time": 1.2441600561141968, "best_triton_kernel": "triton_convolution2d_86", "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"} 2025-09-07T11:45:31.1972760Z AUTOTUNE convolution(2x512x160x239, 256x512x3x3) 2025-09-07T11:45:31.1973377Z strides: [19578880, 1, 122368, 512], [4608, 1, 1536, 512] 2025-09-07T11:45:31.1973770Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:31.1974079Z convolution 0.7055 ms 100.0% 2025-09-07T11:45:31.1975329Z triton_convolution2d_86 1.2442 ms 56.7% 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 2025-09-07T11:45:31.1976852Z triton_convolution2d_88 1.3558 ms 52.0% 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 2025-09-07T11:45:31.1978347Z triton_convolution2d_83 1.8381 ms 38.4% 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 2025-09-07T11:45:31.1979828Z triton_convolution2d_87 2.9051 ms 24.3% 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 2025-09-07T11:45:31.1981322Z triton_convolution2d_89 3.0382 ms 23.2% 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 2025-09-07T11:45:31.1983004Z triton_convolution2d_84 3.1007 ms 22.8% 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 2025-09-07T11:45:31.1984492Z triton_convolution2d_85 10.4704 ms 6.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:31.1985945Z SingleProcess AUTOTUNE benchmarking takes 0.4092 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:31.4942854Z Autotune Choices Stats: 2025-09-07T11:45:31.4944512Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.19865599274635315, "best_triton_pos": 1, "best_triton_time": 0.32870399951934814, "best_triton_kernel": "triton_convolution2d_93", "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"} 2025-09-07T11:45:31.5005055Z AUTOTUNE convolution(2x256x160x239, 128x256x3x3) 2025-09-07T11:45:31.5005486Z strides: [9789440, 1, 61184, 256], [2304, 1, 768, 256] 2025-09-07T11:45:31.5005856Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:31.5006166Z convolution 0.1987 ms 100.0% 2025-09-07T11:45:31.5007057Z triton_convolution2d_93 0.3287 ms 60.4% 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 2025-09-07T11:45:31.5008550Z triton_convolution2d_95 0.3809 ms 52.2% 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 2025-09-07T11:45:31.5010067Z triton_convolution2d_94 0.3871 ms 51.3% 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 2025-09-07T11:45:31.5011547Z triton_convolution2d_96 0.3891 ms 51.1% 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 2025-09-07T11:45:31.5013228Z triton_convolution2d_91 0.4782 ms 41.5% 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 2025-09-07T11:45:31.5014710Z triton_convolution2d_90 0.5509 ms 36.1% 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 2025-09-07T11:45:31.5016449Z triton_convolution2d_92 1.8422 ms 10.8% 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 2025-09-07T11:45:31.5017617Z SingleProcess AUTOTUNE benchmarking takes 0.3022 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:31.8669252Z Autotune Choices Stats: 2025-09-07T11:45:31.8670911Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.7178239822387695, "best_triton_pos": 1, "best_triton_time": 1.2021759748458862, "best_triton_kernel": "triton_convolution2d_100", "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"} 2025-09-07T11:45:31.8727237Z AUTOTUNE convolution(2x256x320x479, 128x256x3x3) 2025-09-07T11:45:31.8727650Z strides: [39239680, 1, 122624, 256], [2304, 1, 768, 256] 2025-09-07T11:45:31.8728035Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:31.8728358Z convolution 0.7178 ms 100.0% 2025-09-07T11:45:31.8729530Z triton_convolution2d_100 1.2022 ms 59.7% 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 2025-09-07T11:45:31.8731035Z triton_convolution2d_101 1.3681 ms 52.5% 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 2025-09-07T11:45:31.8732499Z triton_convolution2d_102 1.4828 ms 48.4% 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 2025-09-07T11:45:31.8734203Z triton_convolution2d_103 1.5063 ms 47.7% 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 2025-09-07T11:45:31.8735692Z triton_convolution2d_98 1.8412 ms 39.0% 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 2025-09-07T11:45:31.8737169Z triton_convolution2d_97 1.8575 ms 38.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:31.8738655Z triton_convolution2d_99 8.9518 ms 8.0% 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 2025-09-07T11:45:31.8739833Z SingleProcess AUTOTUNE benchmarking takes 0.3713 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:32.1745971Z Autotune Choices Stats: 2025-09-07T11:45:32.1747637Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.24268800020217896, "best_triton_pos": 1, "best_triton_time": 0.35839998722076416, "best_triton_kernel": "triton_convolution2d_107", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:45:32.1807327Z AUTOTUNE convolution(2x128x320x479, 64x128x3x3) 2025-09-07T11:45:32.1807762Z strides: [19619840, 1, 61312, 128], [1152, 1, 384, 128] 2025-09-07T11:45:32.1808147Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:32.1808472Z convolution 0.2427 ms 100.0% 2025-09-07T11:45:32.1809387Z triton_convolution2d_107 0.3584 ms 67.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:45:32.1816858Z triton_convolution2d_110 0.3860 ms 62.9% 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 2025-09-07T11:45:32.1818343Z triton_convolution2d_108 0.3963 ms 61.2% 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 2025-09-07T11:45:32.1819836Z triton_convolution2d_105 0.4762 ms 51.0% 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 2025-09-07T11:45:32.1821327Z triton_convolution2d_109 0.4772 ms 50.9% 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=8 2025-09-07T11:45:32.1822998Z triton_convolution2d_104 0.7352 ms 33.0% 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 2025-09-07T11:45:32.1824495Z triton_convolution2d_106 1.5155 ms 16.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:45:32.1825779Z SingleProcess AUTOTUNE benchmarking takes 0.3070 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:45:32.5424764Z Autotune Choices Stats: 2025-09-07T11:45:32.5426467Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.851967990398407, "best_triton_pos": 1, "best_triton_time": 1.368064045906067, "best_triton_kernel": "triton_convolution2d_114", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:45:32.5483791Z AUTOTUNE convolution(2x128x640x959, 64x128x3x3) 2025-09-07T11:45:32.5484221Z strides: [78561280, 1, 122752, 128], [1152, 1, 384, 128] 2025-09-07T11:45:32.5484609Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:45:32.5484921Z convolution 0.8520 ms 100.0% 2025-09-07T11:45:32.5485803Z triton_convolution2d_114 1.3681 ms 62.3% 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 2025-09-07T11:45:32.5487304Z triton_convolution2d_117 1.4152 ms 60.2% 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 2025-09-07T11:45:32.5488794Z triton_convolution2d_115 1.5391 ms 55.4% 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 2025-09-07T11:45:32.5490286Z triton_convolution2d_112 1.7562 ms 48.5% 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 2025-09-07T11:45:32.5491771Z triton_convolution2d_116 1.9671 ms 43.3% 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=8 2025-09-07T11:45:32.5493452Z triton_convolution2d_111 2.6460 ms 32.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:45:32.5495223Z triton_convolution2d_113 5.7549 ms 14.8% 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 2025-09-07T11:45:32.5496416Z SingleProcess AUTOTUNE benchmarking takes 0.3667 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:45:33.0465761Z Autotune Choices Stats: 2025-09-07T11:45:33.0466923Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_129", "best_kernel_desc": "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", "best_time": 0.13619199395179749, "best_triton_pos": 0} 2025-09-07T11:45:33.0525950Z AUTOTUNE addmm(1227520x2, 1227520x64, 64x2) 2025-09-07T11:45:33.0526322Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:45:33.0526687Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:45:33.0527502Z triton_mm_129 0.1362 ms 100.0% 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 2025-09-07T11:45:33.0528986Z triton_mm_135 0.1362 ms 100.0% 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=4, num_warps=4 2025-09-07T11:45:33.0530190Z triton_mm_139 0.1362 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 2025-09-07T11:45:33.0531384Z triton_mm_132 0.1372 ms 99.3% 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 2025-09-07T11:45:33.0532568Z triton_mm_140 0.1372 ms 99.3% 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 2025-09-07T11:45:33.0533995Z triton_mm_126 0.1382 ms 98.5% 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 2025-09-07T11:45:33.0535178Z triton_mm_131 0.1382 ms 98.5% 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 2025-09-07T11:45:33.0536335Z triton_mm_133 0.1393 ms 97.8% 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=3, num_warps=4 2025-09-07T11:45:33.0537514Z triton_mm_134 0.1393 ms 97.8% 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 2025-09-07T11:45:33.0538699Z triton_mm_136 0.1403 ms 97.1% 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=3, num_warps=4 2025-09-07T11:45:33.0539735Z SingleProcess AUTOTUNE benchmarking takes 0.5013 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:45:38.6593962Z pass 2025-09-07T11:45:42.0102023Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:45:42.0103463Z import pynvml # type: ignore[import] 2025-09-07T11:45:44.9275955Z 2025-09-07T11:45:46.9665510Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:45:46.9665906Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:45:46.9846965Z cuda eval resnet152 2025-09-07T11:46:25.3675033Z Autotune Choices Stats: 2025-09-07T11:46:25.3848877Z {"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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T11:46:25.3850533Z AUTOTUNE addmm(12544x256, 12544x64, 64x256) 2025-09-07T11:46:25.3850857Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:46:25.3851238Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:25.3852063Z triton_mm_58 0.0133 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 2025-09-07T11:46:25.3853555Z triton_mm_57 0.0143 ms 92.9% 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 2025-09-07T11:46:25.3854757Z triton_mm_67 0.0143 ms 92.9% 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 2025-09-07T11:46:25.3855945Z triton_mm_59 0.0154 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 2025-09-07T11:46:25.3857377Z triton_mm_63 0.0154 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=3, num_warps=4 2025-09-07T11:46:25.3858559Z triton_mm_64 0.0154 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 2025-09-07T11:46:25.3859750Z triton_mm_66 0.0154 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 2025-09-07T11:46:25.3860933Z triton_mm_54 0.0164 ms 81.2% 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 2025-09-07T11:46:25.3862107Z triton_mm_56 0.0164 ms 81.2% 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 2025-09-07T11:46:25.3863278Z triton_mm_51 0.0184 ms 72.2% 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 2025-09-07T11:46:25.3864288Z SingleProcess AUTOTUNE benchmarking takes 0.4517 seconds and 0.0007 seconds precompiling for 21 choices 2025-09-07T11:46:26.7891794Z Autotune Choices Stats: 2025-09-07T11:46:26.7893325Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_166", "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": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T11:46:26.7950611Z AUTOTUNE addmm(12544x128, 12544x256, 256x128) 2025-09-07T11:46:26.7951000Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:46:26.7951366Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:26.7952211Z triton_mm_166 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:26.7953410Z triton_mm_167 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:26.7954603Z triton_mm_168 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:26.7955796Z triton_mm_169 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:26.7957443Z triton_mm_173 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:26.7958660Z triton_mm_174 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:46:26.7959854Z triton_mm_170 0.0184 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:26.7961037Z triton_mm_172 0.0184 ms 94.4% 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 2025-09-07T11:46:26.7964156Z bias_addmm 0.0195 ms 89.5% 2025-09-07T11:46:26.7964882Z triton_mm_163 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:46:26.7965908Z SingleProcess AUTOTUNE benchmarking takes 0.3152 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:46:27.4368280Z Autotune Choices Stats: 2025-09-07T11:46:27.4369923Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_241", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:46:27.4432116Z AUTOTUNE addmm(3136x512, 3136x128, 128x512) 2025-09-07T11:46:27.4432522Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T11:46:27.4432897Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:27.4433757Z triton_mm_241 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:27.4435026Z triton_mm_242 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:27.4436236Z triton_mm_244 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:27.4436985Z bias_addmm 0.0133 ms 92.3% 2025-09-07T11:46:27.4437700Z triton_mm_238 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:46:27.4438878Z triton_mm_240 0.0133 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 2025-09-07T11:46:27.4440070Z triton_mm_243 0.0133 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 2025-09-07T11:46:27.4441318Z triton_mm_245 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:27.4442511Z triton_mm_247 0.0133 ms 92.3% 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 2025-09-07T11:46:27.4443696Z triton_mm_248 0.0133 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 2025-09-07T11:46:27.4444729Z SingleProcess AUTOTUNE benchmarking takes 0.3140 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:46:28.7372200Z Autotune Choices Stats: 2025-09-07T11:46:28.7373707Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_10", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:46:28.7434978Z AUTOTUNE addmm(12544x64, 12544x64, 64x64) 2025-09-07T11:46:28.7435327Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:46:28.7435688Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:28.7436517Z triton_mm_10 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:46:28.7437702Z triton_mm_12 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:46:28.7439092Z triton_mm_13 0.0102 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 2025-09-07T11:46:28.7440324Z triton_mm_14 0.0102 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 2025-09-07T11:46:28.7441715Z triton_mm_15 0.0102 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 2025-09-07T11:46:28.7442894Z triton_mm_16 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:28.7444067Z triton_mm_18 0.0102 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 2025-09-07T11:46:28.7445255Z triton_mm_22 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:28.7446454Z triton_mm_23 0.0102 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 2025-09-07T11:46:28.7447630Z triton_mm_6 0.0113 ms 90.9% 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 2025-09-07T11:46:28.7448632Z SingleProcess AUTOTUNE benchmarking takes 0.3392 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T11:46:29.3856914Z Autotune Choices Stats: 2025-09-07T11:46:29.3859117Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_78", "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T11:46:29.3937151Z AUTOTUNE addmm(12544x64, 12544x256, 256x64) 2025-09-07T11:46:29.3937811Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:46:29.3938478Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:29.3940079Z triton_mm_78 0.0154 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 2025-09-07T11:46:29.3942345Z triton_mm_80 0.0154 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 2025-09-07T11:46:29.3944590Z triton_mm_76 0.0164 ms 93.7% 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 2025-09-07T11:46:29.3946798Z triton_mm_79 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:29.3949344Z triton_mm_85 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:29.3951625Z triton_mm_86 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:46:29.3953891Z triton_mm_71 0.0174 ms 88.2% 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 2025-09-07T11:46:29.3956131Z triton_mm_75 0.0174 ms 88.2% 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 2025-09-07T11:46:29.3958586Z triton_mm_70 0.0184 ms 83.3% 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 2025-09-07T11:46:29.3960838Z triton_mm_72 0.0184 ms 83.3% 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 2025-09-07T11:46:29.3963074Z SingleProcess AUTOTUNE benchmarking takes 0.3297 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:46:29.7812764Z Autotune Choices Stats: 2025-09-07T11:46:29.7815410Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_519", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T11:46:29.7884959Z AUTOTUNE addmm(3136x256, 3136x512, 512x256) 2025-09-07T11:46:29.7885649Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:46:29.7886303Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:29.7887801Z triton_mm_519 0.0143 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 2025-09-07T11:46:29.7889969Z triton_mm_515 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:46:29.7892242Z triton_mm_518 0.0154 ms 93.3% 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 2025-09-07T11:46:29.7894712Z triton_mm_521 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:29.7896859Z triton_mm_517 0.0174 ms 82.4% 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 2025-09-07T11:46:29.7899022Z triton_mm_520 0.0174 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:29.7901273Z triton_mm_525 0.0174 ms 82.4% 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 2025-09-07T11:46:29.7902695Z bias_addmm 0.0184 ms 77.8% 2025-09-07T11:46:29.7903932Z triton_mm_516 0.0184 ms 77.8% 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 2025-09-07T11:46:29.7906145Z triton_mm_524 0.0184 ms 77.8% 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 2025-09-07T11:46:29.7907900Z SingleProcess AUTOTUNE benchmarking takes 0.3528 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:46:30.3391763Z Autotune Choices Stats: 2025-09-07T11:46:30.3393953Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_593", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:46:30.3487446Z AUTOTUNE addmm(784x1024, 784x256, 256x1024) 2025-09-07T11:46:30.3488122Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:46:30.3488757Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:30.3490233Z triton_mm_593 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:30.3493119Z triton_mm_594 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:30.3495134Z triton_mm_592 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:30.3497596Z triton_mm_589 0.0143 ms 85.7% 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 2025-09-07T11:46:30.3499687Z triton_mm_591 0.0143 ms 85.7% 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 2025-09-07T11:46:30.3501810Z triton_mm_598 0.0143 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:30.3504090Z triton_mm_600 0.0143 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:46:30.3506438Z triton_mm_588 0.0174 ms 70.6% 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=2, num_warps=4 2025-09-07T11:46:30.3507797Z addmm 0.0195 ms 63.2% 2025-09-07T11:46:30.3509032Z triton_mm_587 0.0205 ms 60.0% 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 2025-09-07T11:46:30.3510841Z SingleProcess AUTOTUNE benchmarking takes 0.4119 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T11:46:32.1605257Z Autotune Choices Stats: 2025-09-07T11:46:32.1607441Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_215", "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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T11:46:32.1668264Z AUTOTUNE addmm(3136x128, 3136x512, 512x128) 2025-09-07T11:46:32.1668656Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:46:32.1669014Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:32.1669903Z triton_mm_215 0.0133 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 2025-09-07T11:46:32.1671702Z triton_mm_218 0.0143 ms 92.9% 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 2025-09-07T11:46:32.1672827Z bias_addmm 0.0154 ms 86.7% 2025-09-07T11:46:32.1674099Z triton_mm_209 0.0154 ms 86.7% 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 2025-09-07T11:46:32.1676326Z triton_mm_217 0.0154 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=4, num_warps=8 2025-09-07T11:46:32.1678921Z triton_mm_220 0.0154 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 2025-09-07T11:46:32.1681199Z triton_mm_208 0.0164 ms 81.2% 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 2025-09-07T11:46:32.1683459Z triton_mm_216 0.0174 ms 76.5% 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 2025-09-07T11:46:32.1685601Z triton_mm_219 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:32.1688019Z triton_mm_224 0.0174 ms 76.5% 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 2025-09-07T11:46:32.1689976Z SingleProcess AUTOTUNE benchmarking takes 0.3828 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T11:46:33.0234596Z Autotune Choices Stats: 2025-09-07T11:46:33.0236822Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_2070", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T11:46:33.0297725Z AUTOTUNE addmm(784x512, 784x1024, 1024x512) 2025-09-07T11:46:33.0298387Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T11:46:33.0299097Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:33.0300650Z triton_mm_2070 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:46:33.0302940Z triton_mm_2067 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:46:33.0305274Z triton_mm_2074 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:33.0307561Z triton_mm_2064 0.0205 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 2025-09-07T11:46:33.0309809Z triton_mm_2065 0.0205 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:46:33.0311976Z triton_mm_2066 0.0205 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:46:33.0314268Z triton_mm_2076 0.0205 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 2025-09-07T11:46:33.0315642Z addmm 0.0225 ms 77.3% 2025-09-07T11:46:33.0316945Z triton_mm_2073 0.0225 ms 77.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:33.0319189Z triton_mm_2071 0.0236 ms 73.9% 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 2025-09-07T11:46:33.0321050Z SingleProcess AUTOTUNE benchmarking takes 0.3927 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T11:46:33.4513179Z Autotune Choices Stats: 2025-09-07T11:46:33.4516431Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_mm_2145", "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"} 2025-09-07T11:46:33.4590958Z AUTOTUNE addmm(196x2048, 196x512, 512x2048) 2025-09-07T11:46:33.4591374Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:46:33.4591747Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:33.4592126Z bias_addmm 0.0143 ms 100.0% 2025-09-07T11:46:33.4592875Z triton_mm_2145 0.0143 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:46:33.4594392Z triton_mm_2149 0.0143 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 2025-09-07T11:46:33.4595609Z triton_mm_2139 0.0154 ms 93.3% 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 2025-09-07T11:46:33.4596999Z triton_mm_2148 0.0154 ms 93.3% 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 2025-09-07T11:46:33.4598201Z triton_mm_2151 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:46:33.4599391Z triton_mm_2140 0.0174 ms 82.4% 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 2025-09-07T11:46:33.4600567Z triton_mm_2146 0.0174 ms 82.4% 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 2025-09-07T11:46:33.4601772Z triton_mm_2147 0.0174 ms 82.4% 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 2025-09-07T11:46:33.4602967Z triton_mm_2150 0.0174 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:46:33.4603995Z SingleProcess AUTOTUNE benchmarking takes 0.3122 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:46:34.3640285Z Autotune Choices Stats: 2025-09-07T11:46:34.3641823Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "best_triton_kernel": "triton_mm_562", "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"} 2025-09-07T11:46:34.3703964Z AUTOTUNE addmm(784x256, 784x1024, 1024x256) 2025-09-07T11:46:34.3704343Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T11:46:34.3704742Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:34.3705205Z bias_addmm 0.0133 ms 100.0% 2025-09-07T11:46:34.3705929Z triton_mm_562 0.0133 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 2025-09-07T11:46:34.3707129Z triton_mm_566 0.0133 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 2025-09-07T11:46:34.3708319Z triton_mm_560 0.0154 ms 86.7% 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 2025-09-07T11:46:34.3709742Z triton_mm_561 0.0154 ms 86.7% 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 2025-09-07T11:46:34.3710934Z triton_mm_559 0.0164 ms 81.2% 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 2025-09-07T11:46:34.3712109Z triton_mm_565 0.0164 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:46:34.3712849Z addmm 0.0184 ms 72.2% 2025-09-07T11:46:34.3713535Z triton_mm_569 0.0184 ms 72.2% 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 2025-09-07T11:46:34.3714815Z triton_mm_568 0.0205 ms 65.0% 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 2025-09-07T11:46:34.3715841Z SingleProcess AUTOTUNE benchmarking takes 0.3045 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:46:35.4553204Z Autotune Choices Stats: 2025-09-07T11:46:35.4554796Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_2117", "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T11:46:35.4616520Z AUTOTUNE addmm(196x512, 196x2048, 2048x512) 2025-09-07T11:46:35.4616903Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T11:46:35.4617282Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:35.4618148Z triton_mm_2117 0.0154 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 2025-09-07T11:46:35.4618934Z bias_addmm 0.0184 ms 83.3% 2025-09-07T11:46:35.4619663Z triton_mm_2121 0.0195 ms 78.9% 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 2025-09-07T11:46:35.4620856Z triton_mm_2115 0.0215 ms 71.4% 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 2025-09-07T11:46:35.4622038Z triton_mm_2114 0.0225 ms 68.2% 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 2025-09-07T11:46:35.4623221Z triton_mm_2116 0.0225 ms 68.2% 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 2025-09-07T11:46:35.4623973Z addmm 0.0246 ms 62.5% 2025-09-07T11:46:35.4624677Z triton_mm_2120 0.0246 ms 62.5% 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 2025-09-07T11:46:35.4625939Z triton_mm_2124 0.0287 ms 53.6% 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 2025-09-07T11:46:35.4627137Z triton_mm_2123 0.0317 ms 48.4% 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 2025-09-07T11:46:35.4628172Z SingleProcess AUTOTUNE benchmarking takes 0.3299 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T11:46:36.4680376Z Autotune Choices Stats: 2025-09-07T11:46:36.4682063Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.08191999793052673, "best_triton_pos": 1, "best_triton_time": 0.11468800157308578, "best_triton_kernel": "triton_convolution2d_3", "best_triton_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"} 2025-09-07T11:46:36.4746820Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T11:46:36.4747186Z strides: [150528, 1, 672, 3], [147, 1, 21, 3] 2025-09-07T11:46:36.4747539Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:36.4747851Z convolution 0.0819 ms 100.0% 2025-09-07T11:46:36.4748733Z triton_convolution2d_3 0.1147 ms 71.4% 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 2025-09-07T11:46:36.4750218Z triton_convolution2d_0 0.1167 ms 70.2% 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 2025-09-07T11:46:36.4751866Z triton_convolution2d_4 0.1372 ms 59.7% 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 2025-09-07T11:46:36.4753540Z triton_convolution2d_2 0.1382 ms 59.3% 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 2025-09-07T11:46:36.4755023Z triton_convolution2d_5 0.1495 ms 54.8% 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 2025-09-07T11:46:36.4756498Z triton_convolution2d_1 0.3246 ms 25.2% 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 2025-09-07T11:46:36.4757654Z SingleProcess AUTOTUNE benchmarking takes 0.2452 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T11:46:36.5988625Z Autotune Choices Stats: 2025-09-07T11:46:36.5990289Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_convolution2d_28", "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"} 2025-09-07T11:46:36.6052302Z AUTOTUNE convolution(4x64x56x56, 64x64x3x3) 2025-09-07T11:46:36.6052712Z strides: [200704, 1, 3584, 64], [576, 1, 192, 64] 2025-09-07T11:46:36.6053249Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:36.6053572Z convolution 0.0164 ms 100.0% 2025-09-07T11:46:36.6054454Z triton_convolution2d_28 0.0215 ms 76.2% 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 2025-09-07T11:46:36.6055949Z triton_convolution2d_29 0.0225 ms 72.7% 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=8 2025-09-07T11:46:36.6057441Z triton_convolution2d_27 0.0236 ms 69.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:36.6058919Z triton_convolution2d_24 0.0287 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:36.6060396Z triton_convolution2d_30 0.0328 ms 50.0% 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 2025-09-07T11:46:36.6066491Z triton_convolution2d_25 0.0399 ms 41.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:36.6067985Z triton_convolution2d_26 0.0604 ms 27.1% 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 2025-09-07T11:46:36.6069153Z SingleProcess AUTOTUNE benchmarking takes 0.1295 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:36.7586239Z Autotune Choices Stats: 2025-09-07T11:46:36.7587875Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.03788800165057182, "best_triton_kernel": "triton_convolution2d_179", "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"} 2025-09-07T11:46:36.7653680Z AUTOTUNE convolution(4x128x56x56, 128x128x3x3) 2025-09-07T11:46:36.7654484Z strides: [401408, 1, 7168, 128], [1152, 1, 384, 128] 2025-09-07T11:46:36.7654862Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:36.7655176Z convolution 0.0164 ms 100.0% 2025-09-07T11:46:36.7656069Z triton_convolution2d_179 0.0379 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 2025-09-07T11:46:36.7657569Z triton_convolution2d_180 0.0420 ms 39.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:36.7659074Z triton_convolution2d_178 0.0553 ms 29.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:36.7660572Z triton_convolution2d_175 0.0573 ms 28.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:36.7662060Z triton_convolution2d_181 0.0573 ms 28.6% 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 2025-09-07T11:46:36.7663549Z triton_convolution2d_176 0.0727 ms 22.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:36.7665129Z triton_convolution2d_177 0.1280 ms 12.8% 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 2025-09-07T11:46:36.7666297Z SingleProcess AUTOTUNE benchmarking takes 0.1530 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:36.8832273Z Autotune Choices Stats: 2025-09-07T11:46:36.8833909Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.016383999958634377, "best_triton_kernel": "triton_convolution2d_204", "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"} 2025-09-07T11:46:36.8895737Z AUTOTUNE convolution(4x256x56x56, 512x256x1x1) 2025-09-07T11:46:36.8896210Z strides: [802816, 1, 14336, 256], [256, 1, 1, 1] 2025-09-07T11:46:36.8896721Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:36.8897031Z convolution 0.0143 ms 100.0% 2025-09-07T11:46:36.8897923Z triton_convolution2d_204 0.0164 ms 87.5% 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 2025-09-07T11:46:36.8899424Z triton_convolution2d_203 0.0184 ms 77.8% 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 2025-09-07T11:46:36.8900925Z triton_convolution2d_205 0.0184 ms 77.8% 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 2025-09-07T11:46:36.8902510Z triton_convolution2d_206 0.0195 ms 73.7% 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 2025-09-07T11:46:36.8904148Z triton_convolution2d_200 0.0215 ms 66.7% 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 2025-09-07T11:46:36.8905709Z triton_convolution2d_201 0.0236 ms 60.9% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:46:36.8907206Z triton_convolution2d_202 0.0502 ms 28.6% 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 2025-09-07T11:46:36.8908382Z SingleProcess AUTOTUNE benchmarking takes 0.1233 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:37.0359683Z Autotune Choices Stats: 2025-09-07T11:46:37.0361337Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.03686400130391121, "best_triton_kernel": "triton_convolution2d_229", "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"} 2025-09-07T11:46:37.0427201Z AUTOTUNE convolution(4x128x28x28, 128x128x3x3) 2025-09-07T11:46:37.0427604Z strides: [100352, 1, 3584, 128], [1152, 1, 384, 128] 2025-09-07T11:46:37.0427974Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:37.0428287Z convolution 0.0154 ms 100.0% 2025-09-07T11:46:37.0429169Z triton_convolution2d_229 0.0369 ms 41.7% 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 2025-09-07T11:46:37.0430670Z triton_convolution2d_230 0.0399 ms 38.5% 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 2025-09-07T11:46:37.0432179Z triton_convolution2d_228 0.0522 ms 29.4% 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 2025-09-07T11:46:37.0433676Z triton_convolution2d_225 0.0553 ms 27.8% 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 2025-09-07T11:46:37.0435164Z triton_convolution2d_231 0.0563 ms 27.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:37.0436653Z triton_convolution2d_226 0.0645 ms 23.8% 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 2025-09-07T11:46:37.0438307Z triton_convolution2d_227 0.1198 ms 12.8% 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 2025-09-07T11:46:37.0439477Z SingleProcess AUTOTUNE benchmarking takes 0.1521 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:37.2488269Z Autotune Choices Stats: 2025-09-07T11:46:37.2489940Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.0655359998345375, "best_triton_kernel": "triton_convolution2d_530", "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"} 2025-09-07T11:46:37.2552677Z AUTOTUNE convolution(4x256x28x28, 256x256x3x3) 2025-09-07T11:46:37.2553077Z strides: [200704, 1, 7168, 256], [2304, 1, 768, 256] 2025-09-07T11:46:37.2553443Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:37.2554016Z convolution 0.0205 ms 100.0% 2025-09-07T11:46:37.2554890Z triton_convolution2d_530 0.0655 ms 31.2% 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 2025-09-07T11:46:37.2556396Z triton_convolution2d_529 0.1014 ms 20.2% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:37.2557955Z triton_convolution2d_531 0.1055 ms 19.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:37.2559477Z triton_convolution2d_532 0.1055 ms 19.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:37.2560970Z triton_convolution2d_527 0.1341 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:37.2562463Z triton_convolution2d_526 0.1372 ms 14.9% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:37.2563959Z triton_convolution2d_528 0.2222 ms 9.2% 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 2025-09-07T11:46:37.2565137Z SingleProcess AUTOTUNE benchmarking takes 0.1984 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:37.3784309Z Autotune Choices Stats: 2025-09-07T11:46:37.3786004Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_convolution2d_555", "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"} 2025-09-07T11:46:37.3848688Z AUTOTUNE convolution(4x512x28x28, 1024x512x1x1) 2025-09-07T11:46:37.3849112Z strides: [401408, 1, 14336, 512], [512, 1, 1, 1] 2025-09-07T11:46:37.3849485Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:37.3849798Z convolution 0.0154 ms 100.0% 2025-09-07T11:46:37.3850923Z triton_convolution2d_555 0.0215 ms 71.4% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:46:37.3852434Z triton_convolution2d_554 0.0276 ms 55.6% 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 2025-09-07T11:46:37.3854142Z triton_convolution2d_556 0.0276 ms 55.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:46:37.3855632Z triton_convolution2d_557 0.0287 ms 53.6% 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 2025-09-07T11:46:37.3857213Z triton_convolution2d_551 0.0328 ms 46.9% 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 2025-09-07T11:46:37.3858853Z triton_convolution2d_552 0.0358 ms 42.9% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:46:37.3860331Z triton_convolution2d_553 0.0563 ms 27.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T11:46:37.3861517Z SingleProcess AUTOTUNE benchmarking takes 0.1286 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:37.5743562Z Autotune Choices Stats: 2025-09-07T11:46:37.5745257Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.06656000018119812, "best_triton_kernel": "triton_convolution2d_580", "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"} 2025-09-07T11:46:37.5808153Z AUTOTUNE convolution(4x256x14x14, 256x256x3x3) 2025-09-07T11:46:37.5808556Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T11:46:37.5808920Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:37.5809229Z convolution 0.0195 ms 100.0% 2025-09-07T11:46:37.5810099Z triton_convolution2d_580 0.0666 ms 29.2% 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 2025-09-07T11:46:37.5811596Z triton_convolution2d_579 0.0993 ms 19.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:37.5813259Z triton_convolution2d_581 0.1055 ms 18.4% 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 2025-09-07T11:46:37.5814762Z triton_convolution2d_582 0.1055 ms 18.4% 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 2025-09-07T11:46:37.5816256Z triton_convolution2d_577 0.1249 ms 15.6% 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 2025-09-07T11:46:37.5817752Z triton_convolution2d_576 0.1331 ms 14.6% 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 2025-09-07T11:46:37.5819387Z triton_convolution2d_578 0.2140 ms 9.1% 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 2025-09-07T11:46:37.5820560Z SingleProcess AUTOTUNE benchmarking takes 0.1950 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:37.9127809Z Autotune Choices Stats: 2025-09-07T11:46:37.9129460Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.12800000607967377, "best_triton_kernel": "triton_convolution2d_2085", "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"} 2025-09-07T11:46:37.9193416Z AUTOTUNE convolution(4x512x14x14, 512x512x3x3) 2025-09-07T11:46:37.9193827Z strides: [100352, 1, 7168, 512], [4608, 1, 1536, 512] 2025-09-07T11:46:37.9194188Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:37.9194512Z convolution 0.0266 ms 100.0% 2025-09-07T11:46:37.9195588Z triton_convolution2d_2085 0.1280 ms 20.8% 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 2025-09-07T11:46:37.9197100Z triton_convolution2d_2084 0.1925 ms 13.8% 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 2025-09-07T11:46:37.9198615Z triton_convolution2d_2087 0.1976 ms 13.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:46:37.9200131Z triton_convolution2d_2086 0.2038 ms 13.1% 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 2025-09-07T11:46:37.9201623Z triton_convolution2d_2082 0.2632 ms 10.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:37.9203127Z triton_convolution2d_2081 0.2806 ms 9.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:46:37.9204631Z triton_convolution2d_2083 0.3297 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 2025-09-07T11:46:37.9205813Z SingleProcess AUTOTUNE benchmarking takes 0.2616 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:38.0646830Z Autotune Choices Stats: 2025-09-07T11:46:38.0648520Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "best_triton_kernel": "triton_convolution2d_2110", "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"} 2025-09-07T11:46:38.0711973Z AUTOTUNE convolution(4x1024x14x14, 2048x1024x1x1) 2025-09-07T11:46:38.0712384Z strides: [200704, 1, 14336, 1024], [1024, 1, 1, 1] 2025-09-07T11:46:38.0712730Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:38.0713058Z convolution 0.0184 ms 100.0% 2025-09-07T11:46:38.0713949Z triton_convolution2d_2110 0.0348 ms 52.9% 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 2025-09-07T11:46:38.0715738Z triton_convolution2d_2109 0.0461 ms 40.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:46:38.0717246Z triton_convolution2d_2111 0.0461 ms 40.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:46:38.0718744Z triton_convolution2d_2112 0.0481 ms 38.3% 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 2025-09-07T11:46:38.0720346Z triton_convolution2d_2106 0.0573 ms 32.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:46:38.0722012Z triton_convolution2d_2107 0.0635 ms 29.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:46:38.0723509Z triton_convolution2d_2108 0.1382 ms 13.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T11:46:38.0724694Z SingleProcess AUTOTUNE benchmarking takes 0.1507 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:38.3256696Z Autotune Choices Stats: 2025-09-07T11:46:38.3258379Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.12902399897575378, "best_triton_kernel": "triton_convolution2d_2135", "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"} 2025-09-07T11:46:38.3321009Z AUTOTUNE convolution(4x512x7x7, 512x512x3x3) 2025-09-07T11:46:38.3321426Z strides: [25088, 1, 3584, 512], [4608, 1, 1536, 512] 2025-09-07T11:46:38.3321796Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:46:38.3322110Z convolution 0.0266 ms 100.0% 2025-09-07T11:46:38.3322992Z triton_convolution2d_2135 0.1290 ms 20.6% 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 2025-09-07T11:46:38.3324504Z triton_convolution2d_2134 0.1935 ms 13.8% 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 2025-09-07T11:46:38.3326151Z triton_convolution2d_2136 0.2038 ms 13.1% 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 2025-09-07T11:46:38.3327660Z triton_convolution2d_2137 0.2089 ms 12.7% 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 2025-09-07T11:46:38.3329161Z triton_convolution2d_2133 0.2130 ms 12.5% 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 2025-09-07T11:46:38.3330657Z triton_convolution2d_2132 0.2570 ms 10.4% 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 2025-09-07T11:46:38.3332147Z triton_convolution2d_2131 0.2714 ms 9.8% 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 2025-09-07T11:46:38.3333826Z SingleProcess AUTOTUNE benchmarking takes 0.2597 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:46:38.6342472Z Autotune Choices Stats: 2025-09-07T11:46:38.6343713Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_2203", "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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T11:46:38.6412014Z AUTOTUNE addmm(4x1000, 4x2048, 2048x1000) 2025-09-07T11:46:38.6412383Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T11:46:38.6413102Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:46:38.6413949Z triton_mm_2203 0.0133 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 2025-09-07T11:46:38.6415395Z triton_mm_2207 0.0143 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:46:38.6416166Z bias_addmm 0.0174 ms 76.5% 2025-09-07T11:46:38.6416890Z triton_mm_2211 0.0174 ms 76.5% 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 2025-09-07T11:46:38.6418104Z triton_mm_2215 0.0184 ms 72.2% 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 2025-09-07T11:46:38.6419308Z triton_mm_2202 0.0205 ms 65.0% 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 2025-09-07T11:46:38.6420529Z triton_mm_2200 0.0215 ms 61.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:46:38.6421725Z triton_mm_2201 0.0215 ms 61.9% 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 2025-09-07T11:46:38.6422910Z triton_mm_2206 0.0215 ms 61.9% 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 2025-09-07T11:46:38.6423665Z addmm 0.0225 ms 59.1% 2025-09-07T11:46:38.6424208Z SingleProcess AUTOTUNE benchmarking takes 0.3030 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:46:42.9208273Z pass 2025-09-07T11:46:47.2498635Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:46:47.2500098Z import pynvml # type: ignore[import] 2025-09-07T11:46:50.2271163Z 2025-09-07T11:46:51.4245771Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:46:51.4246395Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:46:51.4272893Z cuda eval resnet18 2025-09-07T11:47:00.1914064Z Autotune Choices Stats: 2025-09-07T11:47:00.1915897Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "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=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:47:00.1974196Z AUTOTUNE convolution(4x64x56x56, 128x64x3x3) 2025-09-07T11:47:00.1974724Z strides: [200704, 1, 3584, 64], [576, 1, 192, 64] 2025-09-07T11:47:00.1975163Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:47:00.1975555Z convolution 0.0133 ms 100.0% 2025-09-07T11:47:00.1976533Z triton_convolution2d_38 0.0225 ms 59.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:47:00.2215838Z triton_convolution2d_39 0.0256 ms 52.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:47:00.2217395Z triton_convolution2d_34 0.0287 ms 46.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:47:00.2219217Z triton_convolution2d_37 0.0297 ms 44.8% 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 2025-09-07T11:47:00.2220921Z triton_convolution2d_40 0.0328 ms 40.6% 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 2025-09-07T11:47:00.2222399Z triton_convolution2d_35 0.0399 ms 33.3% 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 2025-09-07T11:47:00.2223892Z triton_convolution2d_36 0.0666 ms 20.0% 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:47:00.2225138Z SingleProcess AUTOTUNE benchmarking takes 0.1481 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:47:00.3173462Z Autotune Choices Stats: 2025-09-07T11:47:00.3175673Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_52", "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": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T11:47:00.3257705Z AUTOTUNE convolution(4x64x56x56, 128x64x1x1) 2025-09-07T11:47:00.3258530Z strides: [200704, 1, 3584, 64], [64, 1, 1, 1] 2025-09-07T11:47:00.3259140Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:47:00.3260859Z triton_convolution2d_52 0.0082 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 2025-09-07T11:47:00.3263060Z triton_convolution2d_48 0.0092 ms 88.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:47:00.3265259Z triton_convolution2d_53 0.0092 ms 88.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:47:00.3266564Z convolution 0.0102 ms 80.0% 2025-09-07T11:47:00.3267806Z triton_convolution2d_51 0.0102 ms 80.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:47:00.3269943Z triton_convolution2d_54 0.0102 ms 80.0% 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 2025-09-07T11:47:00.3272407Z triton_convolution2d_49 0.0113 ms 72.7% 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 2025-09-07T11:47:00.3274532Z triton_convolution2d_50 0.0154 ms 53.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T11:47:00.3276291Z SingleProcess AUTOTUNE benchmarking takes 0.1223 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:47:00.4835273Z Autotune Choices Stats: 2025-09-07T11:47:00.4837135Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.035840000957250595, "best_triton_kernel": "triton_convolution2d_73", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T11:47:00.5059607Z AUTOTUNE convolution(4x128x28x28, 256x128x3x3) 2025-09-07T11:47:00.5060079Z strides: [100352, 1, 3584, 128], [1152, 1, 384, 128] 2025-09-07T11:47:00.5060865Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:47:00.5061321Z convolution 0.0143 ms 100.0% 2025-09-07T11:47:00.5062315Z triton_convolution2d_73 0.0358 ms 40.0% 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 2025-09-07T11:47:00.5063822Z triton_convolution2d_72 0.0543 ms 26.4% 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 2025-09-07T11:47:00.5065419Z triton_convolution2d_75 0.0563 ms 25.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:47:00.5066926Z triton_convolution2d_74 0.0573 ms 25.0% 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 2025-09-07T11:47:00.5068412Z triton_convolution2d_70 0.0696 ms 20.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:47:00.5069899Z triton_convolution2d_69 0.0717 ms 20.0% 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 2025-09-07T11:47:00.5071393Z triton_convolution2d_71 0.1157 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:47:00.5072561Z SingleProcess AUTOTUNE benchmarking takes 0.1632 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:47:00.6457479Z Autotune Choices Stats: 2025-09-07T11:47:00.6459331Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010239999741315842, "best_triton_pos": 1, "best_triton_time": 0.010239999741315842, "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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T11:47:00.6461092Z AUTOTUNE convolution(4x128x28x28, 256x128x1x1) 2025-09-07T11:47:00.6461531Z strides: [100352, 1, 3584, 128], [128, 1, 1, 1] 2025-09-07T11:47:00.6461960Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:47:00.6462337Z convolution 0.0102 ms 100.0% 2025-09-07T11:47:00.6463538Z triton_convolution2d_87 0.0102 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 2025-09-07T11:47:00.6465214Z triton_convolution2d_86 0.0123 ms 83.3% 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 2025-09-07T11:47:00.6466797Z triton_convolution2d_88 0.0123 ms 83.3% 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 2025-09-07T11:47:00.6468349Z triton_convolution2d_83 0.0133 ms 76.9% 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 2025-09-07T11:47:00.6470024Z triton_convolution2d_89 0.0133 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:47:00.6471764Z triton_convolution2d_84 0.0143 ms 71.4% 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 2025-09-07T11:47:00.6473341Z triton_convolution2d_85 0.0195 ms 52.6% 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 2025-09-07T11:47:00.6474589Z SingleProcess AUTOTUNE benchmarking takes 0.1498 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T11:47:00.8519981Z Autotune Choices Stats: 2025-09-07T11:47:00.8521699Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.06656000018119812, "best_triton_kernel": "triton_convolution2d_108", "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"} 2025-09-07T11:47:00.8591714Z AUTOTUNE convolution(4x256x14x14, 512x256x3x3) 2025-09-07T11:47:00.8592148Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T11:47:00.8592519Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:47:00.8592842Z convolution 0.0195 ms 100.0% 2025-09-07T11:47:00.8593725Z triton_convolution2d_108 0.0666 ms 29.2% 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 2025-09-07T11:47:00.8595265Z triton_convolution2d_107 0.1024 ms 19.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:47:00.8596789Z triton_convolution2d_109 0.1055 ms 18.4% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:47:00.8598297Z triton_convolution2d_110 0.1065 ms 18.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:47:00.8599797Z triton_convolution2d_104 0.1352 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 2025-09-07T11:47:00.8601295Z triton_convolution2d_105 0.1352 ms 14.4% 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 2025-09-07T11:47:00.8603047Z triton_convolution2d_106 0.1751 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T11:47:00.8604229Z SingleProcess AUTOTUNE benchmarking takes 0.2090 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:47:00.9788015Z Autotune Choices Stats: 2025-09-07T11:47:00.9789689Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010239999741315842, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T11:47:00.9858427Z AUTOTUNE convolution(4x256x14x14, 512x256x1x1) 2025-09-07T11:47:00.9858861Z strides: [50176, 1, 3584, 256], [256, 1, 1, 1] 2025-09-07T11:47:00.9859216Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:47:00.9859536Z convolution 0.0102 ms 100.0% 2025-09-07T11:47:00.9860772Z triton_convolution2d_122 0.0133 ms 76.9% 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 2025-09-07T11:47:00.9862277Z triton_convolution2d_121 0.0164 ms 62.5% 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 2025-09-07T11:47:00.9863776Z triton_convolution2d_123 0.0164 ms 62.5% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:47:00.9865337Z triton_convolution2d_124 0.0174 ms 58.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T11:47:00.9866839Z triton_convolution2d_118 0.0195 ms 52.6% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:47:00.9868323Z triton_convolution2d_119 0.0205 ms 50.0% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:47:00.9869823Z triton_convolution2d_120 0.0246 ms 41.7% 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 2025-09-07T11:47:00.9871005Z SingleProcess AUTOTUNE benchmarking takes 0.1235 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:47:01.2527256Z Autotune Choices Stats: 2025-09-07T11:47:01.2528519Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_143", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:47:01.2597499Z AUTOTUNE addmm(4x1000, 4x512, 512x1000) 2025-09-07T11:47:01.2597894Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:47:01.2598254Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:47:01.2599083Z triton_mm_143 0.0092 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 2025-09-07T11:47:01.2600318Z triton_mm_147 0.0092 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 2025-09-07T11:47:01.2601788Z triton_mm_141 0.0102 ms 90.0% 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 2025-09-07T11:47:01.2602976Z triton_mm_142 0.0102 ms 90.0% 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 2025-09-07T11:47:01.2604141Z triton_mm_146 0.0102 ms 90.0% 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 2025-09-07T11:47:01.2605320Z triton_mm_151 0.0102 ms 90.0% 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 2025-09-07T11:47:01.2606586Z triton_mm_155 0.0102 ms 90.0% 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 2025-09-07T11:47:01.2607779Z triton_mm_140 0.0113 ms 81.8% 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 2025-09-07T11:47:01.2609128Z triton_mm_150 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:47:01.2610314Z triton_mm_153 0.0113 ms 81.8% 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=4, num_warps=4 2025-09-07T11:47:01.2611338Z SingleProcess AUTOTUNE benchmarking takes 0.2687 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:47:02.8539958Z pass 2025-09-07T11:47:05.8404559Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:47:05.8406003Z import pynvml # type: ignore[import] 2025-09-07T11:47:08.6256741Z 2025-09-07T11:47:10.2035153Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:10.2035522Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:47:10.2099245Z cuda eval resnet50 2025-09-07T11:47:30.1904730Z pass 2025-09-07T11:47:33.5404203Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:47:33.5405648Z import pynvml # type: ignore[import] 2025-09-07T11:47:36.2963246Z 2025-09-07T11:47:36.4578177Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:36.4578831Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:36.4579412Z cuda eval resnet50_quantized_qat 2025-09-07T11:47:36.4584680Z Traceback (most recent call last): 2025-09-07T11:47:36.4585717Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:47:36.4586695Z ) = runner.load_model( 2025-09-07T11:47:36.4587615Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:47:36.4588665Z benchmark = benchmark_cls( 2025-09-07T11:47:36.4589437Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:47:36.4590305Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:47:36.4591395Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:47:36.4592689Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:47:36.4593592Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:47:36.4603059Z 2025-09-07T11:47:36.4603223Z model_fail_to_load 2025-09-07T11:47:38.1048872Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:47:38.1051046Z import pynvml # type: ignore[import] 2025-09-07T11:47:40.7694054Z 2025-09-07T11:47:42.2925816Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:42.2926429Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:47:42.2990275Z cuda eval resnext50_32x4d 2025-09-07T11:48:01.1094282Z Autotune Choices Stats: 2025-09-07T11:48:01.1095505Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_95", "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": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T11:48:01.1168835Z AUTOTUNE addmm(12544x256, 12544x128, 128x256) 2025-09-07T11:48:01.1169231Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T11:48:01.1169611Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:01.1170895Z triton_mm_95 0.0164 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 2025-09-07T11:48:01.1172094Z triton_mm_92 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:01.1173418Z triton_mm_93 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:48:01.1174614Z triton_mm_96 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:01.1175384Z bias_addmm 0.0195 ms 84.2% 2025-09-07T11:48:01.1176335Z triton_mm_91 0.0195 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:01.1177594Z triton_mm_87 0.0205 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:48:01.1178839Z triton_mm_88 0.0205 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:48:01.1180087Z triton_mm_89 0.0205 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:01.1181321Z triton_mm_90 0.0205 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:48:01.1182417Z SingleProcess AUTOTUNE benchmarking takes 0.3306 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T11:48:01.4995701Z Autotune Choices Stats: 2025-09-07T11:48:01.4996946Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_149", "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": 0.020479999482631683, "best_triton_pos": 0} 2025-09-07T11:48:01.5070202Z AUTOTUNE addmm(12544x256, 12544x256, 256x256) 2025-09-07T11:48:01.5070594Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:48:01.5070988Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:01.5071826Z triton_mm_149 0.0205 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 2025-09-07T11:48:01.5073352Z triton_mm_150 0.0205 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 2025-09-07T11:48:01.5074115Z bias_addmm 0.0225 ms 90.9% 2025-09-07T11:48:01.5074841Z triton_mm_145 0.0225 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:01.5076100Z triton_mm_144 0.0236 ms 87.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:48:01.5077283Z triton_mm_147 0.0236 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 2025-09-07T11:48:01.5078580Z triton_mm_146 0.0246 ms 83.3% 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 2025-09-07T11:48:01.5079936Z triton_mm_143 0.0256 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 2025-09-07T11:48:01.5081125Z triton_mm_141 0.0266 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 2025-09-07T11:48:01.5082306Z triton_mm_151 0.0266 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 2025-09-07T11:48:01.5083341Z SingleProcess AUTOTUNE benchmarking takes 0.3419 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:02.1272724Z Autotune Choices Stats: 2025-09-07T11:48:02.1274563Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_12", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:48:02.1347876Z AUTOTUNE addmm(12544x128, 12544x64, 64x128) 2025-09-07T11:48:02.1348409Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T11:48:02.1348928Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:02.1350109Z triton_mm_12 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:48:02.1351820Z triton_mm_13 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 2025-09-07T11:48:02.1353493Z triton_mm_14 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=5, num_warps=4 2025-09-07T11:48:02.1355156Z triton_mm_15 0.0113 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 2025-09-07T11:48:02.1356838Z triton_mm_19 0.0113 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 2025-09-07T11:48:02.1358586Z triton_mm_20 0.0113 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=4, num_warps=8 2025-09-07T11:48:02.1360796Z triton_mm_10 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:48:02.1363410Z triton_mm_11 0.0123 ms 91.7% 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=2, num_warps=4 2025-09-07T11:48:02.1365607Z triton_mm_16 0.0123 ms 91.7% 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 2025-09-07T11:48:02.1367791Z triton_mm_17 0.0123 ms 91.7% 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 2025-09-07T11:48:02.1369834Z SingleProcess AUTOTUNE benchmarking takes 0.3075 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T11:48:02.4990525Z Autotune Choices Stats: 2025-09-07T11:48:02.4991767Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_204", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T11:48:02.5061059Z AUTOTUNE addmm(3136x512, 3136x256, 256x512) 2025-09-07T11:48:02.5061419Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:48:02.5062100Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:02.5062949Z triton_mm_204 0.0143 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 2025-09-07T11:48:02.5064158Z triton_mm_206 0.0143 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 2025-09-07T11:48:02.5065427Z triton_mm_207 0.0143 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 2025-09-07T11:48:02.5066204Z bias_addmm 0.0154 ms 93.3% 2025-09-07T11:48:02.5066938Z triton_mm_205 0.0154 ms 93.3% 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 2025-09-07T11:48:02.5068126Z triton_mm_208 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:48:02.5069318Z triton_mm_210 0.0154 ms 93.3% 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 2025-09-07T11:48:02.5070508Z triton_mm_211 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:02.5071689Z triton_mm_212 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:48:02.5072872Z triton_mm_201 0.0164 ms 87.5% 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 2025-09-07T11:48:02.5073890Z SingleProcess AUTOTUNE benchmarking takes 0.3026 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:02.8759609Z Autotune Choices Stats: 2025-09-07T11:48:02.8760807Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_296", "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": 0.018432000651955605, "best_triton_pos": 0} 2025-09-07T11:48:02.8830274Z AUTOTUNE addmm(3136x512, 3136x512, 512x512) 2025-09-07T11:48:02.8830643Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:48:02.8831014Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:02.8832043Z triton_mm_296 0.0184 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 2025-09-07T11:48:02.8833294Z triton_mm_301 0.0184 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 2025-09-07T11:48:02.8834499Z triton_mm_302 0.0184 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 2025-09-07T11:48:02.8835266Z bias_addmm 0.0195 ms 94.7% 2025-09-07T11:48:02.8835985Z triton_mm_294 0.0195 ms 94.7% 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 2025-09-07T11:48:02.8837288Z triton_mm_295 0.0195 ms 94.7% 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 2025-09-07T11:48:02.8838462Z triton_mm_297 0.0195 ms 94.7% 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 2025-09-07T11:48:02.8839836Z triton_mm_298 0.0195 ms 94.7% 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 2025-09-07T11:48:02.8841026Z triton_mm_300 0.0205 ms 90.0% 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 2025-09-07T11:48:02.8842209Z triton_mm_292 0.0225 ms 81.8% 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 2025-09-07T11:48:02.8843238Z SingleProcess AUTOTUNE benchmarking takes 0.3139 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:03.4008293Z Autotune Choices Stats: 2025-09-07T11:48:03.4009502Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_357", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T11:48:03.4080854Z AUTOTUNE addmm(784x1024, 784x512, 512x1024) 2025-09-07T11:48:03.4081242Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T11:48:03.4081620Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:03.4082452Z triton_mm_357 0.0143 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 2025-09-07T11:48:03.4083671Z triton_mm_353 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:48:03.4084858Z triton_mm_356 0.0154 ms 93.3% 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 2025-09-07T11:48:03.4086055Z triton_mm_355 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:03.4087243Z triton_mm_362 0.0174 ms 82.4% 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 2025-09-07T11:48:03.4088436Z triton_mm_363 0.0174 ms 82.4% 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 2025-09-07T11:48:03.4089183Z bias_addmm 0.0184 ms 77.8% 2025-09-07T11:48:03.4089900Z triton_mm_354 0.0184 ms 77.8% 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 2025-09-07T11:48:03.4091352Z triton_mm_358 0.0184 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:03.4092542Z triton_mm_359 0.0195 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 2025-09-07T11:48:03.4093710Z SingleProcess AUTOTUNE benchmarking takes 0.3053 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:03.8215656Z Autotune Choices Stats: 2025-09-07T11:48:03.8216862Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_519", "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": 0.01945599913597107, "best_triton_pos": 0} 2025-09-07T11:48:03.8290608Z AUTOTUNE addmm(784x1024, 784x1024, 1024x1024) 2025-09-07T11:48:03.8290968Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T11:48:03.8291338Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:03.8292470Z triton_mm_519 0.0195 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 2025-09-07T11:48:03.8293909Z triton_mm_515 0.0215 ms 90.5% 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 2025-09-07T11:48:03.8295079Z triton_mm_518 0.0215 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:48:03.8295833Z bias_addmm 0.0236 ms 82.6% 2025-09-07T11:48:03.8296559Z triton_mm_516 0.0236 ms 82.6% 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 2025-09-07T11:48:03.8297302Z addmm 0.0256 ms 76.0% 2025-09-07T11:48:03.8298003Z triton_mm_525 0.0256 ms 76.0% 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 2025-09-07T11:48:03.8299193Z triton_mm_517 0.0266 ms 73.1% 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 2025-09-07T11:48:03.8300355Z triton_mm_520 0.0266 ms 73.1% 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 2025-09-07T11:48:03.8301545Z triton_mm_524 0.0266 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 2025-09-07T11:48:03.8302580Z SingleProcess AUTOTUNE benchmarking takes 0.3240 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:04.3906095Z Autotune Choices Stats: 2025-09-07T11:48:04.3908229Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "best_triton_kernel": "triton_mm_580", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T11:48:04.3982506Z AUTOTUNE addmm(196x2048, 196x1024, 1024x2048) 2025-09-07T11:48:04.3983037Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T11:48:04.3983560Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:04.3984161Z bias_addmm 0.0174 ms 100.0% 2025-09-07T11:48:04.3985328Z triton_mm_580 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:04.3987521Z triton_mm_576 0.0205 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:48:04.3989481Z triton_mm_579 0.0215 ms 81.0% 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 2025-09-07T11:48:04.3991517Z triton_mm_582 0.0215 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:48:04.3993628Z triton_mm_570 0.0225 ms 77.3% 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 2025-09-07T11:48:04.3995930Z triton_mm_577 0.0225 ms 77.3% 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 2025-09-07T11:48:04.3997405Z addmm 0.0236 ms 73.9% 2025-09-07T11:48:04.3998897Z triton_mm_573 0.0256 ms 68.0% 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 2025-09-07T11:48:04.4000611Z triton_mm_586 0.0256 ms 68.0% 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 2025-09-07T11:48:04.4002099Z SingleProcess AUTOTUNE benchmarking takes 0.3254 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:04.8047908Z Autotune Choices Stats: 2025-09-07T11:48:04.8050570Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "best_triton_kernel": "triton_mm_559", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T11:48:04.8120963Z AUTOTUNE addmm(196x1024, 196x2048, 2048x1024) 2025-09-07T11:48:04.8121619Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T11:48:04.8122258Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:48:04.8122923Z bias_addmm 0.0174 ms 100.0% 2025-09-07T11:48:04.8124134Z triton_mm_559 0.0195 ms 89.5% 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 2025-09-07T11:48:04.8125429Z addmm 0.0236 ms 73.9% 2025-09-07T11:48:04.8126687Z triton_mm_555 0.0256 ms 68.0% 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 2025-09-07T11:48:04.8128915Z triton_mm_558 0.0256 ms 68.0% 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 2025-09-07T11:48:04.8131086Z triton_mm_552 0.0276 ms 63.0% 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 2025-09-07T11:48:04.8133257Z triton_mm_562 0.0297 ms 58.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:48:04.8135472Z triton_mm_553 0.0328 ms 53.1% 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 2025-09-07T11:48:04.8137600Z triton_mm_554 0.0328 ms 53.1% 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 2025-09-07T11:48:04.8139942Z triton_mm_561 0.0328 ms 53.1% 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 2025-09-07T11:48:04.8141838Z SingleProcess AUTOTUNE benchmarking takes 0.3443 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:48:08.5804927Z pass 2025-09-07T11:48:12.0679368Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:48:12.0680801Z import pynvml # type: ignore[import] 2025-09-07T11:48:14.7824495Z 2025-09-07T11:48:22.7845644Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:48:22.7846026Z loading model: 0it [00:08, ?it/s] 2025-09-07T11:48:22.7972233Z cuda eval sam 2025-09-07T11:49:25.6342555Z Autotune Choices Stats: 2025-09-07T11:49:25.6344533Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.22118400037288666, "best_triton_pos": 1, "best_triton_time": 0.27238398790359497, "best_triton_kernel": "triton_mm_127", "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"} 2025-09-07T11:49:25.6421985Z AUTOTUNE mm(4096x1280, 1280x5120) 2025-09-07T11:49:25.6422321Z strides: [1280, 1], [1, 1280] 2025-09-07T11:49:25.6422633Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:25.6422957Z mm 0.2212 ms 100.0% 2025-09-07T11:49:25.6423680Z triton_mm_127 0.2724 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:25.6424886Z triton_mm_126 0.2847 ms 77.7% 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 2025-09-07T11:49:25.6426160Z triton_mm_122 0.3000 ms 73.7% 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 2025-09-07T11:49:25.6427352Z triton_mm_123 0.3123 ms 70.8% 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 2025-09-07T11:49:25.6428537Z triton_mm_120 0.3164 ms 69.9% 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 2025-09-07T11:49:25.6429725Z triton_mm_128 0.3553 ms 62.2% 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 2025-09-07T11:49:25.6430917Z triton_mm_121 0.3615 ms 61.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:25.6432105Z triton_mm_125 0.3727 ms 59.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T11:49:25.6433284Z triton_mm_124 0.3768 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 2025-09-07T11:49:25.6434307Z SingleProcess AUTOTUNE benchmarking takes 0.7309 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:27.2749238Z Autotune Choices Stats: 2025-09-07T11:49:27.2751222Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4518", "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": 0.2549760043621063, "best_triton_pos": 0} 2025-09-07T11:49:27.2883768Z AUTOTUNE mm(4096x5120, 5120x1280) 2025-09-07T11:49:27.2884397Z strides: [5120, 1], [1, 5120] 2025-09-07T11:49:27.2884952Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:27.2886476Z triton_mm_4518 0.2550 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 2025-09-07T11:49:27.2887931Z mm 0.2570 ms 99.2% 2025-09-07T11:49:27.2889266Z triton_mm_4517 0.2775 ms 91.9% 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 2025-09-07T11:49:27.2891618Z triton_mm_4513 0.3062 ms 83.3% 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 2025-09-07T11:49:27.2894617Z triton_mm_4511 0.3072 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=3, num_warps=4 2025-09-07T11:49:27.2896942Z triton_mm_4514 0.3113 ms 81.9% 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 2025-09-07T11:49:27.2899596Z triton_mm_4519 0.3267 ms 78.1% 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 2025-09-07T11:49:27.2901946Z triton_mm_4512 0.3512 ms 72.6% 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 2025-09-07T11:49:27.2904262Z triton_mm_4508 0.3604 ms 70.7% 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 2025-09-07T11:49:27.2906610Z triton_mm_4509 0.3676 ms 69.4% 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 2025-09-07T11:49:27.2908571Z SingleProcess AUTOTUNE benchmarking takes 0.7623 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:28.5451804Z Autotune Choices Stats: 2025-09-07T11:49:28.5453368Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4595", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:28.5544405Z AUTOTUNE mm(4096x256, 256x128) 2025-09-07T11:49:28.5544768Z strides: [1, 4096], [1, 256] 2025-09-07T11:49:28.5545135Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:28.5545943Z triton_mm_4595 0.0113 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 2025-09-07T11:49:28.5547204Z triton_mm_4596 0.0113 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 2025-09-07T11:49:28.5548408Z triton_mm_4598 0.0113 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=4, num_warps=8 2025-09-07T11:49:28.5549159Z mm 0.0123 ms 91.7% 2025-09-07T11:49:28.5549853Z triton_mm_4586 0.0123 ms 91.7% 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 2025-09-07T11:49:28.5551044Z triton_mm_4592 0.0123 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 2025-09-07T11:49:28.5552229Z triton_mm_4594 0.0123 ms 91.7% 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 2025-09-07T11:49:28.5553684Z triton_mm_4597 0.0123 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 2025-09-07T11:49:28.5554861Z triton_mm_4588 0.0133 ms 84.6% 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 2025-09-07T11:49:28.5556043Z triton_mm_4587 0.0143 ms 78.6% 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 2025-09-07T11:49:28.5557067Z SingleProcess AUTOTUNE benchmarking takes 0.2892 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:29.2002804Z Autotune Choices Stats: 2025-09-07T11:49:29.2004047Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4621", "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=2, num_warps=2", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:29.2074815Z AUTOTUNE mm(5x256, 256x2048) 2025-09-07T11:49:29.2075566Z strides: [256, 1], [1, 256] 2025-09-07T11:49:29.2075867Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:29.2076650Z triton_mm_4621 0.0092 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=2, num_warps=2 2025-09-07T11:49:29.2077864Z triton_mm_4622 0.0092 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=5, num_warps=4 2025-09-07T11:49:29.2079068Z triton_mm_4623 0.0092 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 2025-09-07T11:49:29.2080257Z triton_mm_4627 0.0092 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 2025-09-07T11:49:29.2081467Z triton_mm_4628 0.0092 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 2025-09-07T11:49:29.2082674Z triton_mm_4631 0.0092 ms 100.0% 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 2025-09-07T11:49:29.2083887Z triton_mm_4632 0.0092 ms 100.0% 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 2025-09-07T11:49:29.2085094Z triton_mm_4634 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:29.2086296Z triton_mm_4636 0.0092 ms 100.0% 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 2025-09-07T11:49:29.2087499Z triton_mm_4629 0.0102 ms 90.0% 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 2025-09-07T11:49:29.2088520Z SingleProcess AUTOTUNE benchmarking takes 0.2980 seconds and 0.0004 seconds precompiling for 18 choices 2025-09-07T11:49:29.7614136Z Autotune Choices Stats: 2025-09-07T11:49:29.7615398Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5022", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:49:29.7691605Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T11:49:29.7691918Z strides: [256, 1], [1, 256] 2025-09-07T11:49:29.7692218Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:29.7693261Z triton_mm_5022 0.0072 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 2025-09-07T11:49:29.7694022Z mm 0.0082 ms 87.5% 2025-09-07T11:49:29.7694724Z triton_mm_5019 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:49:29.7695918Z triton_mm_5020 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:29.7697300Z triton_mm_5021 0.0082 ms 87.5% 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 2025-09-07T11:49:29.7698500Z triton_mm_5025 0.0082 ms 87.5% 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 2025-09-07T11:49:29.7699877Z triton_mm_5026 0.0082 ms 87.5% 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 2025-09-07T11:49:29.7701070Z triton_mm_5030 0.0082 ms 87.5% 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 2025-09-07T11:49:29.7702276Z triton_mm_5034 0.0082 ms 87.5% 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 2025-09-07T11:49:29.7703473Z triton_mm_5028 0.0092 ms 77.8% 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 2025-09-07T11:49:29.7704518Z SingleProcess AUTOTUNE benchmarking takes 0.2431 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:49:30.3069797Z Autotune Choices Stats: 2025-09-07T11:49:30.3071072Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_5039", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:49:30.3144423Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T11:49:30.3144769Z strides: [256, 1], [1, 256] 2025-09-07T11:49:30.3145148Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:30.3145951Z triton_mm_5039 0.0072 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 2025-09-07T11:49:30.3146739Z mm 0.0082 ms 87.5% 2025-09-07T11:49:30.3147435Z triton_mm_5036 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:49:30.3148634Z triton_mm_5037 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:30.3149803Z triton_mm_5038 0.0082 ms 87.5% 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 2025-09-07T11:49:30.3150979Z triton_mm_5042 0.0082 ms 87.5% 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 2025-09-07T11:49:30.3152166Z triton_mm_5043 0.0082 ms 87.5% 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 2025-09-07T11:49:30.3153644Z triton_mm_5047 0.0082 ms 87.5% 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 2025-09-07T11:49:30.3154850Z triton_mm_5045 0.0092 ms 77.8% 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 2025-09-07T11:49:30.3156043Z triton_mm_5046 0.0092 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:30.3157079Z SingleProcess AUTOTUNE benchmarking takes 0.2340 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:49:30.5661981Z Autotune Choices Stats: 2025-09-07T11:49:30.5665325Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.0071680000983178616, "best_triton_pos": 1, "best_triton_time": 0.0071680000983178616, "best_triton_kernel": "triton_mm_5067", "best_triton_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"} 2025-09-07T11:49:30.5736389Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T11:49:30.5736751Z strides: [256, 1], [1, 256] 2025-09-07T11:49:30.5737052Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:30.5737358Z mm 0.0072 ms 100.0% 2025-09-07T11:49:30.5738086Z triton_mm_5067 0.0072 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 2025-09-07T11:49:30.5739309Z triton_mm_5064 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:49:30.5740506Z triton_mm_5065 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:30.5741700Z triton_mm_5066 0.0082 ms 87.5% 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 2025-09-07T11:49:30.5742868Z triton_mm_5070 0.0082 ms 87.5% 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 2025-09-07T11:49:30.5744059Z triton_mm_5071 0.0082 ms 87.5% 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 2025-09-07T11:49:30.5745339Z triton_mm_5075 0.0082 ms 87.5% 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 2025-09-07T11:49:30.5746548Z triton_mm_5073 0.0092 ms 77.8% 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 2025-09-07T11:49:30.5747752Z triton_mm_5074 0.0092 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:30.5748786Z SingleProcess AUTOTUNE benchmarking takes 0.2363 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T11:49:30.8411940Z Autotune Choices Stats: 2025-09-07T11:49:30.8413720Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.008191999979317188, "best_triton_pos": 1, "best_triton_time": 0.008191999979317188, "best_triton_kernel": "triton_mm_5109", "best_triton_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=2, num_warps=2"} 2025-09-07T11:49:30.8486518Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T11:49:30.8487065Z strides: [256, 1], [1, 256] 2025-09-07T11:49:30.8487365Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:30.8487678Z mm 0.0082 ms 100.0% 2025-09-07T11:49:30.8488404Z triton_mm_5109 0.0082 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=2, num_warps=2 2025-09-07T11:49:30.8489613Z triton_mm_5110 0.0082 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=5, num_warps=4 2025-09-07T11:49:30.8490807Z triton_mm_5111 0.0082 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 2025-09-07T11:49:30.8492006Z triton_mm_5112 0.0082 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 2025-09-07T11:49:30.8493429Z triton_mm_5115 0.0082 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 2025-09-07T11:49:30.8494831Z triton_mm_5116 0.0082 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 2025-09-07T11:49:30.8496039Z triton_mm_5119 0.0082 ms 100.0% 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 2025-09-07T11:49:30.8497255Z triton_mm_5120 0.0082 ms 100.0% 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 2025-09-07T11:49:30.8498465Z triton_mm_5118 0.0092 ms 88.9% 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 2025-09-07T11:49:30.8499511Z SingleProcess AUTOTUNE benchmarking takes 0.2353 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:49:31.1141475Z Autotune Choices Stats: 2025-09-07T11:49:31.1143051Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.0071680000983178616, "best_triton_pos": 1, "best_triton_time": 0.0071680000983178616, "best_triton_kernel": "triton_mm_5157", "best_triton_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"} 2025-09-07T11:49:31.1216339Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T11:49:31.1216646Z strides: [256, 1], [1, 256] 2025-09-07T11:49:31.1216945Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:31.1217246Z mm 0.0072 ms 100.0% 2025-09-07T11:49:31.1217968Z triton_mm_5157 0.0072 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 2025-09-07T11:49:31.1219187Z triton_mm_5154 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:49:31.1220382Z triton_mm_5155 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:31.1221571Z triton_mm_5156 0.0082 ms 87.5% 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 2025-09-07T11:49:31.1222763Z triton_mm_5160 0.0082 ms 87.5% 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 2025-09-07T11:49:31.1223940Z triton_mm_5161 0.0082 ms 87.5% 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 2025-09-07T11:49:31.1229141Z triton_mm_5164 0.0082 ms 87.5% 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 2025-09-07T11:49:31.1230363Z triton_mm_5165 0.0082 ms 87.5% 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 2025-09-07T11:49:31.1231563Z triton_mm_5167 0.0082 ms 87.5% 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 2025-09-07T11:49:31.1232591Z SingleProcess AUTOTUNE benchmarking takes 0.2334 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T11:49:31.8936235Z Autotune Choices Stats: 2025-09-07T11:49:31.8937748Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.21913599967956543, "best_triton_pos": 1, "best_triton_time": 0.2385919988155365, "best_triton_kernel": "triton_mm_23", "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"} 2025-09-07T11:49:31.9011725Z AUTOTUNE mm(4900x1280, 1280x3840) 2025-09-07T11:49:31.9012093Z strides: [1280, 1], [1, 1280] 2025-09-07T11:49:31.9012402Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:31.9012707Z mm 0.2191 ms 100.0% 2025-09-07T11:49:31.9013626Z triton_mm_23 0.2386 ms 91.8% 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 2025-09-07T11:49:31.9014841Z triton_mm_22 0.2580 ms 84.9% 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 2025-09-07T11:49:31.9016037Z triton_mm_18 0.2755 ms 79.6% 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 2025-09-07T11:49:31.9017225Z triton_mm_19 0.2847 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 2025-09-07T11:49:31.9018402Z triton_mm_16 0.2939 ms 74.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:31.9019592Z triton_mm_24 0.3256 ms 67.3% 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 2025-09-07T11:49:31.9020757Z triton_mm_17 0.3267 ms 67.1% 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 2025-09-07T11:49:31.9021932Z triton_mm_20 0.3502 ms 62.6% 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 2025-09-07T11:49:31.9023102Z triton_mm_13 0.3512 ms 62.4% 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 2025-09-07T11:49:31.9024123Z SingleProcess AUTOTUNE benchmarking takes 0.7013 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:49:32.6567996Z Autotune Choices Stats: 2025-09-07T11:49:32.6569480Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.07782399654388428, "best_triton_pos": 1, "best_triton_time": 0.08499199897050858, "best_triton_kernel": "triton_mm_109", "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"} 2025-09-07T11:49:32.6644129Z AUTOTUNE mm(4900x1280, 1280x1280) 2025-09-07T11:49:32.6644447Z strides: [1280, 1], [1, 1280] 2025-09-07T11:49:32.6644735Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:32.6645044Z mm 0.0778 ms 100.0% 2025-09-07T11:49:32.6645754Z triton_mm_109 0.0850 ms 91.6% 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 2025-09-07T11:49:32.6646947Z triton_mm_108 0.0942 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 2025-09-07T11:49:32.6648131Z triton_mm_104 0.0983 ms 79.2% 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 2025-09-07T11:49:32.6649445Z triton_mm_105 0.0993 ms 78.4% 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 2025-09-07T11:49:32.6650630Z triton_mm_102 0.1085 ms 71.7% 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 2025-09-07T11:49:32.6652016Z triton_mm_110 0.1096 ms 71.0% 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 2025-09-07T11:49:32.6653442Z triton_mm_106 0.1147 ms 67.9% 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 2025-09-07T11:49:32.6654630Z triton_mm_107 0.1167 ms 66.7% 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 2025-09-07T11:49:32.6655816Z triton_mm_103 0.1188 ms 65.5% 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 2025-09-07T11:49:32.6656837Z SingleProcess AUTOTUNE benchmarking takes 0.5065 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:34.3236947Z Autotune Choices Stats: 2025-09-07T11:49:34.3238226Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1093", "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": 0.06656000018119812, "best_triton_pos": 0} 2025-09-07T11:49:34.3316414Z AUTOTUNE mm(4096x1280, 1280x1280) 2025-09-07T11:49:34.3316733Z strides: [1280, 1], [1, 1280] 2025-09-07T11:49:34.3317027Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:34.3317813Z triton_mm_1093 0.0666 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 2025-09-07T11:49:34.3319042Z triton_mm_1088 0.0758 ms 87.8% 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 2025-09-07T11:49:34.3320253Z triton_mm_1092 0.0758 ms 87.8% 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 2025-09-07T11:49:34.3321003Z mm 0.0778 ms 85.5% 2025-09-07T11:49:34.3321692Z triton_mm_1089 0.0778 ms 85.5% 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 2025-09-07T11:49:34.3322869Z triton_mm_1086 0.0819 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 2025-09-07T11:49:34.3324066Z triton_mm_1094 0.0850 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 2025-09-07T11:49:34.3325581Z triton_mm_1087 0.0881 ms 75.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:34.3326780Z triton_mm_1090 0.0881 ms 75.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:34.3327967Z triton_mm_1084 0.1034 ms 64.4% 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 2025-09-07T11:49:34.3329000Z SingleProcess AUTOTUNE benchmarking takes 0.4669 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:36.7504978Z Autotune Choices Stats: 2025-09-07T11:49:36.7506421Z {"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": 0.45875200629234314, "best_triton_pos": 0} 2025-09-07T11:49:36.7586152Z AUTOTUNE convolution(1x3x1024x1024, 1280x3x16x16) 2025-09-07T11:49:36.7587029Z strides: [3145728, 1048576, 1024, 1], [768, 256, 16, 1] 2025-09-07T11:49:36.7587422Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:36.7588354Z triton_convolution2d_6 0.4588 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 2025-09-07T11:49:36.7589876Z triton_convolution2d_1 0.4762 ms 96.3% 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 2025-09-07T11:49:36.7591392Z triton_convolution2d_3 0.5212 ms 88.0% 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 2025-09-07T11:49:36.7592306Z convolution 0.5530 ms 83.0% 2025-09-07T11:49:36.7593191Z triton_convolution2d_5 0.8069 ms 56.9% 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 2025-09-07T11:49:36.7594686Z triton_convolution2d_4 0.8745 ms 52.5% 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 2025-09-07T11:49:36.7596187Z triton_convolution2d_0 0.9032 ms 50.8% 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 2025-09-07T11:49:36.7597698Z triton_convolution2d_2 2.1484 ms 21.4% 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 2025-09-07T11:49:36.7598883Z SingleProcess AUTOTUNE benchmarking takes 0.3179 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:49:37.1404307Z Autotune Choices Stats: 2025-09-07T11:49:37.1405506Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_34", "best_kernel_desc": "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", "best_time": 0.06143999844789505, "best_triton_pos": 0} 2025-09-07T11:49:37.1481442Z AUTOTUNE bmm(400x196x80, 400x80x196) 2025-09-07T11:49:37.1481808Z strides: [80, 32000, 1], [15680, 1, 80] 2025-09-07T11:49:37.1482145Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:37.1482909Z triton_bmm_34 0.0614 ms 100.0% 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 2025-09-07T11:49:37.1484319Z triton_bmm_37 0.0614 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=3, num_warps=4 2025-09-07T11:49:37.1485530Z triton_bmm_35 0.0676 ms 90.9% 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 2025-09-07T11:49:37.1486724Z triton_bmm_38 0.0686 ms 89.6% 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 2025-09-07T11:49:37.1487920Z triton_bmm_40 0.0707 ms 87.0% 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 2025-09-07T11:49:37.1489232Z triton_bmm_41 0.0717 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:37.1490591Z triton_bmm_36 0.0727 ms 84.5% 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 2025-09-07T11:49:37.1491780Z triton_bmm_39 0.0727 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T11:49:37.1493194Z triton_bmm_31 0.0778 ms 78.9% 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 2025-09-07T11:49:37.1494378Z triton_bmm_30 0.0829 ms 74.1% 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 2025-09-07T11:49:37.1495406Z SingleProcess AUTOTUNE benchmarking takes 0.3879 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:37.3872589Z Autotune Choices Stats: 2025-09-07T11:49:37.3873776Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_43", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.023552000522613525, "best_triton_pos": 0} 2025-09-07T11:49:37.3951842Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T11:49:37.3952171Z strides: [448000, 80, 1], [1120, 1, 80] 2025-09-07T11:49:37.3952516Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:37.3953283Z triton_bmm_43 0.0236 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:49:37.3954480Z triton_bmm_48 0.0236 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:37.3955687Z triton_bmm_51 0.0236 ms 100.0% 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=3, num_warps=4 2025-09-07T11:49:37.3956880Z triton_bmm_52 0.0236 ms 100.0% 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 2025-09-07T11:49:37.3958067Z triton_bmm_54 0.0236 ms 100.0% 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 2025-09-07T11:49:37.3959277Z triton_bmm_55 0.0236 ms 100.0% 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 2025-09-07T11:49:37.3960676Z triton_bmm_45 0.0246 ms 95.8% 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 2025-09-07T11:49:37.3961864Z triton_bmm_46 0.0246 ms 95.8% 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=5, num_warps=4 2025-09-07T11:49:37.3963048Z triton_bmm_47 0.0246 ms 95.8% 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 2025-09-07T11:49:37.3964238Z triton_bmm_50 0.0246 ms 95.8% 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 2025-09-07T11:49:37.3965266Z SingleProcess AUTOTUNE benchmarking takes 0.2464 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:49:37.6354024Z Autotune Choices Stats: 2025-09-07T11:49:37.6355182Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_67", "best_kernel_desc": "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", "best_time": 0.02457600086927414, "best_triton_pos": 0} 2025-09-07T11:49:37.6433972Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T11:49:37.6434361Z strides: [80, 1120, 1], [1120, 1, 80] 2025-09-07T11:49:37.6434689Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:37.6435471Z triton_bmm_67 0.0246 ms 100.0% 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=3, num_warps=4 2025-09-07T11:49:37.6436683Z triton_bmm_68 0.0246 ms 100.0% 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 2025-09-07T11:49:37.6437899Z triton_bmm_71 0.0246 ms 100.0% 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 2025-09-07T11:49:37.6439104Z triton_bmm_59 0.0256 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T11:49:37.6440287Z triton_bmm_61 0.0256 ms 96.0% 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 2025-09-07T11:49:37.6441465Z triton_bmm_62 0.0256 ms 96.0% 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 2025-09-07T11:49:37.6442634Z triton_bmm_64 0.0256 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:37.6443810Z triton_bmm_70 0.0256 ms 96.0% 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 2025-09-07T11:49:37.6445014Z triton_bmm_73 0.0256 ms 96.0% 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 2025-09-07T11:49:37.6446206Z triton_bmm_63 0.0266 ms 92.3% 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 2025-09-07T11:49:37.6447233Z SingleProcess AUTOTUNE benchmarking takes 0.2475 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:49:38.0332064Z Autotune Choices Stats: 2025-09-07T11:49:38.0334283Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_90", "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": 0.06860800087451935, "best_triton_pos": 0} 2025-09-07T11:49:38.0414034Z AUTOTUNE bmm(400x196x196, 400x196x80) 2025-09-07T11:49:38.0414627Z strides: [38464, 196, 1], [15680, 80, 1] 2025-09-07T11:49:38.0415215Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:38.0416660Z triton_bmm_90 0.0686 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 2025-09-07T11:49:38.0418856Z triton_bmm_84 0.0717 ms 95.7% 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 2025-09-07T11:49:38.0421020Z triton_bmm_85 0.0717 ms 95.7% 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 2025-09-07T11:49:38.0423497Z triton_bmm_87 0.0748 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:38.0426111Z triton_bmm_86 0.0758 ms 90.5% 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 2025-09-07T11:49:38.0428269Z triton_bmm_88 0.0778 ms 88.2% 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 2025-09-07T11:49:38.0430420Z triton_bmm_89 0.0778 ms 88.2% 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 2025-09-07T11:49:38.0431790Z bmm 0.0809 ms 84.8% 2025-09-07T11:49:38.0433040Z triton_bmm_81 0.0819 ms 83.8% 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 2025-09-07T11:49:38.0435202Z triton_bmm_82 0.0870 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 2025-09-07T11:49:38.0437055Z SingleProcess AUTOTUNE benchmarking takes 0.3974 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:38.8573455Z Autotune Choices Stats: 2025-09-07T11:49:38.8576124Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.1669120043516159, "best_triton_pos": 1, "best_triton_time": 0.19046400487422943, "best_triton_kernel": "triton_mm_1003", "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"} 2025-09-07T11:49:38.8656011Z AUTOTUNE addmm(4096x3840, 4096x1280, 1280x3840) 2025-09-07T11:49:38.8656659Z strides: [0, 1], [1280, 1], [1, 1280] 2025-09-07T11:49:38.8657305Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:49:38.8657883Z bias_addmm 0.1669 ms 100.0% 2025-09-07T11:49:38.8659197Z triton_mm_1003 0.1905 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:38.8661492Z triton_mm_1002 0.2089 ms 79.9% 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 2025-09-07T11:49:38.8663704Z triton_mm_998 0.2396 ms 69.7% 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 2025-09-07T11:49:38.8665859Z triton_mm_999 0.2499 ms 66.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:38.8668080Z triton_mm_996 0.2540 ms 65.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:38.8670606Z triton_mm_1004 0.2724 ms 61.3% 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 2025-09-07T11:49:38.8671886Z addmm 0.2775 ms 60.1% 2025-09-07T11:49:38.8673124Z triton_mm_997 0.2826 ms 59.1% 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 2025-09-07T11:49:38.8675355Z triton_mm_1000 0.3072 ms 54.3% 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 2025-09-07T11:49:38.8677275Z SingleProcess AUTOTUNE benchmarking takes 0.7390 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:49:39.5940351Z Autotune Choices Stats: 2025-09-07T11:49:39.5942516Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_1020", "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": 0.4997119903564453, "best_triton_pos": 0} 2025-09-07T11:49:39.6023186Z AUTOTUNE bmm(16x4096x80, 16x80x4096) 2025-09-07T11:49:39.6023780Z strides: [80, 1280, 1], [80, 1, 3840] 2025-09-07T11:49:39.6024336Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:39.6025671Z triton_bmm_1020 0.4997 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 2025-09-07T11:49:39.6027939Z triton_bmm_1014 0.5202 ms 96.1% 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 2025-09-07T11:49:39.6030216Z triton_bmm_1017 0.5540 ms 90.2% 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 2025-09-07T11:49:39.6032396Z triton_bmm_1019 0.5663 ms 88.2% 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 2025-09-07T11:49:39.6034599Z triton_bmm_1021 0.5960 ms 83.8% 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 2025-09-07T11:49:39.6036886Z triton_bmm_1011 0.6369 ms 78.5% 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 2025-09-07T11:49:39.6039093Z triton_bmm_1018 0.6431 ms 77.7% 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 2025-09-07T11:49:39.6041082Z triton_bmm_1015 0.6441 ms 77.6% 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 2025-09-07T11:49:39.6043380Z triton_bmm_1016 0.6625 ms 75.4% 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 2025-09-07T11:49:39.6044760Z bmm 0.6656 ms 75.1% 2025-09-07T11:49:39.6045693Z SingleProcess AUTOTUNE benchmarking takes 0.7350 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:39.8735680Z Autotune Choices Stats: 2025-09-07T11:49:39.8737876Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_1034", "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": 0.025599999353289604, "best_triton_pos": 0} 2025-09-07T11:49:39.8816988Z AUTOTUNE bmm(64x1024x80, 64x80x64) 2025-09-07T11:49:39.8823218Z strides: [81920, 80, 1], [5120, 1, 80] 2025-09-07T11:49:39.8823795Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:39.8825326Z triton_bmm_1034 0.0256 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 2025-09-07T11:49:39.8827485Z triton_bmm_1036 0.0256 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=3, num_warps=4 2025-09-07T11:49:39.8829698Z triton_bmm_1037 0.0256 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 2025-09-07T11:49:39.8832070Z triton_bmm_1029 0.0266 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 2025-09-07T11:49:39.8834528Z triton_bmm_1030 0.0266 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 2025-09-07T11:49:39.8836928Z triton_bmm_1032 0.0266 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=3, num_warps=4 2025-09-07T11:49:39.8839103Z triton_bmm_1033 0.0266 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=4, num_warps=8 2025-09-07T11:49:39.8841388Z triton_bmm_1038 0.0266 ms 96.2% 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=2, num_warps=8 2025-09-07T11:49:39.8843667Z triton_bmm_1039 0.0266 ms 96.2% 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 2025-09-07T11:49:39.8845939Z triton_bmm_1028 0.0276 ms 92.6% 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=2, num_warps=4 2025-09-07T11:49:39.8847822Z SingleProcess AUTOTUNE benchmarking takes 0.2789 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:40.6024215Z Autotune Choices Stats: 2025-09-07T11:49:40.6027140Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "bmm", "best_time": 0.45158401131629944, "best_triton_pos": 1, "best_triton_time": 0.45875200629234314, "best_triton_kernel": "triton_bmm_1075", "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"} 2025-09-07T11:49:40.6109264Z AUTOTUNE bmm(16x4096x4096, 16x4096x80) 2025-09-07T11:49:40.6109933Z strides: [16777216, 4096, 1], [80, 3840, 1] 2025-09-07T11:49:40.6110558Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:40.6111126Z bmm 0.4516 ms 100.0% 2025-09-07T11:49:40.6112508Z triton_bmm_1075 0.4588 ms 98.4% 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 2025-09-07T11:49:40.6114933Z triton_bmm_1076 0.4628 ms 97.6% 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 2025-09-07T11:49:40.6117340Z triton_bmm_1070 0.4813 ms 93.8% 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 2025-09-07T11:49:40.6119725Z triton_bmm_1066 0.5673 ms 79.6% 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 2025-09-07T11:49:40.6122115Z triton_bmm_1067 0.6124 ms 73.7% 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 2025-09-07T11:49:40.6124815Z triton_bmm_1074 0.6533 ms 69.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:40.6127215Z triton_bmm_1069 0.6605 ms 68.4% 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 2025-09-07T11:49:40.6129597Z triton_bmm_1068 0.6666 ms 67.7% 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 2025-09-07T11:49:40.6131992Z triton_bmm_1071 0.6912 ms 65.3% 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 2025-09-07T11:49:40.6134515Z SingleProcess AUTOTUNE benchmarking takes 0.7263 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:49:41.1921354Z Autotune Choices Stats: 2025-09-07T11:49:41.1924049Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4468", "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=2, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T11:49:41.2008661Z AUTOTUNE mm(5x256, 256x256) 2025-09-07T11:49:41.2009223Z strides: [256, 1], [1, 256] 2025-09-07T11:49:41.2009771Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:41.2011200Z triton_mm_4468 0.0082 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=2, num_warps=2 2025-09-07T11:49:41.2013728Z triton_mm_4469 0.0082 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=5, num_warps=4 2025-09-07T11:49:41.2015938Z triton_mm_4470 0.0082 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 2025-09-07T11:49:41.2018156Z triton_mm_4471 0.0082 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 2025-09-07T11:49:41.2020322Z triton_mm_4474 0.0082 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 2025-09-07T11:49:41.2022552Z triton_mm_4475 0.0082 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 2025-09-07T11:49:41.2024785Z triton_mm_4478 0.0082 ms 100.0% 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 2025-09-07T11:49:41.2027081Z triton_mm_4481 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:41.2029298Z triton_mm_4477 0.0092 ms 88.9% 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 2025-09-07T11:49:41.2031514Z triton_mm_4479 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:41.2033408Z SingleProcess AUTOTUNE benchmarking takes 0.2377 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T11:49:41.3910264Z Autotune Choices Stats: 2025-09-07T11:49:41.3912747Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.04608000069856644, "best_triton_kernel": "triton_convolution2d_4524", "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"} 2025-09-07T11:49:41.3995666Z AUTOTUNE convolution(1x1280x64x64, 256x1280x1x1) 2025-09-07T11:49:41.3996248Z strides: [5242880, 4096, 64, 1], [1280, 1, 1, 1] 2025-09-07T11:49:41.3996763Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:41.3997212Z convolution 0.0276 ms 100.0% 2025-09-07T11:49:41.3998487Z triton_convolution2d_4524 0.0461 ms 60.0% 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 2025-09-07T11:49:41.4000070Z conv1x1_via_mm 0.0492 ms 56.2% 2025-09-07T11:49:41.4001360Z triton_convolution2d_4526 0.0594 ms 46.6% 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 2025-09-07T11:49:41.4003858Z triton_convolution2d_4523 0.0625 ms 44.3% 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 2025-09-07T11:49:41.4006042Z triton_convolution2d_4525 0.0676 ms 40.9% 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 2025-09-07T11:49:41.4008198Z triton_convolution2d_4521 0.0758 ms 36.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T11:49:41.4010349Z triton_convolution2d_4520 0.0860 ms 32.1% 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 2025-09-07T11:49:41.4012507Z triton_convolution2d_4522 0.1270 ms 21.8% 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 2025-09-07T11:49:41.4014548Z SingleProcess AUTOTUNE benchmarking takes 0.1963 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T11:49:41.6487702Z Autotune Choices Stats: 2025-09-07T11:49:41.6490940Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.06143999844789505, "best_triton_pos": 1, "best_triton_time": 0.13516800105571747, "best_triton_kernel": "triton_convolution2d_4533", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T11:49:41.6574153Z AUTOTUNE convolution(1x256x64x64, 256x256x3x3) 2025-09-07T11:49:41.6574871Z strides: [1048576, 4096, 64, 1], [2304, 9, 3, 1] 2025-09-07T11:49:41.6575513Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:41.6576108Z convolution 0.0614 ms 100.0% 2025-09-07T11:49:41.6577864Z triton_convolution2d_4533 0.1352 ms 45.5% 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 2025-09-07T11:49:41.6580848Z triton_convolution2d_4531 0.1597 ms 38.5% 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 2025-09-07T11:49:41.6583825Z triton_convolution2d_4530 0.1720 ms 35.7% 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 2025-09-07T11:49:41.6587161Z triton_convolution2d_4528 0.1731 ms 35.5% 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 2025-09-07T11:49:41.6590143Z triton_convolution2d_4532 0.2468 ms 24.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T11:49:41.6593117Z triton_convolution2d_4527 0.2796 ms 22.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T11:49:41.6596097Z triton_convolution2d_4529 0.3656 ms 16.8% 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 2025-09-07T11:49:41.6598570Z SingleProcess AUTOTUNE benchmarking takes 0.2557 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T11:49:41.8704766Z Autotune Choices Stats: 2025-09-07T11:49:41.8707452Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_4535", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:49:41.8792787Z AUTOTUNE mm(4096x2, 2x128) 2025-09-07T11:49:41.8793243Z strides: [2, 1], [128, 1] 2025-09-07T11:49:41.8793640Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:41.8794753Z triton_mm_4535 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:41.8796488Z triton_mm_4536 0.0072 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 2025-09-07T11:49:41.8798254Z triton_mm_4537 0.0072 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=8 2025-09-07T11:49:41.8800032Z triton_mm_4538 0.0072 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 2025-09-07T11:49:41.8801737Z triton_mm_4539 0.0072 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 2025-09-07T11:49:41.8803478Z triton_mm_4540 0.0072 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 2025-09-07T11:49:41.8805242Z triton_mm_4541 0.0072 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 2025-09-07T11:49:41.8806979Z triton_mm_4542 0.0072 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 2025-09-07T11:49:41.8808677Z triton_mm_4543 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:41.8810388Z triton_mm_4544 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:41.8811860Z SingleProcess AUTOTUNE benchmarking takes 0.2197 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T11:49:42.1295933Z Autotune Choices Stats: 2025-09-07T11:49:42.1298411Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4559", "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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T11:49:42.1382229Z AUTOTUNE mm(4096x256, 256x256) 2025-09-07T11:49:42.1382815Z strides: [256, 1], [256, 1] 2025-09-07T11:49:42.1383293Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:42.1384742Z triton_mm_4559 0.0133 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 2025-09-07T11:49:42.1387116Z triton_mm_4561 0.0133 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 2025-09-07T11:49:42.1389597Z triton_mm_4562 0.0133 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 2025-09-07T11:49:42.1391852Z triton_mm_4566 0.0133 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 2025-09-07T11:49:42.1393520Z mm 0.0143 ms 92.9% 2025-09-07T11:49:42.1394768Z triton_mm_4557 0.0143 ms 92.9% 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 2025-09-07T11:49:42.1396965Z triton_mm_4560 0.0143 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 2025-09-07T11:49:42.1399169Z triton_mm_4563 0.0143 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=4, num_warps=8 2025-09-07T11:49:42.1401393Z triton_mm_4565 0.0143 ms 92.9% 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 2025-09-07T11:49:42.1403635Z triton_mm_4567 0.0143 ms 92.9% 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 2025-09-07T11:49:42.1405554Z SingleProcess AUTOTUNE benchmarking takes 0.2583 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:42.3973911Z Autotune Choices Stats: 2025-09-07T11:49:42.3975604Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_4569", "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=2, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T11:49:42.4061910Z AUTOTUNE addmm(5x128, 5x256, 256x128) 2025-09-07T11:49:42.4062410Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:49:42.4062940Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:49:42.4064133Z triton_mm_4569 0.0082 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=2, num_warps=2 2025-09-07T11:49:42.4065896Z triton_mm_4570 0.0082 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=5, num_warps=4 2025-09-07T11:49:42.4067566Z triton_mm_4571 0.0082 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 2025-09-07T11:49:42.4069248Z triton_mm_4572 0.0082 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 2025-09-07T11:49:42.4070924Z triton_mm_4575 0.0082 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 2025-09-07T11:49:42.4072909Z triton_mm_4576 0.0082 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 2025-09-07T11:49:42.4074588Z triton_mm_4584 0.0082 ms 100.0% 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 2025-09-07T11:49:42.4076257Z triton_mm_4578 0.0092 ms 88.9% 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 2025-09-07T11:49:42.4077909Z triton_mm_4579 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:42.4079779Z triton_mm_4580 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:42.4081472Z SingleProcess AUTOTUNE benchmarking takes 0.2673 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:42.6328644Z Autotune Choices Stats: 2025-09-07T11:49:42.6330848Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4605", "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=5, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:49:42.6416610Z AUTOTUNE mm(5x128, 128x256) 2025-09-07T11:49:42.6417200Z strides: [128, 1], [1, 128] 2025-09-07T11:49:42.6417772Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:42.6419300Z triton_mm_4605 0.0072 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=5, num_warps=4 2025-09-07T11:49:42.6421655Z triton_mm_4606 0.0072 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 2025-09-07T11:49:42.6424012Z triton_mm_4610 0.0072 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 2025-09-07T11:49:42.6426449Z triton_mm_4617 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:42.6428800Z triton_mm_4604 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:49:42.6431162Z triton_mm_4607 0.0082 ms 87.5% 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 2025-09-07T11:49:42.6433509Z triton_mm_4611 0.0082 ms 87.5% 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 2025-09-07T11:49:42.6435855Z triton_mm_4612 0.0082 ms 87.5% 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=3, num_warps=4 2025-09-07T11:49:42.6438184Z triton_mm_4613 0.0082 ms 87.5% 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 2025-09-07T11:49:42.6440537Z triton_mm_4614 0.0082 ms 87.5% 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 2025-09-07T11:49:42.6442580Z SingleProcess AUTOTUNE benchmarking takes 0.2348 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T11:49:42.9057798Z Autotune Choices Stats: 2025-09-07T11:49:42.9060049Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_4641", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:42.9146160Z AUTOTUNE mm(5x2048, 2048x256) 2025-09-07T11:49:42.9146709Z strides: [2048, 1], [1, 2048] 2025-09-07T11:49:42.9147223Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:42.9148677Z triton_mm_4641 0.0113 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 2025-09-07T11:49:42.9151217Z triton_mm_4645 0.0123 ms 91.7% 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 2025-09-07T11:49:42.9152657Z mm 0.0133 ms 84.6% 2025-09-07T11:49:42.9154230Z triton_mm_4649 0.0154 ms 73.3% 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 2025-09-07T11:49:42.9156497Z triton_mm_4640 0.0184 ms 61.1% 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 2025-09-07T11:49:42.9158729Z triton_mm_4653 0.0184 ms 61.1% 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 2025-09-07T11:49:42.9160994Z triton_mm_4639 0.0195 ms 57.9% 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 2025-09-07T11:49:42.9163230Z triton_mm_4644 0.0195 ms 57.9% 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 2025-09-07T11:49:42.9165509Z triton_mm_4638 0.0205 ms 55.0% 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 2025-09-07T11:49:42.9167810Z triton_mm_4648 0.0215 ms 52.4% 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 2025-09-07T11:49:42.9169699Z SingleProcess AUTOTUNE benchmarking takes 0.2723 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T11:49:43.1602773Z Autotune Choices Stats: 2025-09-07T11:49:43.1604529Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4694", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:43.1690983Z AUTOTUNE mm(4096x128, 128x256) 2025-09-07T11:49:43.1691466Z strides: [128, 1], [1, 128] 2025-09-07T11:49:43.1691887Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:43.1693396Z triton_mm_4694 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:43.1695194Z triton_mm_4696 0.0113 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 2025-09-07T11:49:43.1696806Z triton_mm_4697 0.0113 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 2025-09-07T11:49:43.1698431Z triton_mm_4698 0.0113 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 2025-09-07T11:49:43.1700370Z triton_mm_4699 0.0113 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 2025-09-07T11:49:43.1701950Z triton_mm_4700 0.0113 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 2025-09-07T11:49:43.1703545Z triton_mm_4701 0.0113 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=4, num_warps=8 2025-09-07T11:49:43.1705459Z triton_mm_4703 0.0113 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 2025-09-07T11:49:43.1707574Z triton_mm_4704 0.0113 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 2025-09-07T11:49:43.1709834Z triton_mm_4705 0.0113 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 2025-09-07T11:49:43.1711292Z SingleProcess AUTOTUNE benchmarking takes 0.2491 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T11:49:43.4279937Z Autotune Choices Stats: 2025-09-07T11:49:43.4371759Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_4707", "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=2, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T11:49:43.4374477Z AUTOTUNE addmm(5x256, 5x256, 256x256) 2025-09-07T11:49:43.4375038Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:49:43.4375726Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:49:43.4377352Z triton_mm_4707 0.0082 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=2, num_warps=2 2025-09-07T11:49:43.4379768Z triton_mm_4708 0.0082 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=5, num_warps=4 2025-09-07T11:49:43.4382123Z triton_mm_4709 0.0082 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 2025-09-07T11:49:43.4384509Z triton_mm_4710 0.0082 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 2025-09-07T11:49:43.4386929Z triton_mm_4713 0.0082 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 2025-09-07T11:49:43.4389332Z triton_mm_4714 0.0082 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 2025-09-07T11:49:43.4391731Z triton_mm_4716 0.0092 ms 88.9% 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 2025-09-07T11:49:43.4394100Z triton_mm_4717 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:43.4396487Z triton_mm_4718 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:43.4398853Z triton_mm_4719 0.0092 ms 88.9% 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=3, num_warps=4 2025-09-07T11:49:43.4401182Z SingleProcess AUTOTUNE benchmarking takes 0.2673 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:43.7207591Z Autotune Choices Stats: 2025-09-07T11:49:43.7209867Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_4798", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:43.7302064Z AUTOTUNE addmm(4096x128, 4096x256, 256x128) 2025-09-07T11:49:43.7302730Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:49:43.7303409Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:49:43.7305372Z triton_mm_4798 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:43.7307544Z triton_mm_4801 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:43.7310016Z triton_mm_4802 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:43.7312177Z triton_mm_4804 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:43.7313545Z bias_addmm 0.0133 ms 92.3% 2025-09-07T11:49:43.7314825Z triton_mm_4792 0.0133 ms 92.3% 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 2025-09-07T11:49:43.7317051Z triton_mm_4800 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:43.7319191Z triton_mm_4803 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:43.7321266Z triton_mm_4793 0.0143 ms 85.7% 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 2025-09-07T11:49:43.7323257Z triton_mm_4794 0.0143 ms 85.7% 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 2025-09-07T11:49:43.7325136Z SingleProcess AUTOTUNE benchmarking takes 0.2829 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T11:49:43.9382329Z Autotune Choices Stats: 2025-09-07T11:49:43.9384386Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_5054", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:49:43.9469813Z AUTOTUNE addmm(1x32, 1x256, 256x32) 2025-09-07T11:49:43.9470391Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:49:43.9471038Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:49:43.9472603Z triton_mm_5054 0.0072 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 2025-09-07T11:49:43.9474729Z triton_mm_5055 0.0072 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 2025-09-07T11:49:43.9477081Z triton_mm_5058 0.0072 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=3, num_warps=2 2025-09-07T11:49:43.9479645Z triton_mm_5061 0.0072 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=4, num_warps=2 2025-09-07T11:49:43.9481750Z triton_mm_5062 0.0072 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 2025-09-07T11:49:43.9484049Z triton_mm_5053 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T11:49:43.9486342Z triton_mm_5060 0.0082 ms 87.5% 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=4, num_warps=2 2025-09-07T11:49:43.9488633Z triton_mm_5059 0.0092 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=2 2025-09-07T11:49:43.9491181Z triton_mm_5057 0.0113 ms 63.6% 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=2, num_warps=2 2025-09-07T11:49:43.9492610Z addmm 0.0133 ms 53.8% 2025-09-07T11:49:43.9493925Z SingleProcess AUTOTUNE benchmarking takes 0.1901 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T11:49:44.1318251Z Autotune Choices Stats: 2025-09-07T11:49:44.1320425Z {"num_choices": 14, "num_triton_choices": 13, "best_kernel": "triton_mm_5199", "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=2, num_warps=2", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:44.1404160Z AUTOTUNE mm(4x32, 32x65536) 2025-09-07T11:49:44.1404689Z strides: [32, 1], [1, 32] 2025-09-07T11:49:44.1405204Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:44.1406657Z triton_mm_5199 0.0123 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=2, num_warps=2 2025-09-07T11:49:44.1408769Z triton_mm_5200 0.0123 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=5, num_warps=4 2025-09-07T11:49:44.1411066Z triton_mm_5201 0.0123 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 2025-09-07T11:49:44.1413648Z triton_mm_5203 0.0123 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=2, num_warps=4 2025-09-07T11:49:44.1415855Z triton_mm_5204 0.0123 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 2025-09-07T11:49:44.1418074Z triton_mm_5205 0.0123 ms 100.0% 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 2025-09-07T11:49:44.1420446Z triton_mm_5206 0.0123 ms 100.0% 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=8 2025-09-07T11:49:44.1422749Z triton_mm_5207 0.0123 ms 100.0% 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 2025-09-07T11:49:44.1424903Z triton_mm_5208 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T11:49:44.1427537Z triton_mm_5209 0.0123 ms 100.0% 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 2025-09-07T11:49:44.1429558Z SingleProcess AUTOTUNE benchmarking takes 0.1858 seconds and 0.0002 seconds precompiling for 14 choices 2025-09-07T11:49:44.3224307Z Autotune Choices Stats: 2025-09-07T11:49:44.3226132Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_5246", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T11:49:44.3316269Z AUTOTUNE addmm(1x4, 1x256, 256x4) 2025-09-07T11:49:44.3316804Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T11:49:44.3317647Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T11:49:44.3318858Z triton_mm_5246 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T11:49:44.3320584Z triton_mm_5247 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T11:49:44.3322546Z triton_mm_5248 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T11:49:44.3324257Z triton_mm_5251 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T11:49:44.3325943Z triton_mm_5253 0.0072 ms 100.0% 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=4, num_warps=1 2025-09-07T11:49:44.3327626Z triton_mm_5254 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T11:49:44.3329336Z triton_mm_5255 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T11:49:44.3331025Z triton_mm_5252 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T11:49:44.3332102Z bias_addmm 0.0102 ms 70.0% 2025-09-07T11:49:44.3333457Z triton_mm_5250 0.0102 ms 70.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T11:49:44.3334964Z SingleProcess AUTOTUNE benchmarking takes 0.1906 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T11:50:02.9746924Z pass 2025-09-07T11:50:08.1800833Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:50:08.1802362Z import pynvml # type: ignore[import] 2025-09-07T11:50:10.9568648Z 2025-09-07T11:50:46.5641987Z loading model: 0it [00:00, ?it/s]Loading best configs from file /opt/conda/envs/py_3.10/lib/python3.10/site-packages/segment_anything_fast/configs/flash_4_configs_a100.p 2025-09-07T11:50:48.0006621Z 2025-09-07T11:50:48.0007083Z loading model: 0it [00:37, ?it/s] 2025-09-07T11:50:48.0057841Z cuda eval sam_fast 2025-09-07T11:52:15.6947898Z E0907 11:52:15.694000 217473 site-packages/torch/_dynamo/utils.py:3131] Accuracy failed: allclose not within tol=0 2025-09-07T11:52:15.6950789Z E0907 11:52:15.694000 217473 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name low_res_logits 2025-09-07T11:52:15.7213871Z pass 2025-09-07T11:52:19.0430155Z accuracy pass_rate=92.86% 2025-09-07T11:52:19.0436405Z calls_captured gmean=0.00x mean=846.571x 2025-09-07T11:52:19.0440636Z unique_graphs gmean=0.00x mean=1.071x 2025-09-07T11:52:19.0444853Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:52:19.0449209Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:52:19.0453363Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:52:19.0457639Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:52:19.0461748Z cudagraph_skips gmean=0.00x mean=0.071x 2025-09-07T11:52:19.0462995Z compilation_latency mean=27.817 seconds 2025-09-07T11:52:19.9471084Z + [[ 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* ]] 2025-09-07T11:52:19.9472870Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T11:52:19.9473206Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T11:52:19.9474926Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:52:20.5278799Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:52:20.5280282Z import pynvml # type: ignore[import] 2025-09-07T11:52:24.4289526Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:52:24.4292246Z import pynvml # type: ignore[import] 2025-09-07T11:52:27.3158208Z 2025-09-07T11:52:28.1723102Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:52:28.1723521Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:52:28.1750403Z cuda eval phlippe_resnet 2025-09-07T11:52:33.4983336Z pass 2025-09-07T11:52:35.2245221Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:52:35.2246662Z import pynvml # type: ignore[import] 2025-09-07T11:52:38.0893025Z 2025-09-07T11:52:38.5356303Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:52:38.5356694Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:52:38.5357038Z cuda eval pyhpc_equation_of_state 2025-09-07T11:52:43.8635651Z pass 2025-09-07T11:52:45.7202234Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:52:45.7203668Z import pynvml # type: ignore[import] 2025-09-07T11:52:48.4027190Z 2025-09-07T11:52:48.7933808Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:52:48.7934194Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:52:48.7937629Z cuda eval pyhpc_isoneutral_mixing 2025-09-07T11:52:56.1125356Z pass 2025-09-07T11:52:57.8953985Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:52:57.8955766Z import pynvml # type: ignore[import] 2025-09-07T11:53:00.6173434Z 2025-09-07T11:53:01.4733722Z loading model: 0it [00:00, ?it/s]WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:53:01.6285983Z 2025-09-07T11:53:01.6286333Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:53:01.6287016Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:53:01.6287651Z cuda eval pyhpc_turbulent_kinetic_energy 2025-09-07T11:53:01.6497284Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:53:09.9756955Z pass 2025-09-07T11:53:11.9626641Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:53:11.9628436Z import pynvml # type: ignore[import] 2025-09-07T11:53:14.9651689Z 2025-09-07T11:53:15.8103621Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:53:15.8104026Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:53:15.8117158Z cuda eval pytorch_CycleGAN_and_pix2pix 2025-09-07T11:53:21.2322652Z pass 2025-09-07T11:53:22.9948297Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:53:22.9949700Z import pynvml # type: ignore[import] 2025-09-07T11:53:25.7259071Z 2025-09-07T11:53:26.9508444Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:53:26.9508881Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:53:26.9532719Z cuda eval pytorch_stargan 2025-09-07T11:53:33.8146478Z pass 2025-09-07T11:53:35.6070678Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:53:35.6072112Z import pynvml # type: ignore[import] 2025-09-07T11:53:38.4563920Z 2025-09-07T11:53:39.4434097Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:53:39.4434711Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:53:39.4458270Z cuda eval pytorch_unet 2025-09-07T11:53:45.8208813Z pass 2025-09-07T11:53:47.9250954Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:53:47.9253964Z import pynvml # type: ignore[import] 2025-09-07T11:53:50.7706730Z 2025-09-07T11:53:52.9349266Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:53:52.9349635Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:53:52.9530503Z cuda eval resnet152 2025-09-07T11:54:03.6312529Z pass 2025-09-07T11:54:05.5267993Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:54:05.5270511Z import pynvml # type: ignore[import] 2025-09-07T11:54:08.3452532Z 2025-09-07T11:54:09.5147731Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:54:09.5148369Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:54:09.5175213Z cuda eval resnet18 2025-09-07T11:54:14.0417754Z pass 2025-09-07T11:54:15.8855433Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:54:15.8858131Z import pynvml # type: ignore[import] 2025-09-07T11:54:18.7889835Z 2025-09-07T11:54:20.2269668Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:54:20.2270060Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:54:20.2333180Z cuda eval resnet50 2025-09-07T11:54:26.6095083Z pass 2025-09-07T11:54:28.4150689Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:54:28.4154845Z import pynvml # type: ignore[import] 2025-09-07T11:54:31.1280034Z 2025-09-07T11:54:31.2865363Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:54:31.2865738Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:54:31.2866077Z cuda eval resnet50_quantized_qat 2025-09-07T11:54:31.2872267Z Traceback (most recent call last): 2025-09-07T11:54:31.2873784Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:54:31.2874797Z ) = runner.load_model( 2025-09-07T11:54:31.2875792Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T11:54:31.2876843Z benchmark = benchmark_cls( 2025-09-07T11:54:31.2877666Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T11:54:31.2878551Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T11:54:31.2879690Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T11:54:31.2881022Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T11:54:31.2881953Z NotImplementedError: The eval test only supports CPU. 2025-09-07T11:54:31.2882509Z 2025-09-07T11:54:31.2882690Z model_fail_to_load 2025-09-07T11:54:32.8680154Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:54:32.8682326Z import pynvml # type: ignore[import] 2025-09-07T11:54:35.6266615Z 2025-09-07T11:54:37.1395905Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:54:37.1396294Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:54:37.1460440Z cuda eval resnext50_32x4d 2025-09-07T11:54:43.0524044Z pass 2025-09-07T11:54:44.9740322Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:54:44.9741783Z import pynvml # type: ignore[import] 2025-09-07T11:54:48.1457542Z 2025-09-07T11:54:56.1228525Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:54:56.1228897Z loading model: 0it [00:07, ?it/s] 2025-09-07T11:54:56.1351890Z cuda eval sam 2025-09-07T11:55:12.9476069Z pass 2025-09-07T11:55:15.1223060Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:55:15.1225791Z import pynvml # type: ignore[import] 2025-09-07T11:55:17.7664653Z 2025-09-07T11:55:35.5496354Z loading model: 0it [00:00, ?it/s]Loading best configs from file /opt/conda/envs/py_3.10/lib/python3.10/site-packages/segment_anything_fast/configs/flash_4_configs_a100.p 2025-09-07T11:55:36.0108842Z 2025-09-07T11:55:36.0109421Z loading model: 0it [00:18, ?it/s] 2025-09-07T11:55:36.0159878Z cuda eval sam_fast 2025-09-07T11:56:14.4475628Z pass 2025-09-07T11:56:18.1375403Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:56:18.1376842Z import pynvml # type: ignore[import] 2025-09-07T11:56:20.9520212Z 2025-09-07T11:56:22.0241710Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:56:22.0242306Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:56:22.0311218Z cuda eval shufflenet_v2_x1_0 2025-09-07T11:56:27.9444251Z pass 2025-09-07T11:56:29.1833938Z accuracy pass_rate=93.33% 2025-09-07T11:56:29.1840104Z calls_captured gmean=0.00x mean=548.267x 2025-09-07T11:56:29.1844549Z unique_graphs gmean=0.00x mean=0.933x 2025-09-07T11:56:29.1848821Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:56:29.1853008Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:56:29.1857516Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:56:29.1866437Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:56:29.1867056Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:56:29.1867410Z compilation_latency mean=5.460 seconds 2025-09-07T11:56:30.2314159Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:56:30.8259300Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:56:30.8260754Z import pynvml # type: ignore[import] 2025-09-07T11:56:34.7867768Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:56:34.7869616Z import pynvml # type: ignore[import] 2025-09-07T11:56:37.6473250Z 2025-09-07T11:56:38.5019569Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:56:38.5019979Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:56:38.5047789Z cuda eval phlippe_resnet 2025-09-07T11:56:58.6532050Z pass 2025-09-07T11:57:01.4882762Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:57:01.4884225Z import pynvml # type: ignore[import] 2025-09-07T11:57:04.1856761Z 2025-09-07T11:57:04.6230282Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:57:04.6230699Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:57:04.6231031Z cuda eval pyhpc_equation_of_state 2025-09-07T11:57:21.7772385Z pass 2025-09-07T11:57:24.9413181Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:57:24.9415694Z import pynvml # type: ignore[import] 2025-09-07T11:57:27.6034863Z 2025-09-07T11:57:28.0037562Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:57:28.0037952Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:57:28.0042741Z cuda eval pyhpc_isoneutral_mixing 2025-09-07T11:57:49.8541985Z pass 2025-09-07T11:57:52.8831321Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:57:52.8834013Z import pynvml # type: ignore[import] 2025-09-07T11:57:56.0619971Z 2025-09-07T11:57:56.9914402Z loading model: 0it [00:00, ?it/s]WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:57:57.1470372Z 2025-09-07T11:57:57.1470821Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:57:57.1471463Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:57:57.1472438Z cuda eval pyhpc_turbulent_kinetic_energy 2025-09-07T11:57:57.1682762Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T11:58:28.1625753Z pass 2025-09-07T11:58:31.5141548Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:58:31.5142996Z import pynvml # type: ignore[import] 2025-09-07T11:58:34.2697819Z 2025-09-07T11:58:35.1091525Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:58:35.1091912Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:58:35.1144177Z cuda eval pytorch_CycleGAN_and_pix2pix 2025-09-07T11:58:52.9703427Z pass 2025-09-07T11:58:56.0751674Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:58:56.0754134Z import pynvml # type: ignore[import] 2025-09-07T11:58:58.7525941Z 2025-09-07T11:58:59.9424369Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:58:59.9425080Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:58:59.9448263Z cuda eval pytorch_stargan 2025-09-07T11:59:18.6995806Z pass 2025-09-07T11:59:21.7466502Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:59:21.7469145Z import pynvml # type: ignore[import] 2025-09-07T11:59:24.4349676Z 2025-09-07T11:59:25.4557727Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:59:25.4558356Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:59:25.4582830Z cuda eval pytorch_unet 2025-09-07T11:59:46.6549916Z pass 2025-09-07T11:59:49.8828160Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:59:49.8829610Z import pynvml # type: ignore[import] 2025-09-07T11:59:52.6464550Z 2025-09-07T11:59:54.6945112Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:59:54.6945739Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:59:54.7118673Z cuda eval resnet152 2025-09-07T12:00:33.2012683Z pass 2025-09-07T12:00:36.8369570Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:00:36.8372721Z import pynvml # type: ignore[import] 2025-09-07T12:00:39.5148225Z 2025-09-07T12:00:40.8568243Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:00:40.8568625Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:00:40.8596426Z cuda eval resnet18 2025-09-07T12:00:59.0125129Z pass 2025-09-07T12:01:02.1525968Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:01:02.1527415Z import pynvml # type: ignore[import] 2025-09-07T12:01:04.9243491Z 2025-09-07T12:01:06.4606209Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:01:06.4606586Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:01:06.4670643Z cuda eval resnet50 2025-09-07T12:01:28.6608446Z pass 2025-09-07T12:01:31.7649808Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:01:31.7653529Z import pynvml # type: ignore[import] 2025-09-07T12:01:34.4406358Z 2025-09-07T12:01:34.6080162Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:01:34.6080792Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:01:34.6081340Z cuda eval resnet50_quantized_qat 2025-09-07T12:01:34.6087572Z Traceback (most recent call last): 2025-09-07T12:01:34.6088543Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T12:01:34.6089469Z ) = runner.load_model( 2025-09-07T12:01:34.6090414Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T12:01:34.6091505Z benchmark = benchmark_cls( 2025-09-07T12:01:34.6092290Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T12:01:34.6093488Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T12:01:34.6094536Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T12:01:34.6095792Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T12:01:34.6096694Z NotImplementedError: The eval test only supports CPU. 2025-09-07T12:01:34.6097216Z 2025-09-07T12:01:34.6097384Z model_fail_to_load 2025-09-07T12:01:36.4418133Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:01:36.4419652Z import pynvml # type: ignore[import] 2025-09-07T12:01:39.9516812Z 2025-09-07T12:01:41.8954626Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:01:41.8955236Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:01:41.9052618Z cuda eval resnext50_32x4d 2025-09-07T12:02:04.1433065Z pass 2025-09-07T12:02:07.4597452Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:02:07.4598884Z import pynvml # type: ignore[import] 2025-09-07T12:02:10.2724479Z 2025-09-07T12:02:18.4137808Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:02:18.4138215Z loading model: 0it [00:08, ?it/s] 2025-09-07T12:02:18.4267456Z cuda eval sam 2025-09-07T12:03:48.2126021Z pass 2025-09-07T12:03:52.9313824Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:03:52.9316822Z import pynvml # type: ignore[import] 2025-09-07T12:03:55.7088388Z 2025-09-07T12:03:56.7323804Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:03:56.7324204Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:03:56.7393289Z cuda eval shufflenet_v2_x1_0 2025-09-07T12:04:26.2636835Z pass 2025-09-07T12:04:28.8074426Z accuracy pass_rate=92.86% 2025-09-07T12:04:28.8081365Z calls_captured gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8086269Z unique_graphs gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8090265Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8095038Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8099281Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8108166Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8108525Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T12:04:28.8109069Z compilation_latency mean=0.000 seconds 2025-09-07T12:04:29.6911676Z + [[ 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* ]] 2025-09-07T12:04:29.6913204Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T12:04:29.6914676Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T12:04:30.2593620Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:04:30.2596153Z import pynvml # type: ignore[import] 2025-09-07T12:04:34.0754905Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:04:34.0756343Z import pynvml # type: ignore[import] 2025-09-07T12:04:36.8261106Z 2025-09-07T12:04:37.6991389Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:04:37.6992009Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:04:37.7018286Z cuda eval phlippe_resnet 2025-09-07T12:04:49.4110348Z pass 2025-09-07T12:04:52.5740304Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:04:52.5742800Z import pynvml # type: ignore[import] 2025-09-07T12:04:56.3777507Z 2025-09-07T12:04:56.8861200Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:04:56.8861825Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:04:56.8862452Z cuda eval pyhpc_equation_of_state 2025-09-07T12:05:04.1605246Z pass 2025-09-07T12:05:07.0607270Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:05:07.0609943Z import pynvml # type: ignore[import] 2025-09-07T12:05:09.7382772Z 2025-09-07T12:05:10.1357003Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:05:10.1357398Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:05:10.1360912Z cuda eval pyhpc_isoneutral_mixing 2025-09-07T12:05:22.7069958Z skipping cudagraphs due to mutated inputs (7 instances). Found from : 2025-09-07T12:05:22.7070716Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T12:05:22.7071295Z return mod(*inputs) 2025-09-07T12:05:22.7071857Z File "/torchbench/torchbenchmark/models/pyhpc_isoneutral_mixing/__init__.py", line 100, in forward 2025-09-07T12:05:22.7072505Z return isoneutral_pytorch.isoneutral_diffusion_pre( 2025-09-07T12:05:22.7073269Z File "/torchbench/torchbenchmark/models/pyhpc_isoneutral_mixing/isoneutral_pytorch.py", line 164, in isoneutral_diffusion_pre 2025-09-07T12:05:22.7074064Z Ai_ez[1:-2, 2:-2, ki:, ip, kr] = taper * sxe * maskU[1:-2, 2:-2, ki:] 2025-09-07T12:05:22.7074364Z 2025-09-07T12:05:22.7363272Z pass 2025-09-07T12:05:26.2176132Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:05:26.2184721Z import pynvml # type: ignore[import] 2025-09-07T12:05:29.0632636Z 2025-09-07T12:05:29.9910613Z loading model: 0it [00:00, ?it/s]WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T12:05:30.1432081Z 2025-09-07T12:05:30.1432297Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:05:30.1432911Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T12:05:30.1433543Z cuda eval pyhpc_turbulent_kinetic_energy 2025-09-07T12:05:30.1640080Z WARNING:common:Model pyhpc_turbulent_kinetic_energy does not support bfloat16, running with amp instead 2025-09-07T12:05:54.5777887Z pass 2025-09-07T12:05:58.3274881Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:05:58.3277566Z import pynvml # type: ignore[import] 2025-09-07T12:06:00.9719954Z 2025-09-07T12:06:01.8061927Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:06:01.8062330Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:06:01.8075152Z cuda eval pytorch_CycleGAN_and_pix2pix 2025-09-07T12:06:13.9848695Z pass 2025-09-07T12:06:17.5604456Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:06:17.5605900Z import pynvml # type: ignore[import] 2025-09-07T12:06:20.6279663Z 2025-09-07T12:06:21.9607828Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:06:21.9608209Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:06:21.9629804Z cuda eval pytorch_stargan 2025-09-07T12:06:33.8444079Z pass 2025-09-07T12:06:37.0659843Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:06:37.0661284Z import pynvml # type: ignore[import] 2025-09-07T12:06:40.2476667Z 2025-09-07T12:06:41.2030689Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:06:41.2031064Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:06:41.2052573Z cuda eval pytorch_unet 2025-09-07T12:06:59.0289770Z pass 2025-09-07T12:07:02.3318056Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:07:02.3319889Z import pynvml # type: ignore[import] 2025-09-07T12:07:05.5916244Z 2025-09-07T12:07:08.7138608Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:07:08.7139196Z loading model: 0it [00:03, ?it/s] 2025-09-07T12:07:08.7419969Z cuda eval resnet152 2025-09-07T12:07:37.7524821Z Autotune Choices Stats: 2025-09-07T12:07:37.7526970Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_62", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T12:07:37.7618134Z AUTOTUNE mm(12544x64, 64x256) 2025-09-07T12:07:37.7618486Z strides: [64, 1], [1, 64] 2025-09-07T12:07:37.7619044Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:37.7619832Z triton_mm_62 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:07:37.7621029Z triton_mm_58 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:07:37.7622415Z triton_mm_59 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:37.7623594Z triton_mm_61 0.0133 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 2025-09-07T12:07:37.7624773Z triton_mm_65 0.0133 ms 92.3% 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 2025-09-07T12:07:37.7626029Z triton_mm_66 0.0133 ms 92.3% 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 2025-09-07T12:07:37.7627222Z triton_mm_67 0.0133 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 2025-09-07T12:07:37.7628399Z triton_mm_68 0.0133 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=5, num_warps=8 2025-09-07T12:07:37.7629581Z triton_mm_57 0.0143 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=8 2025-09-07T12:07:37.7630744Z triton_mm_63 0.0143 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:37.7631766Z SingleProcess AUTOTUNE benchmarking takes 0.2775 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T12:07:39.9656951Z Autotune Choices Stats: 2025-09-07T12:07:39.9658206Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_166", "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": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T12:07:39.9746478Z AUTOTUNE mm(12544x256, 256x128) 2025-09-07T12:07:39.9747003Z strides: [256, 1], [1, 256] 2025-09-07T12:07:39.9747500Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:39.9748895Z triton_mm_166 0.0164 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 2025-09-07T12:07:39.9751118Z triton_mm_168 0.0164 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:39.9753688Z triton_mm_169 0.0164 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 2025-09-07T12:07:39.9755866Z triton_mm_172 0.0164 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 2025-09-07T12:07:39.9758080Z triton_mm_173 0.0164 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 2025-09-07T12:07:39.9760259Z triton_mm_167 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:07:39.9762682Z triton_mm_170 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:07:39.9764852Z triton_mm_174 0.0174 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 2025-09-07T12:07:39.9767344Z triton_mm_163 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:07:39.9769476Z triton_mm_164 0.0184 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 2025-09-07T12:07:39.9771333Z SingleProcess AUTOTUNE benchmarking takes 0.2700 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:40.5772757Z Autotune Choices Stats: 2025-09-07T12:07:40.5774111Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_241", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T12:07:40.5859624Z AUTOTUNE mm(3136x128, 128x512) 2025-09-07T12:07:40.5859968Z strides: [128, 1], [1, 128] 2025-09-07T12:07:40.5860266Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:40.5861056Z triton_mm_241 0.0113 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 2025-09-07T12:07:40.5862263Z triton_mm_244 0.0113 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 2025-09-07T12:07:40.5863464Z triton_mm_247 0.0113 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 2025-09-07T12:07:40.5864223Z mm 0.0123 ms 91.7% 2025-09-07T12:07:40.5864902Z triton_mm_238 0.0123 ms 91.7% 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 2025-09-07T12:07:40.5866160Z triton_mm_240 0.0123 ms 91.7% 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 2025-09-07T12:07:40.5867343Z triton_mm_242 0.0123 ms 91.7% 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 2025-09-07T12:07:40.5868524Z triton_mm_243 0.0123 ms 91.7% 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 2025-09-07T12:07:40.5869708Z triton_mm_245 0.0123 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=4, num_warps=8 2025-09-07T12:07:40.5871159Z triton_mm_248 0.0123 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=3, num_warps=4 2025-09-07T12:07:40.5872189Z SingleProcess AUTOTUNE benchmarking takes 0.2562 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:42.1135398Z Autotune Choices Stats: 2025-09-07T12:07:42.1136615Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_7", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T12:07:42.1230923Z AUTOTUNE mm(12544x64, 64x64) 2025-09-07T12:07:42.1231519Z strides: [64, 1], [1, 64] 2025-09-07T12:07:42.1231817Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:42.1232584Z triton_mm_7 0.0102 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 2025-09-07T12:07:42.1233995Z triton_mm_10 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:07:42.1235181Z triton_mm_12 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:07:42.1236361Z triton_mm_13 0.0102 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 2025-09-07T12:07:42.1237536Z triton_mm_14 0.0102 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 2025-09-07T12:07:42.1238724Z triton_mm_15 0.0102 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 2025-09-07T12:07:42.1239899Z triton_mm_16 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:07:42.1241068Z triton_mm_17 0.0102 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 2025-09-07T12:07:42.1242227Z triton_mm_18 0.0102 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 2025-09-07T12:07:42.1243407Z triton_mm_19 0.0102 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 2025-09-07T12:07:42.1244440Z SingleProcess AUTOTUNE benchmarking takes 0.2514 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:42.7279009Z Autotune Choices Stats: 2025-09-07T12:07:42.7280258Z {"num_choices": 19, "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T12:07:42.7368353Z AUTOTUNE mm(12544x256, 256x64) 2025-09-07T12:07:42.7368700Z strides: [256, 1], [1, 256] 2025-09-07T12:07:42.7369003Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:42.7369772Z triton_mm_80 0.0154 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 2025-09-07T12:07:42.7370977Z triton_mm_85 0.0154 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:42.7372476Z triton_mm_86 0.0154 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 2025-09-07T12:07:42.7373890Z triton_mm_76 0.0164 ms 93.7% 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 2025-09-07T12:07:42.7375057Z triton_mm_78 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:42.7376225Z triton_mm_79 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:07:42.7377533Z triton_mm_82 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:42.7378903Z triton_mm_83 0.0164 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:07:42.7380081Z triton_mm_70 0.0174 ms 88.2% 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 2025-09-07T12:07:42.7381251Z triton_mm_71 0.0174 ms 88.2% 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 2025-09-07T12:07:42.7382275Z SingleProcess AUTOTUNE benchmarking takes 0.2657 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:43.0671879Z Autotune Choices Stats: 2025-09-07T12:07:43.0673418Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_mm_519", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T12:07:43.0765917Z AUTOTUNE mm(3136x512, 512x256) 2025-09-07T12:07:43.0766221Z strides: [512, 1], [1, 512] 2025-09-07T12:07:43.0766517Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:43.0766819Z mm 0.0143 ms 100.0% 2025-09-07T12:07:43.0767530Z triton_mm_519 0.0143 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 2025-09-07T12:07:43.0768736Z triton_mm_521 0.0143 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=4, num_warps=8 2025-09-07T12:07:43.0769942Z triton_mm_515 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:07:43.0771132Z triton_mm_518 0.0154 ms 93.3% 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 2025-09-07T12:07:43.0772317Z triton_mm_520 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:43.0773771Z triton_mm_524 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:43.0774979Z triton_mm_525 0.0164 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 2025-09-07T12:07:43.0776420Z triton_mm_516 0.0174 ms 82.4% 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 2025-09-07T12:07:43.0777616Z triton_mm_517 0.0174 ms 82.4% 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 2025-09-07T12:07:43.0778647Z SingleProcess AUTOTUNE benchmarking takes 0.2739 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:43.6829560Z Autotune Choices Stats: 2025-09-07T12:07:43.6830802Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_590", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T12:07:43.6920240Z AUTOTUNE mm(784x256, 256x1024) 2025-09-07T12:07:43.6920599Z strides: [256, 1], [1, 256] 2025-09-07T12:07:43.6920898Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:43.6921995Z triton_mm_590 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 2025-09-07T12:07:43.6923193Z triton_mm_593 0.0113 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 2025-09-07T12:07:43.6924408Z triton_mm_594 0.0113 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 2025-09-07T12:07:43.6925163Z mm 0.0123 ms 91.7% 2025-09-07T12:07:43.6925858Z triton_mm_592 0.0123 ms 91.7% 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 2025-09-07T12:07:43.6927053Z triton_mm_595 0.0123 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 2025-09-07T12:07:43.6928260Z triton_mm_596 0.0133 ms 84.6% 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 2025-09-07T12:07:43.6929452Z triton_mm_598 0.0133 ms 84.6% 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 2025-09-07T12:07:43.6930645Z triton_mm_599 0.0133 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 2025-09-07T12:07:43.6931844Z triton_mm_600 0.0133 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=5, num_warps=8 2025-09-07T12:07:43.6933136Z SingleProcess AUTOTUNE benchmarking takes 0.2621 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T12:07:46.0788940Z Autotune Choices Stats: 2025-09-07T12:07:46.0790183Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_214", "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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T12:07:46.0882372Z AUTOTUNE mm(3136x512, 512x128) 2025-09-07T12:07:46.0882714Z strides: [512, 1], [1, 512] 2025-09-07T12:07:46.0883003Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:46.0883791Z triton_mm_214 0.0133 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 2025-09-07T12:07:46.0885023Z triton_mm_215 0.0133 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 2025-09-07T12:07:46.0891696Z triton_mm_218 0.0133 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 2025-09-07T12:07:46.0892454Z mm 0.0143 ms 92.9% 2025-09-07T12:07:46.0893453Z triton_mm_217 0.0143 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 2025-09-07T12:07:46.0894639Z triton_mm_220 0.0143 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=4, num_warps=8 2025-09-07T12:07:46.0895997Z triton_mm_208 0.0154 ms 86.7% 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 2025-09-07T12:07:46.0897185Z triton_mm_209 0.0154 ms 86.7% 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 2025-09-07T12:07:46.0898559Z triton_mm_210 0.0154 ms 86.7% 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 2025-09-07T12:07:46.0899751Z triton_mm_211 0.0154 ms 86.7% 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 2025-09-07T12:07:46.0900790Z SingleProcess AUTOTUNE benchmarking takes 0.2708 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:46.8749078Z Autotune Choices Stats: 2025-09-07T12:07:46.8750344Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_2071", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T12:07:46.8839687Z AUTOTUNE mm(784x1024, 1024x512) 2025-09-07T12:07:46.8840000Z strides: [1024, 1], [1, 1024] 2025-09-07T12:07:46.8840312Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:46.8841083Z triton_mm_2071 0.0143 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 2025-09-07T12:07:46.8841841Z mm 0.0154 ms 93.3% 2025-09-07T12:07:46.8842533Z triton_mm_2070 0.0164 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=8 2025-09-07T12:07:46.8843721Z triton_mm_2067 0.0184 ms 77.8% 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 2025-09-07T12:07:46.8844926Z triton_mm_2074 0.0184 ms 77.8% 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 2025-09-07T12:07:46.8846119Z triton_mm_2064 0.0205 ms 70.0% 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 2025-09-07T12:07:46.8847290Z triton_mm_2065 0.0205 ms 70.0% 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 2025-09-07T12:07:46.8848470Z triton_mm_2066 0.0205 ms 70.0% 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 2025-09-07T12:07:46.8849660Z triton_mm_2073 0.0205 ms 70.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:07:46.8851106Z triton_mm_2076 0.0205 ms 70.0% 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 2025-09-07T12:07:46.8852144Z SingleProcess AUTOTUNE benchmarking takes 0.2788 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:47.4839724Z Autotune Choices Stats: 2025-09-07T12:07:47.4841239Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "best_triton_kernel": "triton_mm_2149", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T12:07:47.4933184Z AUTOTUNE mm(196x512, 512x2048) 2025-09-07T12:07:47.4933531Z strides: [512, 1], [1, 512] 2025-09-07T12:07:47.4933836Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:47.4934170Z mm 0.0133 ms 100.0% 2025-09-07T12:07:47.4934884Z triton_mm_2149 0.0133 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 2025-09-07T12:07:47.4936455Z triton_mm_2145 0.0143 ms 92.9% 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 2025-09-07T12:07:47.4937653Z triton_mm_2148 0.0143 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 2025-09-07T12:07:47.4938846Z triton_mm_2151 0.0143 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=4, num_warps=8 2025-09-07T12:07:47.4940052Z triton_mm_2139 0.0164 ms 81.2% 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 2025-09-07T12:07:47.4941251Z triton_mm_2146 0.0164 ms 81.2% 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 2025-09-07T12:07:47.4942448Z triton_mm_2147 0.0164 ms 81.2% 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 2025-09-07T12:07:47.4943633Z triton_mm_2150 0.0164 ms 81.2% 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 2025-09-07T12:07:47.4944833Z triton_mm_2154 0.0164 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:07:47.4945962Z SingleProcess AUTOTUNE benchmarking takes 0.2648 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:48.5403118Z Autotune Choices Stats: 2025-09-07T12:07:48.5404376Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_562", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T12:07:48.5496713Z AUTOTUNE mm(784x1024, 1024x256) 2025-09-07T12:07:48.5497032Z strides: [1024, 1], [1, 1024] 2025-09-07T12:07:48.5497342Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:48.5498099Z triton_mm_562 0.0123 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 2025-09-07T12:07:48.5498855Z mm 0.0133 ms 92.3% 2025-09-07T12:07:48.5499545Z triton_mm_566 0.0133 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 2025-09-07T12:07:48.5501001Z triton_mm_560 0.0154 ms 80.0% 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 2025-09-07T12:07:48.5502182Z triton_mm_561 0.0154 ms 80.0% 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 2025-09-07T12:07:48.5503351Z triton_mm_565 0.0154 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:07:48.5504512Z triton_mm_559 0.0164 ms 75.0% 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 2025-09-07T12:07:48.5505894Z triton_mm_569 0.0174 ms 70.6% 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 2025-09-07T12:07:48.5507077Z triton_mm_568 0.0205 ms 60.0% 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 2025-09-07T12:07:48.5508428Z triton_mm_571 0.0205 ms 60.0% 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 2025-09-07T12:07:48.5509458Z SingleProcess AUTOTUNE benchmarking takes 0.2761 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:50.1299472Z Autotune Choices Stats: 2025-09-07T12:07:50.1300714Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_2117", "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T12:07:50.1393410Z AUTOTUNE mm(196x2048, 2048x512) 2025-09-07T12:07:50.1393711Z strides: [2048, 1], [1, 2048] 2025-09-07T12:07:50.1394023Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:07:50.1394819Z triton_mm_2117 0.0154 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 2025-09-07T12:07:50.1395575Z mm 0.0174 ms 88.2% 2025-09-07T12:07:50.1396270Z triton_mm_2121 0.0174 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 2025-09-07T12:07:50.1397448Z triton_mm_2115 0.0215 ms 71.4% 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 2025-09-07T12:07:50.1398630Z triton_mm_2116 0.0215 ms 71.4% 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 2025-09-07T12:07:50.1399812Z triton_mm_2114 0.0225 ms 68.2% 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 2025-09-07T12:07:50.1401004Z triton_mm_2120 0.0236 ms 65.2% 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 2025-09-07T12:07:50.1402186Z triton_mm_2124 0.0276 ms 55.6% 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 2025-09-07T12:07:50.1403375Z triton_mm_2123 0.0317 ms 48.4% 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 2025-09-07T12:07:50.1404569Z triton_mm_2126 0.0328 ms 46.9% 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 2025-09-07T12:07:50.1405844Z SingleProcess AUTOTUNE benchmarking takes 0.3032 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:07:58.7321030Z pass 2025-09-07T12:08:02.7187852Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:08:02.7189284Z import pynvml # type: ignore[import] 2025-09-07T12:08:05.4310343Z 2025-09-07T12:08:06.8762009Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:08:06.8762547Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:08:06.8791785Z cuda eval resnet18 2025-09-07T12:08:17.5040538Z pass 2025-09-07T12:08:21.1138647Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:08:21.1140097Z import pynvml # type: ignore[import] 2025-09-07T12:08:24.0648142Z 2025-09-07T12:08:25.5671218Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:08:25.5671585Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:08:25.5734759Z cuda eval resnet50 2025-09-07T12:08:45.5587537Z pass 2025-09-07T12:08:50.4399619Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:08:50.4402184Z import pynvml # type: ignore[import] 2025-09-07T12:08:54.8597276Z 2025-09-07T12:08:55.1255315Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:08:55.1255972Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:08:55.1256558Z cuda eval resnet50_quantized_qat 2025-09-07T12:08:55.1265257Z Traceback (most recent call last): 2025-09-07T12:08:55.1266304Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T12:08:55.1267283Z ) = runner.load_model( 2025-09-07T12:08:55.1268215Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 332, in load_model 2025-09-07T12:08:55.1269269Z benchmark = benchmark_cls( 2025-09-07T12:08:55.1270011Z File "/torchbench/torchbenchmark/util/model.py", line 43, in __call__ 2025-09-07T12:08:55.1270853Z obj = type.__call__(cls, *args, **kwargs) 2025-09-07T12:08:55.1271952Z File "/torchbench/torchbenchmark/models/resnet50_quantized_qat/__init__.py", line 22, in __init__ 2025-09-07T12:08:55.1273165Z raise NotImplementedError("The eval test only supports CPU.") 2025-09-07T12:08:55.1274073Z NotImplementedError: The eval test only supports CPU. 2025-09-07T12:08:55.1274597Z 2025-09-07T12:08:55.1274758Z model_fail_to_load 2025-09-07T12:08:57.0042197Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:08:57.0044885Z import pynvml # type: ignore[import] 2025-09-07T12:08:59.7975402Z 2025-09-07T12:09:01.4041793Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:09:01.4042191Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:09:01.4104788Z cuda eval resnext50_32x4d 2025-09-07T12:09:16.9844598Z Autotune Choices Stats: 2025-09-07T12:09:16.9846590Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_89", "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": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T12:09:17.0017806Z AUTOTUNE mm(12544x128, 128x256) 2025-09-07T12:09:17.0018367Z strides: [128, 1], [1, 128] 2025-09-07T12:09:17.0018839Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:17.0020170Z triton_mm_89 0.0154 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 2025-09-07T12:09:17.0022209Z triton_mm_94 0.0154 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=2, num_warps=8 2025-09-07T12:09:17.0024257Z triton_mm_95 0.0154 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 2025-09-07T12:09:17.0026767Z triton_mm_91 0.0164 ms 93.7% 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 2025-09-07T12:09:17.0029294Z triton_mm_90 0.0174 ms 88.2% 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 2025-09-07T12:09:17.0031316Z triton_mm_86 0.0184 ms 83.3% 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 2025-09-07T12:09:17.0033328Z triton_mm_87 0.0184 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 2025-09-07T12:09:17.0035314Z triton_mm_88 0.0184 ms 83.3% 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 2025-09-07T12:09:17.0037353Z triton_mm_97 0.0195 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 2025-09-07T12:09:17.0039386Z triton_mm_84 0.0215 ms 71.4% 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 2025-09-07T12:09:17.0041108Z SingleProcess AUTOTUNE benchmarking takes 0.4134 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T12:09:17.5725008Z Autotune Choices Stats: 2025-09-07T12:09:17.5727292Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_149", "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": 0.01945599913597107, "best_triton_pos": 0} 2025-09-07T12:09:17.5903688Z AUTOTUNE mm(12544x256, 256x256) 2025-09-07T12:09:17.5904252Z strides: [256, 1], [1, 256] 2025-09-07T12:09:17.5904752Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:17.5906233Z triton_mm_149 0.0195 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 2025-09-07T12:09:17.5908417Z triton_mm_146 0.0205 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:17.5910763Z triton_mm_143 0.0215 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:17.5913007Z triton_mm_144 0.0225 ms 86.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:09:17.5915206Z triton_mm_147 0.0225 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 2025-09-07T12:09:17.5917925Z triton_mm_145 0.0236 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 2025-09-07T12:09:17.5920203Z triton_mm_150 0.0236 ms 82.6% 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 2025-09-07T12:09:17.5922455Z triton_mm_141 0.0246 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 2025-09-07T12:09:17.5924657Z triton_mm_140 0.0256 ms 76.0% 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 2025-09-07T12:09:17.5927142Z triton_mm_151 0.0256 ms 76.0% 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 2025-09-07T12:09:17.5929078Z SingleProcess AUTOTUNE benchmarking takes 0.4208 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T12:09:18.7134967Z Autotune Choices Stats: 2025-09-07T12:09:18.7137349Z {"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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T12:09:18.7436000Z AUTOTUNE mm(12544x64, 64x128) 2025-09-07T12:09:18.7436619Z strides: [64, 1], [1, 64] 2025-09-07T12:09:18.7437150Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:18.7438468Z triton_mm_14 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=5, num_warps=4 2025-09-07T12:09:18.7440570Z triton_mm_15 0.0113 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 2025-09-07T12:09:18.7442707Z triton_mm_22 0.0113 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 2025-09-07T12:09:18.7444831Z triton_mm_23 0.0113 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 2025-09-07T12:09:18.7446933Z triton_mm_21 0.0123 ms 91.7% 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 2025-09-07T12:09:18.7448984Z triton_mm_6 0.0143 ms 78.6% 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 2025-09-07T12:09:18.7450985Z triton_mm_18 0.0195 ms 57.9% 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 2025-09-07T12:09:18.7453485Z triton_mm_19 0.0205 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=3, num_warps=4 2025-09-07T12:09:18.7455250Z triton_mm_7 0.0225 ms 50.0% 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 2025-09-07T12:09:18.7457340Z triton_mm_8 0.0236 ms 47.8% 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 2025-09-07T12:09:18.7459075Z SingleProcess AUTOTUNE benchmarking takes 0.4609 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T12:09:19.3368907Z Autotune Choices Stats: 2025-09-07T12:09:19.3371127Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_206", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T12:09:19.3547679Z AUTOTUNE mm(3136x256, 256x512) 2025-09-07T12:09:19.3548205Z strides: [256, 1], [1, 256] 2025-09-07T12:09:19.3548619Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:19.3549814Z triton_mm_206 0.0143 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 2025-09-07T12:09:19.3551599Z triton_mm_207 0.0143 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 2025-09-07T12:09:19.3553851Z triton_mm_208 0.0143 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=4, num_warps=8 2025-09-07T12:09:19.3555089Z mm 0.0154 ms 93.3% 2025-09-07T12:09:19.3556629Z triton_mm_201 0.0164 ms 87.5% 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 2025-09-07T12:09:19.3558703Z triton_mm_202 0.0164 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=8 2025-09-07T12:09:19.3560894Z triton_mm_200 0.0195 ms 73.7% 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=2, num_warps=4 2025-09-07T12:09:19.3563024Z triton_mm_211 0.0195 ms 73.7% 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 2025-09-07T12:09:19.3565269Z triton_mm_203 0.0215 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:09:19.3567032Z triton_mm_196 0.0236 ms 60.9% 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 2025-09-07T12:09:19.3568558Z SingleProcess AUTOTUNE benchmarking takes 0.4166 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T12:09:19.9899557Z Autotune Choices Stats: 2025-09-07T12:09:19.9901535Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_301", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.01740800030529499, "best_triton_pos": 0} 2025-09-07T12:09:20.0067479Z AUTOTUNE mm(3136x512, 512x512) 2025-09-07T12:09:20.0068069Z strides: [512, 1], [1, 512] 2025-09-07T12:09:20.0068575Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:20.0069925Z triton_mm_301 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:20.0072175Z triton_mm_302 0.0174 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:09:20.0074323Z triton_mm_294 0.0184 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:20.0076525Z triton_mm_297 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:20.0078643Z triton_mm_300 0.0195 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:20.0081306Z triton_mm_295 0.0205 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:09:20.0083506Z triton_mm_292 0.0225 ms 77.3% 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 2025-09-07T12:09:20.0085788Z triton_mm_296 0.0225 ms 77.3% 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 2025-09-07T12:09:20.0088076Z triton_mm_291 0.0236 ms 73.9% 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 2025-09-07T12:09:20.0090563Z triton_mm_293 0.0276 ms 63.0% 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 2025-09-07T12:09:20.0093227Z SingleProcess AUTOTUNE benchmarking takes 0.4314 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T12:09:21.2384637Z Autotune Choices Stats: 2025-09-07T12:09:21.2385972Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_356", "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": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T12:09:21.2566822Z AUTOTUNE mm(784x512, 512x1024) 2025-09-07T12:09:21.2567349Z strides: [512, 1], [1, 512] 2025-09-07T12:09:21.2567826Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:21.2569085Z triton_mm_356 0.0143 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 2025-09-07T12:09:21.2570976Z triton_mm_357 0.0143 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 2025-09-07T12:09:21.2573303Z triton_mm_355 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:21.2575357Z triton_mm_362 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:21.2577451Z triton_mm_363 0.0164 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 2025-09-07T12:09:21.2579227Z triton_mm_354 0.0174 ms 82.4% 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 2025-09-07T12:09:21.2581166Z triton_mm_352 0.0205 ms 70.0% 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 2025-09-07T12:09:21.2583222Z triton_mm_348 0.0215 ms 66.7% 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 2025-09-07T12:09:21.2585297Z triton_mm_347 0.0246 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 2025-09-07T12:09:21.2599116Z triton_mm_350 0.0246 ms 58.3% 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 2025-09-07T12:09:21.2600950Z SingleProcess AUTOTUNE benchmarking takes 0.4189 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T12:09:21.9823919Z Autotune Choices Stats: 2025-09-07T12:09:21.9826380Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_515", "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": 0.020479999482631683, "best_triton_pos": 0} 2025-09-07T12:09:21.9986601Z AUTOTUNE mm(784x1024, 1024x1024) 2025-09-07T12:09:21.9987228Z strides: [1024, 1], [1, 1024] 2025-09-07T12:09:21.9987756Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:21.9989097Z triton_mm_515 0.0205 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 2025-09-07T12:09:21.9991630Z triton_mm_519 0.0215 ms 95.2% 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 2025-09-07T12:09:21.9993781Z triton_mm_516 0.0225 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:09:21.9996317Z triton_mm_525 0.0246 ms 83.3% 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 2025-09-07T12:09:21.9998467Z triton_mm_518 0.0266 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:09:22.0000689Z triton_mm_520 0.0266 ms 76.9% 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 2025-09-07T12:09:22.0002863Z triton_mm_517 0.0287 ms 71.4% 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 2025-09-07T12:09:22.0005128Z triton_mm_521 0.0287 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:09:22.0007267Z triton_mm_511 0.0328 ms 62.5% 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 2025-09-07T12:09:22.0009073Z triton_mm_510 0.0338 ms 60.6% 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 2025-09-07T12:09:22.0010610Z SingleProcess AUTOTUNE benchmarking takes 0.4275 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T12:09:23.0673941Z Autotune Choices Stats: 2025-09-07T12:09:23.0675467Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "best_triton_kernel": "triton_mm_580", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T12:09:23.0771145Z AUTOTUNE mm(196x1024, 1024x2048) 2025-09-07T12:09:23.0771532Z strides: [1024, 1], [1, 1024] 2025-09-07T12:09:23.0771845Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:23.0772169Z mm 0.0164 ms 100.0% 2025-09-07T12:09:23.0773099Z triton_mm_580 0.0195 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:09:23.0774299Z triton_mm_576 0.0205 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:09:23.0775491Z triton_mm_577 0.0215 ms 76.2% 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 2025-09-07T12:09:23.0776957Z triton_mm_579 0.0215 ms 76.2% 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 2025-09-07T12:09:23.0778133Z triton_mm_582 0.0215 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=4, num_warps=8 2025-09-07T12:09:23.0779327Z triton_mm_570 0.0225 ms 72.7% 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 2025-09-07T12:09:23.0780510Z triton_mm_573 0.0236 ms 69.6% 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 2025-09-07T12:09:23.0781796Z triton_mm_586 0.0236 ms 69.6% 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 2025-09-07T12:09:23.0783180Z triton_mm_578 0.0256 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 2025-09-07T12:09:23.0784218Z SingleProcess AUTOTUNE benchmarking takes 0.2953 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:09:23.5056109Z Autotune Choices Stats: 2025-09-07T12:09:23.5057620Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.018432000651955605, "best_triton_kernel": "triton_mm_559", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T12:09:23.5152389Z AUTOTUNE mm(196x2048, 2048x1024) 2025-09-07T12:09:23.5152715Z strides: [2048, 1], [1, 2048] 2025-09-07T12:09:23.5153005Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:09:23.5153320Z mm 0.0174 ms 100.0% 2025-09-07T12:09:23.5154035Z triton_mm_559 0.0184 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:09:23.5155230Z triton_mm_555 0.0246 ms 70.8% 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 2025-09-07T12:09:23.5156414Z triton_mm_558 0.0256 ms 68.0% 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 2025-09-07T12:09:23.5157597Z triton_mm_552 0.0276 ms 63.0% 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 2025-09-07T12:09:23.5158779Z triton_mm_562 0.0287 ms 60.7% 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 2025-09-07T12:09:23.5159961Z triton_mm_553 0.0317 ms 54.8% 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 2025-09-07T12:09:23.5161129Z triton_mm_554 0.0317 ms 54.8% 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 2025-09-07T12:09:23.5162309Z triton_mm_561 0.0328 ms 53.1% 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 2025-09-07T12:09:23.5163500Z triton_mm_564 0.0328 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 2025-09-07T12:09:23.5164769Z SingleProcess AUTOTUNE benchmarking takes 0.3186 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:09:31.9215396Z pass 2025-09-07T12:09:35.7939230Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:09:35.7940687Z import pynvml # type: ignore[import] 2025-09-07T12:09:39.8137498Z 2025-09-07T12:09:48.8331365Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:09:48.8331731Z loading model: 0it [00:09, ?it/s] 2025-09-07T12:09:48.8470536Z cuda eval sam 2025-09-07T12:10:45.1729330Z Autotune Choices Stats: 2025-09-07T12:10:45.1730845Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.01228800043463707, "best_triton_pos": 1, "best_triton_time": 0.01228800043463707, "best_triton_kernel": "triton_mm_4625", "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"} 2025-09-07T12:10:45.1836811Z AUTOTUNE mm(4096x256, 256x128) 2025-09-07T12:10:45.1837140Z strides: [256, 1], [1, 256] 2025-09-07T12:10:45.1837438Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:10:45.1837749Z mm 0.0123 ms 100.0% 2025-09-07T12:10:45.1838451Z triton_mm_4625 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:10:45.1839676Z triton_mm_4627 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:10:45.1840893Z triton_mm_4628 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:10:45.1842107Z triton_mm_4629 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:10:45.1843310Z triton_mm_4630 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:10:45.1844519Z triton_mm_4631 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:10:45.1845719Z triton_mm_4619 0.0133 ms 92.3% 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 2025-09-07T12:10:45.1846899Z triton_mm_4621 0.0133 ms 92.3% 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 2025-09-07T12:10:45.1848096Z triton_mm_4634 0.0133 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 2025-09-07T12:10:45.1849129Z SingleProcess AUTOTUNE benchmarking takes 0.2822 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T12:11:05.1857452Z pass 2025-09-07T12:11:09.9959812Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:11:09.9961268Z import pynvml # type: ignore[import] 2025-09-07T12:11:12.7625355Z 2025-09-07T12:11:30.2964350Z loading model: 0it [00:00, ?it/s]Loading best configs from file /opt/conda/envs/py_3.10/lib/python3.10/site-packages/segment_anything_fast/configs/flash_4_configs_a100.p 2025-09-07T12:11:30.9939113Z 2025-09-07T12:11:30.9941494Z loading model: 0it [00:18, ?it/s] 2025-09-07T12:11:31.0030123Z cuda eval sam_fast 2025-09-07T12:12:56.1623853Z Autotune Choices Stats: 2025-09-07T12:12:56.1625454Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.22015999257564545, "best_triton_pos": 1, "best_triton_time": 0.2693119943141937, "best_triton_kernel": "triton_mm_91", "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"} 2025-09-07T12:12:56.1725072Z AUTOTUNE mm(4096x1280, 1280x5120) 2025-09-07T12:12:56.1725418Z strides: [1280, 1], [1, 1280] 2025-09-07T12:12:56.1725969Z dtypes: torch.float16, torch.float16 2025-09-07T12:12:56.1726278Z mm 0.2202 ms 100.0% 2025-09-07T12:12:56.1726997Z triton_mm_91 0.2693 ms 81.7% 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 2025-09-07T12:12:56.1728400Z triton_mm_90 0.2990 ms 73.6% 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 2025-09-07T12:12:56.1729584Z triton_mm_86 0.3205 ms 68.7% 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 2025-09-07T12:12:56.1730759Z triton_mm_87 0.3226 ms 68.3% 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 2025-09-07T12:12:56.1731915Z triton_mm_84 0.3308 ms 66.6% 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 2025-09-07T12:12:56.1733292Z triton_mm_92 0.3686 ms 59.7% 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 2025-09-07T12:12:56.1734481Z triton_mm_89 0.3871 ms 56.9% 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 2025-09-07T12:12:56.1735657Z triton_mm_85 0.3881 ms 56.7% 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 2025-09-07T12:12:56.1736828Z triton_mm_88 0.3912 ms 56.3% 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 2025-09-07T12:12:56.1737851Z SingleProcess AUTOTUNE benchmarking takes 0.7112 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T12:12:57.8467838Z Autotune Choices Stats: 2025-09-07T12:12:57.8469388Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.20377600193023682, "best_triton_pos": 1, "best_triton_time": 0.27136000990867615, "best_triton_kernel": "triton_mm_3446", "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"} 2025-09-07T12:12:57.8576433Z AUTOTUNE mm(4096x5120, 5120x1280) 2025-09-07T12:12:57.8576749Z strides: [5120, 1], [1, 5120] 2025-09-07T12:12:57.8577050Z dtypes: torch.float16, torch.float16 2025-09-07T12:12:57.8577355Z mm 0.2038 ms 100.0% 2025-09-07T12:12:57.8578055Z triton_mm_3446 0.2714 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=3, num_warps=4 2025-09-07T12:12:57.8579278Z triton_mm_3445 0.2847 ms 71.6% 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 2025-09-07T12:12:57.8580760Z triton_mm_3442 0.3185 ms 64.0% 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 2025-09-07T12:12:57.8581971Z triton_mm_3441 0.3256 ms 62.6% 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 2025-09-07T12:12:57.8583193Z triton_mm_3439 0.3328 ms 61.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:12:57.8584391Z triton_mm_3447 0.3389 ms 60.1% 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 2025-09-07T12:12:57.8585795Z triton_mm_3436 0.3656 ms 55.7% 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 2025-09-07T12:12:57.8586977Z triton_mm_3443 0.3768 ms 54.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:12:57.8588364Z triton_mm_3440 0.3820 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=4, num_warps=8 2025-09-07T12:12:57.8589403Z SingleProcess AUTOTUNE benchmarking takes 0.7235 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:12:58.2396769Z Autotune Choices Stats: 2025-09-07T12:12:58.2398275Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.01228800043463707, "best_triton_pos": 1, "best_triton_time": 0.01228800043463707, "best_triton_kernel": "triton_mm_3503", "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"} 2025-09-07T12:12:58.2496143Z AUTOTUNE mm(4096x256, 256x128) 2025-09-07T12:12:58.2496441Z strides: [256, 1], [1, 256] 2025-09-07T12:12:58.2496732Z dtypes: torch.float16, torch.float16 2025-09-07T12:12:58.2497056Z mm 0.0123 ms 100.0% 2025-09-07T12:12:58.2497759Z triton_mm_3503 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:12:58.2498969Z triton_mm_3505 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:12:58.2500161Z triton_mm_3506 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:12:58.2501368Z triton_mm_3507 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:12:58.2502574Z triton_mm_3508 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:12:58.2503771Z triton_mm_3509 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:12:58.2504969Z triton_mm_3497 0.0133 ms 92.3% 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 2025-09-07T12:12:58.2506233Z triton_mm_3499 0.0133 ms 92.3% 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 2025-09-07T12:12:58.2507680Z triton_mm_3512 0.0133 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 2025-09-07T12:12:58.2508709Z SingleProcess AUTOTUNE benchmarking takes 0.2520 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:12:58.8149684Z Autotune Choices Stats: 2025-09-07T12:12:58.8150917Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3532", "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=2, num_warps=2", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T12:12:58.8248113Z AUTOTUNE mm(7x256, 256x2048) 2025-09-07T12:12:58.8248437Z strides: [256, 1], [1, 256] 2025-09-07T12:12:58.8248949Z dtypes: torch.float16, torch.float16 2025-09-07T12:12:58.8249735Z triton_mm_3532 0.0092 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=2, num_warps=2 2025-09-07T12:12:58.8250954Z triton_mm_3533 0.0092 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=5, num_warps=4 2025-09-07T12:12:58.8252325Z triton_mm_3534 0.0092 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 2025-09-07T12:12:58.8253769Z triton_mm_3535 0.0092 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 2025-09-07T12:12:58.8254972Z triton_mm_3538 0.0092 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 2025-09-07T12:12:58.8256173Z triton_mm_3539 0.0092 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 2025-09-07T12:12:58.8257374Z triton_mm_3542 0.0092 ms 100.0% 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 2025-09-07T12:12:58.8258596Z triton_mm_3543 0.0092 ms 100.0% 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 2025-09-07T12:12:58.8259799Z triton_mm_3545 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:12:58.8260996Z triton_mm_3547 0.0092 ms 100.0% 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 2025-09-07T12:12:58.8262036Z SingleProcess AUTOTUNE benchmarking takes 0.2476 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T12:12:59.3824460Z Autotune Choices Stats: 2025-09-07T12:12:59.3825817Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3951", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T12:12:59.3925518Z AUTOTUNE mm(1x256, 256x256) 2025-09-07T12:12:59.3925868Z strides: [256, 1], [1, 256] 2025-09-07T12:12:59.3926160Z dtypes: torch.float16, torch.float16 2025-09-07T12:12:59.3926940Z triton_mm_3951 0.0072 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 2025-09-07T12:12:59.3927713Z mm 0.0082 ms 87.5% 2025-09-07T12:12:59.3928400Z triton_mm_3948 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T12:12:59.3929892Z triton_mm_3949 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:12:59.3931085Z triton_mm_3950 0.0082 ms 87.5% 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 2025-09-07T12:12:59.3932272Z triton_mm_3954 0.0082 ms 87.5% 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 2025-09-07T12:12:59.3933678Z triton_mm_3955 0.0082 ms 87.5% 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 2025-09-07T12:12:59.3934976Z triton_mm_3958 0.0082 ms 87.5% 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 2025-09-07T12:12:59.3936357Z triton_mm_3959 0.0082 ms 87.5% 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 2025-09-07T12:12:59.3937559Z triton_mm_3957 0.0092 ms 77.8% 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 2025-09-07T12:12:59.3938593Z SingleProcess AUTOTUNE benchmarking takes 0.2457 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T12:13:00.2734319Z Autotune Choices Stats: 2025-09-07T12:13:00.2735829Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.06143999844789505, "best_triton_pos": 1, "best_triton_time": 0.06758400052785873, "best_triton_kernel": "triton_mm_805", "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"} 2025-09-07T12:13:00.2833939Z AUTOTUNE mm(4096x1280, 1280x1280) 2025-09-07T12:13:00.2834236Z strides: [1280, 1], [1, 1280] 2025-09-07T12:13:00.2834559Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:00.2834869Z mm 0.0614 ms 100.0% 2025-09-07T12:13:00.2835577Z triton_mm_805 0.0676 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:00.2836775Z triton_mm_804 0.0758 ms 81.1% 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 2025-09-07T12:13:00.2837950Z triton_mm_800 0.0768 ms 80.0% 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 2025-09-07T12:13:00.2839147Z triton_mm_801 0.0788 ms 77.9% 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 2025-09-07T12:13:00.2840333Z triton_mm_798 0.0829 ms 74.1% 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 2025-09-07T12:13:00.2841518Z triton_mm_806 0.0860 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:13:00.2842702Z triton_mm_799 0.0901 ms 68.2% 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 2025-09-07T12:13:00.2843890Z triton_mm_802 0.0901 ms 68.2% 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 2025-09-07T12:13:00.2845334Z triton_mm_796 0.1034 ms 59.4% 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 2025-09-07T12:13:00.2846346Z SingleProcess AUTOTUNE benchmarking takes 0.4573 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T12:13:01.6481637Z Autotune Choices Stats: 2025-09-07T12:13:01.6483036Z {"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": 0.45772799849510193, "best_triton_pos": 0} 2025-09-07T12:13:01.6587205Z AUTOTUNE convolution(1x3x1024x1024, 1280x3x16x16) 2025-09-07T12:13:01.6592028Z strides: [3145728, 1048576, 1024, 1], [768, 256, 16, 1] 2025-09-07T12:13:01.6592401Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:01.6593347Z triton_convolution2d_6 0.4577 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 2025-09-07T12:13:01.6595125Z triton_convolution2d_3 0.5212 ms 87.8% 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 2025-09-07T12:13:01.6596049Z convolution 0.5478 ms 83.6% 2025-09-07T12:13:01.6596921Z triton_convolution2d_1 0.5560 ms 82.3% 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 2025-09-07T12:13:01.6598427Z triton_convolution2d_5 0.8069 ms 56.7% 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 2025-09-07T12:13:01.6599936Z triton_convolution2d_4 0.8735 ms 52.4% 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 2025-09-07T12:13:01.6601428Z triton_convolution2d_0 0.9032 ms 50.7% 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=4 2025-09-07T12:13:01.6602934Z triton_convolution2d_2 2.1494 ms 21.3% 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 2025-09-07T12:13:01.6604116Z SingleProcess AUTOTUNE benchmarking takes 0.3232 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T12:13:02.3619053Z Autotune Choices Stats: 2025-09-07T12:13:02.3620560Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.19865599274635315, "best_triton_pos": 1, "best_triton_time": 0.2539519965648651, "best_triton_kernel": "triton_mm_23", "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"} 2025-09-07T12:13:02.3723381Z AUTOTUNE mm(4900x1280, 1280x3840) 2025-09-07T12:13:02.3723728Z strides: [1280, 1], [1, 1280] 2025-09-07T12:13:02.3724032Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:02.3724330Z mm 0.1987 ms 100.0% 2025-09-07T12:13:02.3725046Z triton_mm_23 0.2540 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=3, num_warps=4 2025-09-07T12:13:02.3726258Z triton_mm_22 0.2621 ms 75.8% 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 2025-09-07T12:13:02.3727673Z triton_mm_16 0.2877 ms 69.0% 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 2025-09-07T12:13:02.3728857Z triton_mm_18 0.2898 ms 68.6% 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 2025-09-07T12:13:02.3730030Z triton_mm_19 0.2939 ms 67.6% 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 2025-09-07T12:13:02.3731201Z triton_mm_24 0.3471 ms 57.2% 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 2025-09-07T12:13:02.3732505Z triton_mm_17 0.3482 ms 57.1% 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 2025-09-07T12:13:02.3733907Z triton_mm_20 0.3492 ms 56.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:13:02.3735277Z triton_mm_21 0.3604 ms 55.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T12:13:02.3736314Z SingleProcess AUTOTUNE benchmarking takes 0.7129 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:02.6150909Z Autotune Choices Stats: 2025-09-07T12:13:02.6152147Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_33", "best_kernel_desc": "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", "best_time": 0.023552000522613525, "best_triton_pos": 0} 2025-09-07T12:13:02.6293219Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T12:13:02.6293579Z strides: [448000, 80, 1], [1152, 1, 80] 2025-09-07T12:13:02.6293906Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:02.6294675Z triton_bmm_33 0.0236 ms 100.0% 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=3, num_warps=4 2025-09-07T12:13:02.6295880Z triton_bmm_34 0.0236 ms 100.0% 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 2025-09-07T12:13:02.6297085Z triton_bmm_37 0.0236 ms 100.0% 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 2025-09-07T12:13:02.6298289Z triton_bmm_25 0.0246 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T12:13:02.6299476Z triton_bmm_27 0.0246 ms 95.8% 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 2025-09-07T12:13:02.6300658Z triton_bmm_28 0.0246 ms 95.8% 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=5, num_warps=4 2025-09-07T12:13:02.6301848Z triton_bmm_29 0.0246 ms 95.8% 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 2025-09-07T12:13:02.6303025Z triton_bmm_30 0.0246 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:13:02.6304198Z triton_bmm_32 0.0246 ms 95.8% 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 2025-09-07T12:13:02.6305733Z triton_bmm_35 0.0246 ms 95.8% 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 2025-09-07T12:13:02.6306784Z SingleProcess AUTOTUNE benchmarking takes 0.2551 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T12:13:02.8704861Z Autotune Choices Stats: 2025-09-07T12:13:02.8706076Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_41", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.02457600086927414, "best_triton_pos": 0} 2025-09-07T12:13:02.8806818Z AUTOTUNE bmm(14x5600x80, 14x80x14) 2025-09-07T12:13:02.8807313Z strides: [80, 1120, 1], [1152, 1, 80] 2025-09-07T12:13:02.8807636Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:02.8808411Z triton_bmm_41 0.0246 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T12:13:02.8809791Z triton_bmm_49 0.0246 ms 100.0% 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=3, num_warps=4 2025-09-07T12:13:02.8810990Z triton_bmm_50 0.0246 ms 100.0% 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 2025-09-07T12:13:02.8812194Z triton_bmm_52 0.0246 ms 100.0% 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 2025-09-07T12:13:02.8813606Z triton_bmm_53 0.0246 ms 100.0% 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 2025-09-07T12:13:02.8814812Z triton_bmm_43 0.0256 ms 96.0% 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 2025-09-07T12:13:02.8815998Z triton_bmm_44 0.0256 ms 96.0% 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 2025-09-07T12:13:02.8817161Z triton_bmm_46 0.0256 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:13:02.8818347Z triton_bmm_45 0.0266 ms 92.3% 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 2025-09-07T12:13:02.8819536Z triton_bmm_48 0.0266 ms 92.3% 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 2025-09-07T12:13:02.8820566Z SingleProcess AUTOTUNE benchmarking takes 0.2507 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T12:13:03.3891937Z Autotune Choices Stats: 2025-09-07T12:13:03.3893689Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.07782399654388428, "best_triton_pos": 1, "best_triton_time": 0.08601599931716919, "best_triton_kernel": "triton_mm_73", "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"} 2025-09-07T12:13:03.3994303Z AUTOTUNE mm(4900x1280, 1280x1280) 2025-09-07T12:13:03.3994630Z strides: [1280, 1], [1, 1280] 2025-09-07T12:13:03.3994918Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:03.3995223Z mm 0.0778 ms 100.0% 2025-09-07T12:13:03.3995932Z triton_mm_73 0.0860 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:03.3997371Z triton_mm_72 0.0952 ms 81.7% 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 2025-09-07T12:13:03.3998563Z triton_mm_68 0.0983 ms 79.2% 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 2025-09-07T12:13:03.3999748Z triton_mm_69 0.1065 ms 73.1% 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 2025-09-07T12:13:03.4000912Z triton_mm_66 0.1075 ms 72.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:03.4002196Z triton_mm_74 0.1106 ms 70.4% 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 2025-09-07T12:13:03.4003380Z triton_mm_67 0.1167 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:13:03.4004742Z triton_mm_71 0.1219 ms 63.9% 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 2025-09-07T12:13:03.4005926Z triton_mm_70 0.1249 ms 62.3% 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 2025-09-07T12:13:03.4006950Z SingleProcess AUTOTUNE benchmarking takes 0.5181 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:04.2405948Z Autotune Choices Stats: 2025-09-07T12:13:04.2407524Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.19763199985027313, "best_triton_pos": 1, "best_triton_time": 0.2099200040102005, "best_triton_kernel": "triton_mm_750", "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"} 2025-09-07T12:13:04.2511717Z AUTOTUNE addmm(4096x3840, 4096x1280, 1280x3840) 2025-09-07T12:13:04.2512090Z strides: [0, 1], [1280, 1], [1, 1280] 2025-09-07T12:13:04.2512450Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:13:04.2512822Z bias_addmm 0.1976 ms 100.0% 2025-09-07T12:13:04.2513548Z triton_mm_750 0.2099 ms 94.1% 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 2025-09-07T12:13:04.2514757Z triton_mm_751 0.2130 ms 92.8% 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 2025-09-07T12:13:04.2515513Z addmm 0.2376 ms 83.2% 2025-09-07T12:13:04.2516221Z triton_mm_744 0.2427 ms 81.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:04.2517403Z triton_mm_746 0.2427 ms 81.4% 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 2025-09-07T12:13:04.2518568Z triton_mm_747 0.2560 ms 77.2% 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 2025-09-07T12:13:04.2519758Z triton_mm_752 0.2857 ms 69.2% 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 2025-09-07T12:13:04.2520958Z triton_mm_745 0.2929 ms 67.5% 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 2025-09-07T12:13:04.2522484Z triton_mm_748 0.3195 ms 61.9% 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 2025-09-07T12:13:04.2523517Z SingleProcess AUTOTUNE benchmarking takes 0.7414 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T12:13:04.5271892Z Autotune Choices Stats: 2025-09-07T12:13:04.5273082Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_764", "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": 0.025599999353289604, "best_triton_pos": 0} 2025-09-07T12:13:04.5375928Z AUTOTUNE bmm(64x1024x80, 64x80x64) 2025-09-07T12:13:04.5376438Z strides: [81920, 80, 1], [5120, 1, 80] 2025-09-07T12:13:04.5376759Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:04.5377514Z triton_bmm_764 0.0256 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 2025-09-07T12:13:04.5378957Z triton_bmm_766 0.0256 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=3, num_warps=4 2025-09-07T12:13:04.5380186Z triton_bmm_767 0.0256 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 2025-09-07T12:13:04.5381391Z triton_bmm_758 0.0266 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=2, num_warps=4 2025-09-07T12:13:04.5382579Z triton_bmm_759 0.0266 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 2025-09-07T12:13:04.5383776Z triton_bmm_762 0.0266 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=3, num_warps=4 2025-09-07T12:13:04.5384969Z triton_bmm_763 0.0266 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=4, num_warps=8 2025-09-07T12:13:04.5386235Z triton_bmm_768 0.0266 ms 96.2% 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=2, num_warps=8 2025-09-07T12:13:04.5387437Z triton_bmm_769 0.0266 ms 96.2% 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 2025-09-07T12:13:04.5388637Z triton_bmm_760 0.0276 ms 92.6% 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 2025-09-07T12:13:04.5389672Z SingleProcess AUTOTUNE benchmarking takes 0.2846 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:05.1401909Z Autotune Choices Stats: 2025-09-07T12:13:05.1403125Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_3315", "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": 0.006144000217318535, "best_triton_pos": 0} 2025-09-07T12:13:05.1508036Z AUTOTUNE mm(2x2, 2x128) 2025-09-07T12:13:05.1508306Z strides: [2, 1], [128, 1] 2025-09-07T12:13:05.1508597Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:05.1509369Z triton_mm_3315 0.0061 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 2025-09-07T12:13:05.1510585Z triton_mm_3316 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T12:13:05.1511980Z triton_mm_3317 0.0061 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 2025-09-07T12:13:05.1513188Z triton_mm_3318 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T12:13:05.1514375Z triton_mm_3319 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:13:05.1515582Z triton_mm_3320 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:05.1516877Z triton_mm_3321 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:05.1518257Z triton_mm_3322 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:13:05.1519476Z triton_mm_3323 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:05.1520688Z triton_mm_3324 0.0061 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:05.1521730Z SingleProcess AUTOTUNE benchmarking takes 0.1768 seconds and 0.0003 seconds precompiling for 13 choices 2025-09-07T12:13:05.4092218Z Autotune Choices Stats: 2025-09-07T12:13:05.4093664Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_3328", "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=2, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T12:13:05.4198708Z AUTOTUNE addmm(7x256, 7x256, 256x256) 2025-09-07T12:13:05.4199057Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T12:13:05.4199412Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:13:05.4200221Z triton_mm_3328 0.0082 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=2, num_warps=2 2025-09-07T12:13:05.4201432Z triton_mm_3329 0.0082 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=5, num_warps=4 2025-09-07T12:13:05.4202632Z triton_mm_3330 0.0082 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 2025-09-07T12:13:05.4203833Z triton_mm_3331 0.0082 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 2025-09-07T12:13:05.4205029Z triton_mm_3334 0.0082 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 2025-09-07T12:13:05.4206226Z triton_mm_3335 0.0082 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 2025-09-07T12:13:05.4207428Z triton_mm_3338 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:05.4208805Z triton_mm_3339 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:05.4210004Z triton_mm_3340 0.0092 ms 88.9% 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=3, num_warps=4 2025-09-07T12:13:05.4211181Z triton_mm_3341 0.0092 ms 88.9% 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 2025-09-07T12:13:05.4212204Z SingleProcess AUTOTUNE benchmarking takes 0.2684 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:05.6524654Z Autotune Choices Stats: 2025-09-07T12:13:05.6525864Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3379", "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=2, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T12:13:05.6631474Z AUTOTUNE mm(7x256, 256x256) 2025-09-07T12:13:05.6631753Z strides: [256, 1], [1, 256] 2025-09-07T12:13:05.6632038Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:05.6633039Z triton_mm_3379 0.0082 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=2, num_warps=2 2025-09-07T12:13:05.6634251Z triton_mm_3380 0.0082 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=5, num_warps=4 2025-09-07T12:13:05.6635446Z triton_mm_3381 0.0082 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 2025-09-07T12:13:05.6636643Z triton_mm_3382 0.0082 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 2025-09-07T12:13:05.6637857Z triton_mm_3385 0.0082 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 2025-09-07T12:13:05.6639060Z triton_mm_3386 0.0082 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 2025-09-07T12:13:05.6640268Z triton_mm_3389 0.0082 ms 100.0% 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 2025-09-07T12:13:05.6641466Z triton_mm_3392 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:05.6642669Z triton_mm_3394 0.0082 ms 100.0% 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 2025-09-07T12:13:05.6643876Z triton_mm_3388 0.0092 ms 88.9% 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 2025-09-07T12:13:05.6644895Z SingleProcess AUTOTUNE benchmarking takes 0.2369 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T12:13:05.9221506Z Autotune Choices Stats: 2025-09-07T12:13:05.9222677Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_3396", "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=2, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T12:13:05.9328606Z AUTOTUNE addmm(7x128, 7x256, 256x128) 2025-09-07T12:13:05.9328937Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T12:13:05.9329463Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:13:05.9330290Z triton_mm_3396 0.0082 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=2, num_warps=2 2025-09-07T12:13:05.9331514Z triton_mm_3397 0.0082 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=5, num_warps=4 2025-09-07T12:13:05.9332712Z triton_mm_3398 0.0082 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 2025-09-07T12:13:05.9334156Z triton_mm_3399 0.0082 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 2025-09-07T12:13:05.9335462Z triton_mm_3402 0.0082 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 2025-09-07T12:13:05.9336827Z triton_mm_3403 0.0082 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 2025-09-07T12:13:05.9338037Z triton_mm_3411 0.0082 ms 100.0% 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 2025-09-07T12:13:05.9339239Z triton_mm_3405 0.0092 ms 88.9% 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 2025-09-07T12:13:05.9340437Z triton_mm_3406 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:05.9341638Z triton_mm_3407 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:05.9342684Z SingleProcess AUTOTUNE benchmarking takes 0.2690 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:06.1246581Z Autotune Choices Stats: 2025-09-07T12:13:06.1248240Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.04710400104522705, "best_triton_kernel": "triton_convolution2d_3452", "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"} 2025-09-07T12:13:06.1354272Z AUTOTUNE convolution(1x1280x64x64, 256x1280x1x1) 2025-09-07T12:13:06.1354698Z strides: [5242880, 4096, 64, 1], [1280, 1, 1, 1] 2025-09-07T12:13:06.1355044Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:06.1355366Z convolution 0.0276 ms 100.0% 2025-09-07T12:13:06.1356236Z triton_convolution2d_3452 0.0471 ms 58.7% 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 2025-09-07T12:13:06.1357150Z conv1x1_via_mm 0.0492 ms 56.2% 2025-09-07T12:13:06.1358036Z triton_convolution2d_3454 0.0604 ms 45.8% 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 2025-09-07T12:13:06.1359543Z triton_convolution2d_3451 0.0614 ms 45.0% 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 2025-09-07T12:13:06.1361048Z triton_convolution2d_3453 0.0686 ms 40.3% 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 2025-09-07T12:13:06.1362750Z triton_convolution2d_3449 0.0758 ms 36.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T12:13:06.1364246Z triton_convolution2d_3448 0.0860 ms 32.1% 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 2025-09-07T12:13:06.1365744Z triton_convolution2d_3450 0.1260 ms 22.0% 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 2025-09-07T12:13:06.1366998Z SingleProcess AUTOTUNE benchmarking takes 0.1985 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T12:13:06.3832950Z Autotune Choices Stats: 2025-09-07T12:13:06.3835008Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.06143999844789505, "best_triton_pos": 1, "best_triton_time": 0.13619199395179749, "best_triton_kernel": "triton_convolution2d_3461", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T12:13:06.3939537Z AUTOTUNE convolution(1x256x64x64, 256x256x3x3) 2025-09-07T12:13:06.3939917Z strides: [1048576, 4096, 64, 1], [2304, 9, 3, 1] 2025-09-07T12:13:06.3940272Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:06.3940577Z convolution 0.0614 ms 100.0% 2025-09-07T12:13:06.3941474Z triton_convolution2d_3461 0.1362 ms 45.1% 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 2025-09-07T12:13:06.3942989Z triton_convolution2d_3459 0.1608 ms 38.2% 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 2025-09-07T12:13:06.3944500Z triton_convolution2d_3458 0.1720 ms 35.7% 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 2025-09-07T12:13:06.3946087Z triton_convolution2d_3456 0.1751 ms 35.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T12:13:06.3947586Z triton_convolution2d_3460 0.2499 ms 24.6% 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 2025-09-07T12:13:06.3949090Z triton_convolution2d_3455 0.2796 ms 22.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T12:13:06.3950600Z triton_convolution2d_3457 0.3656 ms 16.8% 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 2025-09-07T12:13:06.3951775Z SingleProcess AUTOTUNE benchmarking takes 0.2563 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T12:13:06.6089616Z Autotune Choices Stats: 2025-09-07T12:13:06.6090816Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_3462", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T12:13:06.6195910Z AUTOTUNE mm(4096x2, 2x128) 2025-09-07T12:13:06.6196213Z strides: [2, 1], [128, 1] 2025-09-07T12:13:06.6196495Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:06.6197270Z triton_mm_3462 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T12:13:06.6198488Z triton_mm_3463 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:13:06.6199691Z triton_mm_3464 0.0072 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 2025-09-07T12:13:06.6200895Z triton_mm_3465 0.0072 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=8 2025-09-07T12:13:06.6202231Z triton_mm_3466 0.0072 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 2025-09-07T12:13:06.6203631Z triton_mm_3467 0.0072 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 2025-09-07T12:13:06.6204839Z triton_mm_3468 0.0072 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 2025-09-07T12:13:06.6206028Z triton_mm_3469 0.0072 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 2025-09-07T12:13:06.6207234Z triton_mm_3470 0.0072 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 2025-09-07T12:13:06.6208450Z triton_mm_3471 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:13:06.6209497Z SingleProcess AUTOTUNE benchmarking takes 0.2234 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T12:13:06.8442917Z Autotune Choices Stats: 2025-09-07T12:13:06.8444088Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3516", "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=5, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T12:13:06.8549831Z AUTOTUNE mm(7x128, 128x256) 2025-09-07T12:13:06.8550144Z strides: [128, 1], [1, 128] 2025-09-07T12:13:06.8550454Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:06.8551235Z triton_mm_3516 0.0072 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=5, num_warps=4 2025-09-07T12:13:06.8552471Z triton_mm_3517 0.0072 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 2025-09-07T12:13:06.8553673Z triton_mm_3521 0.0072 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 2025-09-07T12:13:06.8554863Z triton_mm_3525 0.0072 ms 100.0% 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 2025-09-07T12:13:06.8556064Z triton_mm_3528 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:06.8556809Z mm 0.0082 ms 87.5% 2025-09-07T12:13:06.8557756Z triton_mm_3515 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T12:13:06.8558956Z triton_mm_3518 0.0082 ms 87.5% 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 2025-09-07T12:13:06.8560157Z triton_mm_3522 0.0082 ms 87.5% 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 2025-09-07T12:13:06.8561345Z triton_mm_3523 0.0082 ms 87.5% 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=3, num_warps=4 2025-09-07T12:13:06.8562448Z SingleProcess AUTOTUNE benchmarking takes 0.2348 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T12:13:07.1220765Z Autotune Choices Stats: 2025-09-07T12:13:07.1222327Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3552", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T12:13:07.1330694Z AUTOTUNE mm(7x2048, 2048x256) 2025-09-07T12:13:07.1330977Z strides: [2048, 1], [1, 2048] 2025-09-07T12:13:07.1331281Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:07.1332056Z triton_mm_3552 0.0113 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 2025-09-07T12:13:07.1332986Z mm 0.0133 ms 84.6% 2025-09-07T12:13:07.1333687Z triton_mm_3556 0.0133 ms 84.6% 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 2025-09-07T12:13:07.1334891Z triton_mm_3560 0.0154 ms 73.3% 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 2025-09-07T12:13:07.1336105Z triton_mm_3564 0.0174 ms 64.7% 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 2025-09-07T12:13:07.1337291Z triton_mm_3551 0.0184 ms 61.1% 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 2025-09-07T12:13:07.1338469Z triton_mm_3550 0.0195 ms 57.9% 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 2025-09-07T12:13:07.1339644Z triton_mm_3555 0.0195 ms 57.9% 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 2025-09-07T12:13:07.1340833Z triton_mm_3549 0.0205 ms 55.0% 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 2025-09-07T12:13:07.1342029Z triton_mm_3559 0.0215 ms 52.4% 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 2025-09-07T12:13:07.1343043Z SingleProcess AUTOTUNE benchmarking takes 0.2775 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T12:13:07.3826760Z Autotune Choices Stats: 2025-09-07T12:13:07.3827978Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_3626", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T12:13:07.3936135Z AUTOTUNE mm(4096x128, 128x256) 2025-09-07T12:13:07.3936703Z strides: [128, 1], [1, 128] 2025-09-07T12:13:07.3937000Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:07.3937807Z triton_mm_3626 0.0113 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 2025-09-07T12:13:07.3939032Z triton_mm_3628 0.0113 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 2025-09-07T12:13:07.3940241Z triton_mm_3629 0.0113 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 2025-09-07T12:13:07.3941431Z triton_mm_3630 0.0113 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=4, num_warps=8 2025-09-07T12:13:07.3942750Z triton_mm_3632 0.0113 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 2025-09-07T12:13:07.3944150Z triton_mm_3633 0.0113 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 2025-09-07T12:13:07.3944916Z mm 0.0123 ms 91.7% 2025-09-07T12:13:07.3945685Z triton_mm_3621 0.0123 ms 91.7% 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 2025-09-07T12:13:07.3946884Z triton_mm_3623 0.0123 ms 91.7% 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 2025-09-07T12:13:07.3948076Z triton_mm_3624 0.0123 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 2025-09-07T12:13:07.3949097Z SingleProcess AUTOTUNE benchmarking takes 0.2539 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:07.6866482Z Autotune Choices Stats: 2025-09-07T12:13:07.6867706Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_3727", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T12:13:07.6977426Z AUTOTUNE addmm(4096x128, 4096x256, 256x128) 2025-09-07T12:13:07.6977828Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T12:13:07.6978179Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:13:07.6978982Z triton_mm_3727 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:13:07.6980219Z triton_mm_3730 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:13:07.6981430Z triton_mm_3731 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:07.6982629Z triton_mm_3733 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:13:07.6983392Z bias_addmm 0.0133 ms 92.3% 2025-09-07T12:13:07.6984118Z triton_mm_3721 0.0133 ms 92.3% 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 2025-09-07T12:13:07.6985356Z triton_mm_3729 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:07.6986761Z triton_mm_3732 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:07.6987951Z triton_mm_3722 0.0143 ms 85.7% 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 2025-09-07T12:13:07.6989128Z triton_mm_3723 0.0143 ms 85.7% 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 2025-09-07T12:13:07.6990148Z SingleProcess AUTOTUNE benchmarking takes 0.2888 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T12:13:07.9180962Z Autotune Choices Stats: 2025-09-07T12:13:07.9182169Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_3983", "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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T12:13:07.9291893Z AUTOTUNE addmm(1x32, 1x256, 256x32) 2025-09-07T12:13:07.9292563Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T12:13:07.9293160Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:13:07.9293987Z triton_mm_3983 0.0072 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 2025-09-07T12:13:07.9295205Z triton_mm_3984 0.0072 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 2025-09-07T12:13:07.9296413Z triton_mm_3987 0.0072 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=3, num_warps=2 2025-09-07T12:13:07.9297620Z triton_mm_3990 0.0072 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=4, num_warps=2 2025-09-07T12:13:07.9298824Z triton_mm_3991 0.0072 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 2025-09-07T12:13:07.9300023Z triton_mm_3982 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T12:13:07.9301194Z triton_mm_3988 0.0082 ms 87.5% 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=3, num_warps=2 2025-09-07T12:13:07.9302377Z triton_mm_3989 0.0082 ms 87.5% 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=4, num_warps=2 2025-09-07T12:13:07.9303560Z triton_mm_3986 0.0102 ms 70.0% 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=2, num_warps=2 2025-09-07T12:13:07.9304740Z triton_mm_3981 0.0123 ms 58.3% 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 2025-09-07T12:13:07.9305854Z SingleProcess AUTOTUNE benchmarking takes 0.1987 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T12:13:08.1206046Z Autotune Choices Stats: 2025-09-07T12:13:08.1207262Z {"num_choices": 14, "num_triton_choices": 13, "best_kernel": "triton_mm_4128", "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=2, num_warps=2", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T12:13:08.1322076Z AUTOTUNE mm(4x32, 32x65536) 2025-09-07T12:13:08.1322370Z strides: [32, 1], [1, 32] 2025-09-07T12:13:08.1322657Z dtypes: torch.float16, torch.float16 2025-09-07T12:13:08.1323433Z triton_mm_4128 0.0123 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=2, num_warps=2 2025-09-07T12:13:08.1324636Z triton_mm_4129 0.0123 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=5, num_warps=4 2025-09-07T12:13:08.1325825Z triton_mm_4130 0.0123 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 2025-09-07T12:13:08.1327002Z triton_mm_4132 0.0123 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=2, num_warps=4 2025-09-07T12:13:08.1328328Z triton_mm_4133 0.0123 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 2025-09-07T12:13:08.1329696Z triton_mm_4134 0.0123 ms 100.0% 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 2025-09-07T12:13:08.1330905Z triton_mm_4135 0.0123 ms 100.0% 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=8 2025-09-07T12:13:08.1332113Z triton_mm_4136 0.0123 ms 100.0% 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 2025-09-07T12:13:08.1333535Z triton_mm_4137 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:13:08.1334747Z triton_mm_4138 0.0123 ms 100.0% 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 2025-09-07T12:13:08.1335770Z SingleProcess AUTOTUNE benchmarking takes 0.1935 seconds and 0.0002 seconds precompiling for 14 choices 2025-09-07T12:13:08.3183278Z Autotune Choices Stats: 2025-09-07T12:13:08.3185660Z {"num_choices": 13, "num_triton_choices": 11, "best_kernel": "triton_mm_4175", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T12:13:08.3294787Z AUTOTUNE addmm(1x4, 1x256, 256x4) 2025-09-07T12:13:08.3295391Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T12:13:08.3296036Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:13:08.3297607Z triton_mm_4175 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T12:13:08.3299973Z triton_mm_4176 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T12:13:08.3302309Z triton_mm_4177 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T12:13:08.3304640Z triton_mm_4180 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T12:13:08.3307021Z triton_mm_4182 0.0072 ms 100.0% 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=4, num_warps=1 2025-09-07T12:13:08.3309677Z triton_mm_4183 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T12:13:08.3312055Z triton_mm_4184 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T12:13:08.3314393Z triton_mm_4181 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T12:13:08.3315846Z bias_addmm 0.0102 ms 70.0% 2025-09-07T12:13:08.3317207Z triton_mm_4179 0.0102 ms 70.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T12:13:08.3319412Z SingleProcess AUTOTUNE benchmarking takes 0.1966 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T12:13:26.0627874Z pass 2025-09-07T12:13:32.5630041Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:13:32.5631510Z import pynvml # type: ignore[import] 2025-09-07T12:13:35.7998030Z 2025-09-07T12:13:36.9499422Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:13:36.9500041Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:13:36.9567829Z cuda eval shufflenet_v2_x1_0 2025-09-07T12:13:53.0246543Z Autotune Choices Stats: 2025-09-07T12:13:53.0247769Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_30", "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=5, num_warps=4", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T12:13:53.0366580Z AUTOTUNE mm(12544x24, 24x58) 2025-09-07T12:13:53.0366953Z strides: [24, 1], [1, 24] 2025-09-07T12:13:53.0367250Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:53.0368068Z triton_mm_30 0.0082 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=5, num_warps=4 2025-09-07T12:13:53.0369266Z triton_mm_25 0.0092 ms 88.9% 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 2025-09-07T12:13:53.0370441Z triton_mm_26 0.0092 ms 88.9% 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=4 2025-09-07T12:13:53.0371625Z triton_mm_28 0.0092 ms 88.9% 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 2025-09-07T12:13:53.0373079Z triton_mm_29 0.0092 ms 88.9% 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 2025-09-07T12:13:53.0374278Z triton_mm_31 0.0092 ms 88.9% 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=4 2025-09-07T12:13:53.0375467Z triton_mm_35 0.0092 ms 88.9% 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 2025-09-07T12:13:53.0376655Z triton_mm_36 0.0092 ms 88.9% 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 2025-09-07T12:13:53.0377846Z triton_mm_37 0.0092 ms 88.9% 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=5, num_warps=8 2025-09-07T12:13:53.0378823Z mm 0.0102 ms 80.0% 2025-09-07T12:13:53.0379357Z SingleProcess AUTOTUNE benchmarking takes 0.3270 seconds and 0.0004 seconds precompiling for 17 choices 2025-09-07T12:13:53.7628539Z Autotune Choices Stats: 2025-09-07T12:13:53.7629793Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_183", "best_kernel_desc": "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", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T12:13:53.7740854Z AUTOTUNE mm(3136x116, 116x116) 2025-09-07T12:13:53.7741168Z strides: [116, 1], [1, 116] 2025-09-07T12:13:53.7741456Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:53.7742241Z triton_mm_183 0.0102 ms 100.0% 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=2, num_warps=4 2025-09-07T12:13:53.7743803Z triton_mm_186 0.0102 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 2025-09-07T12:13:53.7745314Z triton_mm_189 0.0102 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 2025-09-07T12:13:53.7746537Z triton_mm_190 0.0102 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 2025-09-07T12:13:53.7747753Z triton_mm_191 0.0102 ms 100.0% 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 2025-09-07T12:13:53.7748953Z triton_mm_193 0.0102 ms 100.0% 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 2025-09-07T12:13:53.7750154Z triton_mm_184 0.0113 ms 90.9% 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 2025-09-07T12:13:53.7751339Z triton_mm_185 0.0113 ms 90.9% 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 2025-09-07T12:13:53.7752523Z triton_mm_188 0.0113 ms 90.9% 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 2025-09-07T12:13:53.7753705Z triton_mm_192 0.0113 ms 90.9% 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 2025-09-07T12:13:53.7754729Z SingleProcess AUTOTUNE benchmarking takes 0.2694 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:54.4418001Z Autotune Choices Stats: 2025-09-07T12:13:54.4419527Z {"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": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T12:13:54.4525738Z AUTOTUNE mm(3136x58, 58x58) 2025-09-07T12:13:54.4526017Z strides: [58, 1], [1, 58] 2025-09-07T12:13:54.4526304Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:54.4527075Z triton_mm_57 0.0082 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 2025-09-07T12:13:54.4528280Z triton_mm_58 0.0082 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 2025-09-07T12:13:54.4529474Z triton_mm_59 0.0082 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 2025-09-07T12:13:54.4530931Z triton_mm_60 0.0082 ms 100.0% 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 2025-09-07T12:13:54.4532116Z triton_mm_62 0.0082 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=2, num_warps=4 2025-09-07T12:13:54.4533562Z triton_mm_63 0.0082 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 2025-09-07T12:13:54.4534743Z triton_mm_64 0.0082 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=5, num_warps=4 2025-09-07T12:13:54.4536035Z triton_mm_65 0.0082 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 2025-09-07T12:13:54.4537391Z triton_mm_66 0.0082 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 2025-09-07T12:13:54.4538577Z triton_mm_67 0.0082 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 2025-09-07T12:13:54.4539586Z SingleProcess AUTOTUNE benchmarking takes 0.2603 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T12:13:55.1183548Z Autotune Choices Stats: 2025-09-07T12:13:55.1184778Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_491", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T12:13:55.1291432Z AUTOTUNE mm(784x232, 232x232) 2025-09-07T12:13:55.1291729Z strides: [232, 1], [1, 232] 2025-09-07T12:13:55.1292016Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:55.1293006Z triton_mm_491 0.0092 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 2025-09-07T12:13:55.1294217Z triton_mm_490 0.0102 ms 90.0% 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 2025-09-07T12:13:55.1295412Z triton_mm_492 0.0102 ms 90.0% 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 2025-09-07T12:13:55.1296612Z triton_mm_495 0.0102 ms 90.0% 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 2025-09-07T12:13:55.1297815Z triton_mm_496 0.0102 ms 90.0% 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 2025-09-07T12:13:55.1298562Z mm 0.0113 ms 81.8% 2025-09-07T12:13:55.1299234Z triton_mm_489 0.0113 ms 81.8% 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 2025-09-07T12:13:55.1300428Z triton_mm_497 0.0113 ms 81.8% 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 2025-09-07T12:13:55.1301619Z triton_mm_498 0.0113 ms 81.8% 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 2025-09-07T12:13:55.1303083Z triton_mm_499 0.0113 ms 81.8% 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 2025-09-07T12:13:55.1304123Z SingleProcess AUTOTUNE benchmarking takes 0.2579 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:55.7956501Z Autotune Choices Stats: 2025-09-07T12:13:55.7958742Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_219", "best_kernel_desc": "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", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T12:13:55.8069693Z AUTOTUNE mm(784x116, 116x116) 2025-09-07T12:13:55.8070294Z strides: [116, 1], [1, 116] 2025-09-07T12:13:55.8071236Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:55.8072713Z triton_mm_219 0.0082 ms 100.0% 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=2, num_warps=4 2025-09-07T12:13:55.8075071Z triton_mm_220 0.0082 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 2025-09-07T12:13:55.8077738Z triton_mm_221 0.0082 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 2025-09-07T12:13:55.8079980Z triton_mm_222 0.0082 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 2025-09-07T12:13:55.8081446Z mm 0.0092 ms 88.9% 2025-09-07T12:13:55.8082632Z triton_mm_224 0.0092 ms 88.9% 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 2025-09-07T12:13:55.8084893Z triton_mm_225 0.0092 ms 88.9% 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 2025-09-07T12:13:55.8087092Z triton_mm_226 0.0092 ms 88.9% 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 2025-09-07T12:13:55.8089469Z triton_mm_227 0.0102 ms 80.0% 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 2025-09-07T12:13:55.8091582Z triton_mm_223 0.0113 ms 72.7% 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=2, num_warps=4 2025-09-07T12:13:55.8093955Z SingleProcess AUTOTUNE benchmarking takes 0.3244 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:56.5939577Z Autotune Choices Stats: 2025-09-07T12:13:56.5942431Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.009216000325977802, "best_triton_pos": 1, "best_triton_time": 0.009216000325977802, "best_triton_kernel": "triton_mm_525", "best_triton_kernel_desc": "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"} 2025-09-07T12:13:56.6048682Z AUTOTUNE mm(196x232, 232x232) 2025-09-07T12:13:56.6049262Z strides: [232, 1], [1, 232] 2025-09-07T12:13:56.6049756Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:56.6050331Z mm 0.0092 ms 100.0% 2025-09-07T12:13:56.6051625Z triton_mm_525 0.0092 ms 100.0% 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=2, num_warps=4 2025-09-07T12:13:56.6054258Z triton_mm_526 0.0092 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 2025-09-07T12:13:56.6056867Z triton_mm_527 0.0092 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 2025-09-07T12:13:56.6059304Z triton_mm_528 0.0092 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 2025-09-07T12:13:56.6061677Z triton_mm_531 0.0092 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 2025-09-07T12:13:56.6064043Z triton_mm_532 0.0102 ms 90.0% 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 2025-09-07T12:13:56.6066662Z triton_mm_534 0.0102 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 2025-09-07T12:13:56.6068998Z triton_mm_535 0.0102 ms 90.0% 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 2025-09-07T12:13:56.6071678Z triton_mm_533 0.0113 ms 81.8% 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 2025-09-07T12:13:56.6073664Z SingleProcess AUTOTUNE benchmarking takes 0.2585 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:57.4380808Z Autotune Choices Stats: 2025-09-07T12:13:57.4382196Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_2", "best_kernel_desc": "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", "best_time": 0.021503999829292297, "best_triton_pos": 0} 2025-09-07T12:13:57.4491630Z AUTOTUNE convolution(4x3x224x224, 24x3x3x3) 2025-09-07T12:13:57.4492012Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T12:13:57.4492354Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:57.4493518Z triton_convolution2d_2 0.0215 ms 100.0% 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T12:13:57.4495024Z triton_convolution2d_4 0.0215 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 2025-09-07T12:13:57.4495937Z convolution 0.0246 ms 87.5% 2025-09-07T12:13:57.4496796Z triton_convolution2d_0 0.0256 ms 84.0% 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=4 2025-09-07T12:13:57.4498281Z triton_convolution2d_3 0.0256 ms 84.0% 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 2025-09-07T12:13:57.4499763Z triton_convolution2d_1 0.0266 ms 80.8% 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 2025-09-07T12:13:57.4501239Z triton_convolution2d_5 0.0287 ms 75.0% 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 2025-09-07T12:13:57.4502407Z SingleProcess AUTOTUNE benchmarking takes 0.1193 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T12:13:57.6613372Z Autotune Choices Stats: 2025-09-07T12:13:57.6614555Z {"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": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T12:13:57.6775466Z AUTOTUNE mm(3136x24, 24x58) 2025-09-07T12:13:57.6775764Z strides: [24, 1], [1, 24] 2025-09-07T12:13:57.6776051Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:57.6776818Z triton_mm_7 0.0072 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 2025-09-07T12:13:57.6778015Z triton_mm_8 0.0072 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 2025-09-07T12:13:57.6779371Z triton_mm_9 0.0072 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 2025-09-07T12:13:57.6780537Z triton_mm_10 0.0072 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 2025-09-07T12:13:57.6781906Z triton_mm_12 0.0072 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=2, num_warps=4 2025-09-07T12:13:57.6783093Z triton_mm_13 0.0072 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=8 2025-09-07T12:13:57.6784274Z triton_mm_14 0.0072 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=5, num_warps=4 2025-09-07T12:13:57.6785536Z triton_mm_15 0.0072 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 2025-09-07T12:13:57.6786724Z triton_mm_16 0.0072 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 2025-09-07T12:13:57.6787911Z triton_mm_17 0.0072 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=4 2025-09-07T12:13:57.6788922Z SingleProcess AUTOTUNE benchmarking takes 0.2278 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T12:13:57.9836814Z Autotune Choices Stats: 2025-09-07T12:13:57.9838278Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.011264000087976456, "best_triton_pos": 1, "best_triton_time": 0.011264000087976456, "best_triton_kernel": "triton_mm_640", "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"} 2025-09-07T12:13:57.9946682Z AUTOTUNE mm(196x464, 464x1024) 2025-09-07T12:13:57.9946982Z strides: [464, 1], [1, 464] 2025-09-07T12:13:57.9947264Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T12:13:57.9947589Z mm 0.0113 ms 100.0% 2025-09-07T12:13:57.9948294Z triton_mm_640 0.0113 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 2025-09-07T12:13:57.9949502Z triton_mm_633 0.0123 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 2025-09-07T12:13:57.9950688Z triton_mm_639 0.0123 ms 91.7% 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 2025-09-07T12:13:57.9951861Z triton_mm_634 0.0133 ms 84.6% 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 2025-09-07T12:13:57.9953227Z triton_mm_642 0.0133 ms 84.6% 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 2025-09-07T12:13:57.9954419Z triton_mm_643 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:57.9955609Z triton_mm_645 0.0133 ms 84.6% 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 2025-09-07T12:13:57.9956794Z triton_mm_635 0.0143 ms 78.6% 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 2025-09-07T12:13:57.9958071Z triton_mm_636 0.0143 ms 78.6% 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 2025-09-07T12:13:57.9959275Z SingleProcess AUTOTUNE benchmarking takes 0.2610 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:13:58.2689572Z Autotune Choices Stats: 2025-09-07T12:13:58.2690764Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_654", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T12:13:58.2804464Z AUTOTUNE addmm(4x1000, 4x1024, 1024x1000) 2025-09-07T12:13:58.2804813Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T12:13:58.2805199Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T12:13:58.2806021Z triton_mm_654 0.0102 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 2025-09-07T12:13:58.2807235Z triton_mm_658 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:13:58.2817057Z triton_mm_662 0.0123 ms 83.3% 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 2025-09-07T12:13:58.2818287Z triton_mm_666 0.0133 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:13:58.2819035Z bias_addmm 0.0143 ms 71.4% 2025-09-07T12:13:58.2819764Z triton_mm_652 0.0143 ms 71.4% 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 2025-09-07T12:13:58.2820956Z triton_mm_653 0.0143 ms 71.4% 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 2025-09-07T12:13:58.2822139Z triton_mm_657 0.0143 ms 71.4% 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 2025-09-07T12:13:58.2823322Z triton_mm_651 0.0154 ms 66.7% 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 2025-09-07T12:13:58.2824507Z triton_mm_661 0.0154 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:13:58.2825643Z SingleProcess AUTOTUNE benchmarking takes 0.2847 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T12:14:03.5988465Z pass 2025-09-07T12:14:06.4684995Z accuracy pass_rate=93.33% 2025-09-07T12:14:06.4691509Z calls_captured gmean=0.00x mean=409.467x 2025-09-07T12:14:06.4696649Z unique_graphs gmean=0.00x mean=0.867x 2025-09-07T12:14:06.4700397Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T12:14:06.4704550Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T12:14:06.4708841Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:14:06.4712779Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:14:06.4716862Z cudagraph_skips gmean=0.00x mean=0.067x 2025-09-07T12:14:06.4718249Z compilation_latency mean=24.528 seconds 2025-09-07T12:14:07.4487961Z + [[ 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* ]] 2025-09-07T12:14:07.4495893Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T12:14:07.4497432Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --quant --backend inductor --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv 2025-09-07T12:14:08.0475853Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:14:08.0477288Z import pynvml # type: ignore[import] 2025-09-07T12:14:11.0307829Z usage: torchbench.py 2025-09-07T12:14:11.0308179Z [-h] 2025-09-07T12:14:11.0308404Z [--filter FILTER] 2025-09-07T12:14:11.0308675Z [--exclude EXCLUDE] 2025-09-07T12:14:11.0308974Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T12:14:11.0309371Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T12:14:11.0309791Z [--partition-id PARTITION_ID] 2025-09-07T12:14:11.0310109Z [--devices DEVICES] 2025-09-07T12:14:11.0310377Z [--device-index DEVICE_INDEX] 2025-09-07T12:14:11.0310682Z [--repeat REPEAT] 2025-09-07T12:14:11.0310995Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T12:14:11.0311350Z [--randomize-input] 2025-09-07T12:14:11.0311611Z [--threads THREADS] 2025-09-07T12:14:11.0311870Z [--nopython] 2025-09-07T12:14:11.0312106Z [--no-skip] 2025-09-07T12:14:11.0312347Z [--prims-nvfuser] 2025-09-07T12:14:11.0312598Z [--dump-raw-metrics] 2025-09-07T12:14:11.0312882Z [--log-operator-inputs] 2025-09-07T12:14:11.0313167Z [--channels-last] 2025-09-07T12:14:11.0313438Z [--batch-size BATCH_SIZE] 2025-09-07T12:14:11.0313731Z [--iterations ITERATIONS] 2025-09-07T12:14:11.0314044Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T12:14:11.0314365Z [--cosine] 2025-09-07T12:14:11.0314586Z [--freezing] 2025-09-07T12:14:11.0314848Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T12:14:11.0315157Z [--ci] 2025-09-07T12:14:11.0315372Z [--dashboard] 2025-09-07T12:14:11.0315607Z [--skip-fp64-check] 2025-09-07T12:14:11.0315865Z [--fast] 2025-09-07T12:14:11.0316088Z [--only ONLY] 2025-09-07T12:14:11.0316328Z [--multiprocess] 2025-09-07T12:14:11.0316556Z [--ddp] 2025-09-07T12:14:11.0316772Z [--fsdp] 2025-09-07T12:14:11.0317030Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T12:14:11.0317433Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T12:14:11.0317800Z [--dynamic-shapes] 2025-09-07T12:14:11.0318079Z [--propagate-real-tensors] 2025-09-07T12:14:11.0318383Z [--dynamic-batch-only] 2025-09-07T12:14:11.0318671Z [--specialize-int] 2025-09-07T12:14:11.0318918Z [--use-eval-mode] 2025-09-07T12:14:11.0319187Z [--skip-accuracy-check] 2025-09-07T12:14:11.0319792Z [--generate-aot-autograd-stats] 2025-09-07T12:14:11.0320114Z [--inductor-settings] 2025-09-07T12:14:11.0320379Z [--suppress-errors] 2025-09-07T12:14:11.0320648Z [--output OUTPUT] 2025-09-07T12:14:11.0320932Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T12:14:11.0321272Z [--disable-output] 2025-09-07T12:14:11.0321525Z [--baseline BASELINE] 2025-09-07T12:14:11.0321792Z [--part PART] 2025-09-07T12:14:11.0322051Z [--export-profiler-trace] 2025-09-07T12:14:11.0322386Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T12:14:11.0322723Z [--profile-details] 2025-09-07T12:14:11.0323000Z [--export-perfdoctor] 2025-09-07T12:14:11.0323295Z [--diff-branch DIFF_BRANCH] 2025-09-07T12:14:11.0323581Z [--tag TAG] 2025-09-07T12:14:11.0323796Z [--explain] 2025-09-07T12:14:11.0324131Z [--stats] 2025-09-07T12:14:11.0324374Z [--use-warm-peak-memory] 2025-09-07T12:14:11.0324659Z [--print-memory] 2025-09-07T12:14:11.0324921Z [--print-compilation-time] 2025-09-07T12:14:11.0325233Z [--print-dataframe-summary] 2025-09-07T12:14:11.0325542Z [--disable-cudagraphs] 2025-09-07T12:14:11.0325841Z [--disable-split-reductions] 2025-09-07T12:14:11.0326336Z [--disable-persistent-reductions] 2025-09-07T12:14:11.0326683Z [--disable-divisible-by-16] 2025-09-07T12:14:11.0327038Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T12:14:11.0327405Z [--print-graph-breaks] 2025-09-07T12:14:11.0327680Z [--log-graph-breaks] 2025-09-07T12:14:11.0327955Z [--trace-on-xla] 2025-09-07T12:14:11.0328229Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T12:14:11.0328544Z [--collect-outputs] 2025-09-07T12:14:11.0328828Z [--enable-activation-checkpointing] 2025-09-07T12:14:11.0329150Z [--timing] 2025-09-07T12:14:11.0329381Z [--progress] 2025-09-07T12:14:11.0329639Z [--timeout TIMEOUT] 2025-09-07T12:14:11.0329981Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T12:14:11.0330394Z [--no-translation-validation] 2025-09-07T12:14:11.0330692Z [--minify] 2025-09-07T12:14:11.0330931Z [--compiled-autograd] 2025-09-07T12:14:11.0331211Z [--profile_dynamo_cache_lookup] 2025-09-07T12:14:11.0331526Z [--snapshot-memory] 2025-09-07T12:14:11.0331793Z [--retain-output] 2025-09-07T12:14:11.0332059Z [--caching-precompile] 2025-09-07T12:14:11.0332385Z [--cold-start-latency | --warm-start-latency] 2025-09-07T12:14:11.0332730Z [--nnc] 2025-09-07T12:14:11.0333260Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T12:14:11.0333619Z [--amp-dtype {bfloat16,float16}] 2025-09-07T12:14:11.0333923Z [--verbose | --quiet] 2025-09-07T12:14:11.0337449Z [--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] 2025-09-07T12:14:11.0341046Z (--accuracy | --performance | --tolerance) 2025-09-07T12:14:11.0341381Z (--training | --inference) 2025-09-07T12:14:11.0341803Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T12:14:11.7146003Z + true 2025-09-07T12:14:11.7147325Z + cp /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv 2025-09-07T12:14:11.7163064Z + for target in "${targets[@]}" 2025-09-07T12:14:11.7163442Z + target_flag=('--performance') 2025-09-07T12:14:11.7163744Z + local target_flag 2025-09-07T12:14:11.7164018Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T12:14:11.7164373Z + target_flag+=(--cold-start-latency) 2025-09-07T12:14:11.7165759Z + [[ 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* ]] 2025-09-07T12:14:11.7168197Z + [[ 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* ]] 2025-09-07T12:14:11.7171292Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 4 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv 2025-09-07T12:14:12.2884684Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:14:12.2887144Z import pynvml # type: ignore[import] 2025-09-07T12:14:16.0743234Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:14:16.0744713Z import pynvml # type: ignore[import] 2025-09-07T12:14:19.0496976Z 2025-09-07T12:14:19.8653975Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:14:19.8654372Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:14:19.8676332Z cuda eval phlippe_resnet 2025-09-07T12:14:27.9996518Z 2025-09-07T12:14:28.0998881Z running benchmark: 0% 0/30 [00:00 2025-09-07T12:39:41.4671171Z torchbench_main() 2025-09-07T12:39:41.4671717Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T12:39:41.4672677Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T12:39:41.4673285Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T12:39:41.4676696Z process_entry(0, runner, original_dir, args) 2025-09-07T12:39:41.4677287Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T12:39:41.4680642Z result = run(runner, args, original_dir) 2025-09-07T12:39:41.4681182Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4251, in run 2025-09-07T12:39:41.4685606Z assert marked, f"nothing in example_inputs had a dim with {batch_size}" 2025-09-07T12:39:41.4686527Z AssertionError: nothing in example_inputs had a dim with 32 2025-09-07T12:39:45.4013599Z Run failed with return code: 1 2025-09-07T12:39:45.4013985Z Output: None 2025-09-07T12:39:45.4014210Z Error: None 2025-09-07T12:39:46.0241645Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:39:46.0243086Z import pynvml # type: ignore[import] 2025-09-07T12:39:48.9866900Z 2025-09-07T12:39:50.2084679Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:39:50.2085245Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:39:50.2139373Z cuda eval shufflenet_v2_x1_0 2025-09-07T12:40:06.2270172Z 2025-09-07T12:40:06.3363211Z running benchmark: 0% 0/30 [00:00> $GITHUB_ENV 2025-09-07T13:35:36.6140882Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-09-07T13:35:36.6160186Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:35:36.6161032Z env: 2025-09-07T13:35:36.6161403Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:35:36.6161987Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:35:36.6162787Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:35:36.6163835Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:35:36.6164763Z ##[endgroup] 2025-09-07T13:35:36.6205917Z + [[ -n '' ]] 2025-09-07T13:35:36.6206604Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T13:35:36.9372989Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T13:35:37.7300931Z Collecting boto3==1.35.33 2025-09-07T13:35:37.8062930Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-09-07T13:35:37.8446313Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 3.6 MB/s eta 0:00:00 2025-09-07T13:35:38.0054838Z Collecting psutil==7.0.0 2025-09-07T13:35:38.0166964Z 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) 2025-09-07T13:35:38.0572415Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 7.0 MB/s eta 0:00:00 2025-09-07T13:35:38.1024623Z Collecting pynvml==12.0.0 2025-09-07T13:35:38.1130749Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-09-07T13:35:38.8799230Z Collecting botocore<1.36.0,>=1.35.33 2025-09-07T13:35:38.8912842Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-09-07T13:35:39.3445060Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 39.5 MB/s eta 0:00:00 2025-09-07T13:35:39.4077111Z Collecting jmespath<2.0.0,>=0.7.1 2025-09-07T13:35:39.4183320Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-09-07T13:35:39.4526958Z Collecting s3transfer<0.11.0,>=0.10.0 2025-09-07T13:35:39.4648491Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-09-07T13:35:39.4709631Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 17.3 MB/s eta 0:00:00 2025-09-07T13:35:39.5129047Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-09-07T13:35:39.5234337Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-09-07T13:35:39.5293368Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 9.1 MB/s eta 0:00:00 2025-09-07T13:35:39.5361113Z 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) 2025-09-07T13:35:39.5374822Z 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) 2025-09-07T13:35:39.8147140Z Installing collected packages: nvidia-ml-py, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-09-07T13:35:39.8148262Z Attempting uninstall: nvidia-ml-py 2025-09-07T13:35:39.8153906Z Found existing installation: nvidia-ml-py 11.525.84 2025-09-07T13:35:39.8192400Z Uninstalling nvidia-ml-py-11.525.84: 2025-09-07T13:35:39.8216978Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-09-07T13:35:39.8970173Z Attempting uninstall: psutil 2025-09-07T13:35:39.8981097Z Found existing installation: psutil 5.9.8 2025-09-07T13:35:39.9211584Z Uninstalling psutil-5.9.8: 2025-09-07T13:35:39.9223175Z Successfully uninstalled psutil-5.9.8 2025-09-07T13:35:40.7916224Z 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 2025-09-07T13:35:41.0141231Z + DEVICE_NAME= 2025-09-07T13:35:41.0141512Z + DEVICE_TYPE= 2025-09-07T13:35:41.0141767Z + command -v nvidia-smi 2025-09-07T13:35:41.0142388Z + python3 -mpip install torch==2.7.1 2025-09-07T13:35:41.0142760Z /usr/bin/nvidia-smi 2025-09-07T13:35:41.3528984Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T13:35:41.6626937Z Collecting torch==2.7.1 2025-09-07T13:35:41.7446882Z Downloading torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) 2025-09-07T13:35:53.2893141Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 1.4 MB/s eta 0:00:00 2025-09-07T13:35:55.4691491Z Collecting nvidia-cufile-cu12==1.11.1.6 2025-09-07T13:35:55.4818053Z Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) 2025-09-07T13:35:55.4977601Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 81.8 MB/s eta 0:00:00 2025-09-07T13:35:55.5266533Z Collecting nvidia-cuda-nvrtc-cu12==12.6.77 2025-09-07T13:35:55.5371384Z Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) 2025-09-07T13:35:55.7096421Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 86.9 MB/s eta 0:00:00 2025-09-07T13:35:55.7955109Z Collecting nvidia-curand-cu12==10.3.7.77 2025-09-07T13:35:55.8093992Z Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) 2025-09-07T13:35:56.1989996Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 49.7 MB/s eta 0:00:00 2025-09-07T13:35:56.3413184Z Requirement already satisfied: typing-extensions>=4.10.0 in /home/bob/.local/lib/python3.10/site-packages (from torch==2.7.1) (4.15.0) 2025-09-07T13:35:56.3850963Z Collecting networkx 2025-09-07T13:35:56.3954391Z Downloading networkx-3.4.2-py3-none-any.whl (1.7 MB) 2025-09-07T13:35:56.4148945Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 97.4 MB/s eta 0:00:00 2025-09-07T13:35:56.4481636Z Collecting nvidia-cusparse-cu12==12.5.4.2 2025-09-07T13:35:56.4617838Z Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) 2025-09-07T13:35:58.5727845Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 8.3 MB/s eta 0:00:00 2025-09-07T13:35:59.2609539Z Collecting nvidia-cusolver-cu12==11.7.1.2 2025-09-07T13:35:59.2716752Z Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) 2025-09-07T13:36:01.9879603Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 4.8 MB/s eta 0:00:00 2025-09-07T13:36:02.5522247Z Collecting sympy>=1.13.3 2025-09-07T13:36:02.5641826Z Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB) 2025-09-07T13:36:02.6326651Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 95.4 MB/s eta 0:00:00 2025-09-07T13:36:02.7061188Z Collecting triton==3.3.1 2025-09-07T13:36:02.7181559Z Downloading triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) 2025-09-07T13:36:04.2957831Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 14.0 MB/s eta 0:00:00 2025-09-07T13:36:04.8327588Z Collecting nvidia-cublas-cu12==12.6.4.1 2025-09-07T13:36:04.8456267Z Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) 2025-09-07T13:36:09.4820501Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 3.4 MB/s eta 0:00:00 2025-09-07T13:36:10.4896111Z Collecting nvidia-nvtx-cu12==12.6.77 2025-09-07T13:36:10.5002570Z Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) 2025-09-07T13:36:10.5076232Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.3/89.3 KB 14.4 MB/s eta 0:00:00 2025-09-07T13:36:10.5370775Z Collecting nvidia-cudnn-cu12==9.5.1.17 2025-09-07T13:36:10.5496536Z Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) 2025-09-07T13:36:21.2874556Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.2 MB/s eta 0:00:00 2025-09-07T13:36:22.7361569Z Collecting nvidia-cufft-cu12==11.3.0.4 2025-09-07T13:36:22.7480980Z Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) 2025-09-07T13:36:24.6127524Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 9.5 MB/s eta 0:00:00 2025-09-07T13:36:25.1429407Z Collecting nvidia-cuda-runtime-cu12==12.6.77 2025-09-07T13:36:25.1552308Z Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) 2025-09-07T13:36:25.1735368Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 KB 55.8 MB/s eta 0:00:00 2025-09-07T13:36:25.1975664Z Collecting nvidia-cusparselt-cu12==0.6.3 2025-09-07T13:36:25.2130006Z Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) 2025-09-07T13:36:26.5161157Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 15.7 MB/s eta 0:00:00 2025-09-07T13:36:26.9562478Z Collecting fsspec 2025-09-07T13:36:26.9674450Z Downloading fsspec-2025.9.0-py3-none-any.whl (199 kB) 2025-09-07T13:36:26.9790506Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.3/199.3 KB 20.6 MB/s eta 0:00:00 2025-09-07T13:36:27.0086806Z Collecting nvidia-nvjitlink-cu12==12.6.85 2025-09-07T13:36:27.0233786Z Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) 2025-09-07T13:36:27.1644064Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 102.3 MB/s eta 0:00:00 2025-09-07T13:36:27.2555706Z Collecting filelock 2025-09-07T13:36:27.2668361Z Downloading filelock-3.19.1-py3-none-any.whl (15 kB) 2025-09-07T13:36:27.2962623Z Collecting nvidia-nccl-cu12==2.26.2 2025-09-07T13:36:27.3086496Z Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) 2025-09-07T13:36:30.7683385Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 3.9 MB/s eta 0:00:00 2025-09-07T13:36:31.4621265Z Collecting nvidia-cuda-cupti-cu12==12.6.80 2025-09-07T13:36:31.4771546Z Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) 2025-09-07T13:36:31.7293125Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 35.7 MB/s eta 0:00:00 2025-09-07T13:36:31.8762087Z Collecting jinja2 2025-09-07T13:36:31.8876429Z Downloading jinja2-3.1.6-py3-none-any.whl (134 kB) 2025-09-07T13:36:31.9968248Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.9/134.9 KB 1.2 MB/s eta 0:00:00 2025-09-07T13:36:32.0276062Z 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) 2025-09-07T13:36:32.1230719Z Collecting mpmath<1.4,>=1.1.0 2025-09-07T13:36:32.1341006Z Downloading mpmath-1.3.0-py3-none-any.whl (536 kB) 2025-09-07T13:36:32.1477004Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 46.7 MB/s eta 0:00:00 2025-09-07T13:36:32.3579014Z Collecting MarkupSafe>=2.0 2025-09-07T13:36:32.3692111Z Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) 2025-09-07T13:36:32.8260064Z 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 2025-09-07T13:36:37.5872348Z WARNING: The scripts proton and proton-viewer are installed in '/home/bob/.local/bin' which is not on PATH. 2025-09-07T13:36:37.5874153Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:36:42.1086958Z WARNING: The script isympy is installed in '/home/bob/.local/bin' which is not on PATH. 2025-09-07T13:36:42.1087839Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:37:19.2581551Z WARNING: The scripts torchfrtrace and torchrun are installed in '/home/bob/.local/bin' which is not on PATH. 2025-09-07T13:37:19.2582494Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:37:19.5703506Z 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 2025-09-07T13:37:20.1777563Z + echo DEVICE_NAME= 2025-09-07T13:37:20.1777863Z + echo DEVICE_TYPE= 2025-09-07T13:37:20.1914622Z ##[group]Run set -eux 2025-09-07T13:37:20.1914919Z set -eux 2025-09-07T13:37:20.1915146Z  2025-09-07T13:37:20.1915376Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-09-07T13:37:20.1915744Z  echo "Missing github-token input" 2025-09-07T13:37:20.1916070Z  exit 1 2025-09-07T13:37:20.1916300Z fi 2025-09-07T13:37:20.1929343Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:20.1929739Z env: 2025-09-07T13:37:20.1929962Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:20.1930303Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:20.1930786Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:20.1931393Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:20.1932051Z DEVICE_NAME: 2025-09-07T13:37:20.1932286Z DEVICE_TYPE: 2025-09-07T13:37:20.1932742Z GITHUB_TOKEN: *** 2025-09-07T13:37:20.1933266Z ##[endgroup] 2025-09-07T13:37:20.2042348Z + [[ -z *** ]] 2025-09-07T13:37:20.2248813Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-09-07T13:37:20.2249272Z with: 2025-09-07T13:37:20.2249782Z github-token: *** 2025-09-07T13:37:20.2250003Z env: 2025-09-07T13:37:20.2250217Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:20.2250563Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:20.2251029Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:20.2251618Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:20.2252125Z DEVICE_NAME: 2025-09-07T13:37:20.2252364Z DEVICE_TYPE: 2025-09-07T13:37:20.2252587Z ##[endgroup] 2025-09-07T13:37:20.2471889Z ##[group]Run set -eux 2025-09-07T13:37:20.2472214Z set -eux 2025-09-07T13:37:20.2472445Z  2025-09-07T13:37:20.2472937Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T13:37:20.2486288Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:20.2486686Z env: 2025-09-07T13:37:20.2486909Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:20.2487252Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:20.2487726Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:20.2488323Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:20.2488839Z DEVICE_NAME: 2025-09-07T13:37:20.2489070Z DEVICE_TYPE: 2025-09-07T13:37:20.2489625Z GITHUB_TOKEN: *** 2025-09-07T13:37:20.2489853Z ##[endgroup] 2025-09-07T13:37:20.2606041Z + python3 /home/bob/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525309334 i-01a21955dc3821a00-1002 2025-09-07T13:37:21.3055221Z setting job-id=49775768421 2025-09-07T13:37:21.3055821Z setting job-name=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T13:37:21.3199052Z ##[group]Run set -eux 2025-09-07T13:37:21.3199346Z set -eux 2025-09-07T13:37:21.3199577Z  2025-09-07T13:37:21.3199798Z if [[ -n "" ]]; then 2025-09-07T13:37:21.3200079Z  source "" 2025-09-07T13:37:21.3200310Z fi 2025-09-07T13:37:21.3200521Z  2025-09-07T13:37:21.3200917Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-09-07T13:37:21.3201454Z  --schema-version "${SCHEMA_VERSION}" \ 2025-09-07T13:37:21.3201800Z  --repo "${REPO}" \ 2025-09-07T13:37:21.3202113Z  --head-branch "${HEAD_BRANCH}" \ 2025-09-07T13:37:21.3202463Z  --head-sha "${HEAD_SHA}" \ 2025-09-07T13:37:21.3203037Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-09-07T13:37:21.3203412Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-09-07T13:37:21.3203734Z  --job-id "${JOB_ID}" \ 2025-09-07T13:37:21.3204040Z  --job-name "${JOB_NAME}" 2025-09-07T13:37:21.3217441Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:21.3217841Z env: 2025-09-07T13:37:21.3218053Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:21.3218396Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:21.3218859Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:21.3219466Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:21.3219979Z DEVICE_NAME: 2025-09-07T13:37:21.3220198Z DEVICE_TYPE: 2025-09-07T13:37:21.3220427Z SCHEMA_VERSION: v3 2025-09-07T13:37:21.3220691Z REPO: pytorch/pytorch 2025-09-07T13:37:21.3220961Z HEAD_BRANCH: refs/heads/main 2025-09-07T13:37:21.3221284Z HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T13:37:21.3221760Z WORKFLOW_RUN_ID: 17525309334 2025-09-07T13:37:21.3222035Z RUN_ATTEMPT: 1 2025-09-07T13:37:21.3222267Z JOB_ID: 49775768421 2025-09-07T13:37:21.3222699Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T13:37:21.3223204Z ##[endgroup] 2025-09-07T13:37:21.3258051Z + [[ -n '' ]] 2025-09-07T13:37:21.3260297Z + python3 /home/bob/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha 93fb23d6fae7c4e82c4239a1033e522088742634 --workflow-id 17525309334 --run-attempt 1 --job-id 49775768421 --job-name 'cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)' 2025-09-07T13:37:21.3695824Z ##[group]Run set -eux 2025-09-07T13:37:21.3696126Z set -eux 2025-09-07T13:37:21.3696337Z  2025-09-07T13:37:21.3696571Z if [[ -n "" ]]; then 2025-09-07T13:37:21.3696857Z  source "" 2025-09-07T13:37:21.3697082Z fi 2025-09-07T13:37:21.3697292Z  2025-09-07T13:37:21.3697694Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-09-07T13:37:21.3711109Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:21.3711501Z env: 2025-09-07T13:37:21.3711706Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:21.3712044Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:21.3712507Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:21.3713106Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:21.3713618Z DEVICE_NAME: 2025-09-07T13:37:21.3713831Z DEVICE_TYPE: 2025-09-07T13:37:21.3714052Z ##[endgroup] 2025-09-07T13:37:21.3817842Z + [[ -n '' ]] 2025-09-07T13:37:21.3818610Z + python3 /home/bob/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-09-07T13:37:22.2330867Z /home/bob/.local/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:276: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:81.) 2025-09-07T13:37:22.2332141Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-09-07T13:37:23.6308235Z ##[group]Run set -eux 2025-09-07T13:37:23.6308528Z set -eux 2025-09-07T13:37:23.6308757Z  2025-09-07T13:37:23.6308997Z # TODO (huydhn): Implement this part 2025-09-07T13:37:23.6309393Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-09-07T13:37:23.6322339Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:23.6322733Z env: 2025-09-07T13:37:23.6322959Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:23.6323306Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:23.6323987Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:23.6324600Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:23.6325113Z DEVICE_NAME: 2025-09-07T13:37:23.6325325Z DEVICE_TYPE: 2025-09-07T13:37:23.6325553Z ##[endgroup] 2025-09-07T13:37:23.6437169Z + echo 'dependencies={}' 2025-09-07T13:37:23.6790922Z ##[group]Run set -eux 2025-09-07T13:37:23.6791209Z set -eux 2025-09-07T13:37:23.6791438Z  2025-09-07T13:37:23.6791640Z if [[ -n "" ]]; then 2025-09-07T13:37:23.6791917Z  source "" 2025-09-07T13:37:23.6792156Z fi 2025-09-07T13:37:23.6792365Z  2025-09-07T13:37:23.6792619Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-09-07T13:37:23.6793075Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-09-07T13:37:23.6793595Z  # We don't want the job to fail if the directory doesn't exist 2025-09-07T13:37:23.6794019Z  exit 0 2025-09-07T13:37:23.6794377Z fi 2025-09-07T13:37:23.6794573Z  2025-09-07T13:37:23.6794813Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-09-07T13:37:23.6795307Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T13:37:23.6795884Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T13:37:23.6796309Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T13:37:23.6796667Z  --runners "${RUNNER_INFO}" \ 2025-09-07T13:37:23.6797019Z  --dependencies "${DEPENDENCIES}" \ 2025-09-07T13:37:23.6797352Z  --dry-run 2025-09-07T13:37:23.6797700Z else 2025-09-07T13:37:23.6798085Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T13:37:23.6798653Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T13:37:23.6799087Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T13:37:23.6799452Z  --runners "${RUNNER_INFO}" \ 2025-09-07T13:37:23.6799790Z  --dependencies "${DEPENDENCIES}" 2025-09-07T13:37:23.6800108Z fi 2025-09-07T13:37:23.6812472Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:23.6813008Z env: 2025-09-07T13:37:23.6813230Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:23.6813574Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:23.6814042Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:23.6814635Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:23.6815150Z DEVICE_NAME: 2025-09-07T13:37:23.6815378Z DEVICE_TYPE: 2025-09-07T13:37:23.6815634Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-09-07T13:37:23.6815941Z DRY_RUN: false 2025-09-07T13:37:23.6817463Z BENCHMARK_METADATA: {"timestamp": 1757252241, "schema_version": "v3", "name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525309334, "run_attempt": 1, "job_id": 49775768421} 2025-09-07T13:37:23.6819440Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 1121, "extra_info": {"hostname": "19cef9d253c5"}, "name": "cuda", "type": "NVIDIA A100-SXM4-40GB", "gpu_count": 1, "avail_gpu_mem_in_gb": 39}] 2025-09-07T13:37:23.6820288Z DEPENDENCIES: {} 2025-09-07T13:37:23.6820523Z ##[endgroup] 2025-09-07T13:37:23.6914410Z + [[ -n '' ]] 2025-09-07T13:37:23.6914675Z + [[ ! -d test/test-reports ]] 2025-09-07T13:37:23.6914967Z + [[ false == \t\r\u\e ]] 2025-09-07T13:37:23.6918137Z + python3 /home/bob/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757252241, "schema_version": "v3", "name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525309334, "run_attempt": 1, "job_id": 49775768421}' --runners '[{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 1121, "extra_info": {"hostname": "19cef9d253c5"}, "name": "cuda", "type": "NVIDIA A100-SXM4-40GB", "gpu_count": 1, "avail_gpu_mem_in_gb": 39}]' --dependencies '{}' 2025-09-07T13:37:23.8286421Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:23.8679723Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role 2025-09-07T13:37:24.1168674Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:24.2652495Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:24.4218083Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:24.6398156Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:24.8371859Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:37:25.0449805Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:25.2490606Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:25.4706424Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:25.6434344Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:25.8632078Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:26.0535354Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:26.2141696Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:37:26.3698577Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:37:26.5240008Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:26.7111324Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:26.8461929Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:37:27.0196215Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:27.2384678Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:37:27.4358427Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:27.6770663Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_dynamic_torchbench_amp_training_cuda_performance.json 2025-09-07T13:37:27.8700706Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:28.0299260Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:28.1926849Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json 2025-09-07T13:37:28.3700018Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json 2025-09-07T13:37:28.5532776Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:37:28.7146971Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:28.8723299Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:29.0360087Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:37:29.1916656Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:29.3479965Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_max_autotune_torchbench_amp_training_cuda_performance.json 2025-09-07T13:37:29.5185320Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:37:29.7390813Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:37:29.9281172Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:37:30.1402472Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:30.3075723Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:30.4635610Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json 2025-09-07T13:37:30.6243348Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:37:30.8091773Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:37:30.9717984Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768421/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:37:31.2137719Z ##[group]Run cat test/**/*_toprint.log || true 2025-09-07T13:37:31.2138413Z cat test/**/*_toprint.log || true 2025-09-07T13:37:31.2158380Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:31.2159014Z env: 2025-09-07T13:37:31.2159370Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:31.2159962Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:31.2160708Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:31.2161735Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:31.2162598Z DEVICE_NAME: 2025-09-07T13:37:31.2162969Z DEVICE_TYPE: 2025-09-07T13:37:31.2163332Z ##[endgroup] 2025-09-07T13:37:31.2338988Z cat: 'test/**/*_toprint.log': No such file or directory 2025-09-07T13:37:31.2583060Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-09-07T13:37:31.2583442Z kill "$MONITOR_SCRIPT_PID" 2025-09-07T13:37:31.2595332Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:31.2595840Z env: 2025-09-07T13:37:31.2596060Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:31.2596407Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:31.2596870Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:31.2597461Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:31.2597973Z DEVICE_NAME: 2025-09-07T13:37:31.2598202Z DEVICE_TYPE: 2025-09-07T13:37:31.2598438Z MONITOR_SCRIPT_PID: 9474 2025-09-07T13:37:31.2598693Z ##[endgroup] 2025-09-07T13:37:31.2922567Z Prepare all required actions 2025-09-07T13:37:31.2923356Z Getting action download info 2025-09-07T13:37:31.4498830Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T13:37:32.2997421Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-09-07T13:37:34.2153807Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-09-07T13:37:34.2154174Z with: 2025-09-07T13:37:34.2154536Z file-suffix: test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T13:37:34.2154991Z s3-bucket: gha-artifacts 2025-09-07T13:37:34.2155243Z env: 2025-09-07T13:37:34.2155446Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:34.2155772Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:34.2156213Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:34.2156846Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:34.2157347Z DEVICE_NAME: 2025-09-07T13:37:34.2157558Z DEVICE_TYPE: 2025-09-07T13:37:34.2157768Z ##[endgroup] 2025-09-07T13:37:34.2483440Z ##[group]Run # Remove any previous test jsons if they exist 2025-09-07T13:37:34.2483930Z # Remove any previous test jsons if they exist 2025-09-07T13:37:34.2484458Z rm -f test-jsons-*.zip 2025-09-07T13:37:34.2484887Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-09-07T13:37:34.2498231Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:34.2498626Z env: 2025-09-07T13:37:34.2498845Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:34.2499183Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:34.2499631Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:34.2500231Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:34.2500741Z DEVICE_NAME: 2025-09-07T13:37:34.2500979Z DEVICE_TYPE: 2025-09-07T13:37:34.2501353Z FILE_SUFFIX: test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T13:37:34.2501792Z ##[endgroup] 2025-09-07T13:37:34.2678370Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.2705576Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.2732509Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.2808967Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.2910799Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.2993010Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3030722Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.3153642Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3180698Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3295062Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3407261Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3444891Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.3462006Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3479374Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3519884Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.3545090Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3562295Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3676156Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3757384Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3861615Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.3887441Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.3914838Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3941846Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.3968069Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.3994278Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4011524Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.4036820Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.4074486Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4091639Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.4129289Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4155506Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4248394Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.4324767Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.4406409Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.4446934Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4472064Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.4497951Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4538192Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:37:34.4563536Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:37:34.4663250Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:37:34.4738719Z ##[group]Run # Remove any previous test reports if they exist 2025-09-07T13:37:34.4739228Z # Remove any previous test reports if they exist 2025-09-07T13:37:34.4739626Z rm -f test-reports-*.zip 2025-09-07T13:37:34.4740113Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-09-07T13:37:34.4753597Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:34.4753992Z env: 2025-09-07T13:37:34.4754220Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:34.4754563Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:34.4755013Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:34.4755623Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:34.4756144Z DEVICE_NAME: 2025-09-07T13:37:34.4756385Z DEVICE_TYPE: 2025-09-07T13:37:34.4756764Z FILE_SUFFIX: test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T13:37:34.4757200Z ##[endgroup] 2025-09-07T13:37:34.4875035Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T13:37:34.4876251Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4877292Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 55%) 2025-09-07T13:37:34.4878437Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 54%) 2025-09-07T13:37:34.4879486Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4880457Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4881440Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4882501Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4883619Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4884692Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 55%) 2025-09-07T13:37:34.4885672Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4886574Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4887556Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T13:37:34.4888502Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.csv (deflated 55%) 2025-09-07T13:37:34.4889491Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T13:37:34.4890542Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4891559Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.csv (deflated 54%) 2025-09-07T13:37:34.4892673Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 54%) 2025-09-07T13:37:34.4893945Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4895029Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.csv (deflated 55%) 2025-09-07T13:37:34.4896110Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 55%) 2025-09-07T13:37:34.4897178Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4898128Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4899163Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4900158Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 65%) 2025-09-07T13:37:34.4901163Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T13:37:34.4902253Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T13:37:34.4903397Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 54%) 2025-09-07T13:37:34.4904486Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4905476Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4906385Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.csv (deflated 54%) 2025-09-07T13:37:34.4907275Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4908208Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4909266Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T13:37:34.4910268Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:37:34.4911172Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4912088Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.csv (deflated 52%) 2025-09-07T13:37:34.4913032Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.csv (deflated 54%) 2025-09-07T13:37:34.4913959Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.csv (deflated 51%) 2025-09-07T13:37:34.4914954Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T13:37:34.4916071Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 54%) 2025-09-07T13:37:34.4917208Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T13:37:34.4952152Z ##[group]Run # Remove any previous usage logs if they exist 2025-09-07T13:37:34.4952640Z # Remove any previous usage logs if they exist 2025-09-07T13:37:34.4953163Z rm -f logs-*.zip 2025-09-07T13:37:34.4953512Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true 2025-09-07T13:37:34.4954054Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true 2025-09-07T13:37:34.4967370Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:34.4967770Z env: 2025-09-07T13:37:34.4967997Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:34.4968324Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:34.4968965Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:34.4969582Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:34.4970104Z DEVICE_NAME: 2025-09-07T13:37:34.4970341Z DEVICE_TYPE: 2025-09-07T13:37:34.4970722Z FILE_SUFFIX: test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T13:37:34.4971186Z ##[endgroup] 2025-09-07T13:37:34.5252248Z adding: usage_log.txt (deflated 91%) 2025-09-07T13:37:34.5269671Z 2025-09-07T13:37:34.5270072Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip) 2025-09-07T13:37:34.5375216Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-09-07T13:37:34.5375783Z # Remove any previous debugging artifacts if they exist 2025-09-07T13:37:34.5376202Z rm -f debug-*.zip 2025-09-07T13:37:34.5376478Z if [ -d 'test/debug' ]; then 2025-09-07T13:37:34.5376858Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-09-07T13:37:34.5377204Z fi 2025-09-07T13:37:34.5390599Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:34.5390999Z env: 2025-09-07T13:37:34.5391208Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:34.5391549Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:34.5392154Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:34.5392773Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:34.5393294Z DEVICE_NAME: 2025-09-07T13:37:34.5393513Z DEVICE_TYPE: 2025-09-07T13:37:34.5393893Z FILE_SUFFIX: test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421 2025-09-07T13:37:34.5394351Z ##[endgroup] 2025-09-07T13:37:34.5616027Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:37:34.5616391Z with: 2025-09-07T13:37:34.5616619Z s3-bucket: gha-artifacts 2025-09-07T13:37:34.5616972Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:34.5617319Z retention-days: 14 2025-09-07T13:37:34.5617578Z if-no-files-found: warn 2025-09-07T13:37:34.5617852Z path: test-jsons-*.zip 2025-09-07T13:37:34.5618117Z name: artifact 2025-09-07T13:37:34.5618336Z region: us-east-1 2025-09-07T13:37:34.5618576Z env: 2025-09-07T13:37:34.5618800Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:34.5619141Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:34.5619598Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:34.5620198Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:34.5620707Z DEVICE_NAME: 2025-09-07T13:37:34.5620940Z DEVICE_TYPE: 2025-09-07T13:37:34.5621147Z ##[endgroup] 2025-09-07T13:37:34.9530224Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T13:37:34.9530724Z With the provided path, there will be 1 file uploaded 2025-09-07T13:37:34.9531220Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:34.9539264Z Starting upload of test-jsons-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:35.3250152Z Finished upload of test-jsons-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:35.3529631Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:37:35.3530000Z with: 2025-09-07T13:37:35.3530213Z s3-bucket: gha-artifacts 2025-09-07T13:37:35.3530652Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:35.3531013Z retention-days: 14 2025-09-07T13:37:35.3531273Z if-no-files-found: error 2025-09-07T13:37:35.3531541Z path: test-reports-*.zip 2025-09-07T13:37:35.3531812Z name: artifact 2025-09-07T13:37:35.3532044Z region: us-east-1 2025-09-07T13:37:35.3532260Z env: 2025-09-07T13:37:35.3532470Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:35.3533013Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:35.3533670Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:35.3534279Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:35.3534778Z DEVICE_NAME: 2025-09-07T13:37:35.3535005Z DEVICE_TYPE: 2025-09-07T13:37:35.3535226Z ##[endgroup] 2025-09-07T13:37:35.6820017Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T13:37:35.6820534Z With the provided path, there will be 1 file uploaded 2025-09-07T13:37:35.6821007Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:35.6828927Z Starting upload of test-reports-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:35.8622789Z Finished upload of test-reports-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:35.8811563Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:37:35.8811909Z with: 2025-09-07T13:37:35.8812133Z s3-bucket: gha-artifacts 2025-09-07T13:37:35.8812477Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:35.8812981Z retention-days: 14 2025-09-07T13:37:35.8813240Z if-no-files-found: ignore 2025-09-07T13:37:35.8813513Z path: logs-*.zip 2025-09-07T13:37:35.8813737Z name: artifact 2025-09-07T13:37:35.8813984Z region: us-east-1 2025-09-07T13:37:35.8814210Z env: 2025-09-07T13:37:35.8814574Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:35.8814901Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:35.8815373Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:35.8815989Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:35.8816503Z DEVICE_NAME: 2025-09-07T13:37:35.8816731Z DEVICE_TYPE: 2025-09-07T13:37:35.8816940Z ##[endgroup] 2025-09-07T13:37:36.2231779Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T13:37:36.2232267Z With the provided path, there will be 1 file uploaded 2025-09-07T13:37:36.2232760Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:36.2241071Z Starting upload of logs-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:36.4414036Z Finished upload of logs-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:36.4603637Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:37:36.4604001Z with: 2025-09-07T13:37:36.4604221Z s3-bucket: gha-artifacts 2025-09-07T13:37:36.4604542Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:37:36.4604893Z retention-days: 14 2025-09-07T13:37:36.4605149Z if-no-files-found: ignore 2025-09-07T13:37:36.4605420Z path: debug-*.zip 2025-09-07T13:37:36.4605655Z name: artifact 2025-09-07T13:37:36.4605868Z region: us-east-1 2025-09-07T13:37:36.4606096Z env: 2025-09-07T13:37:36.4606304Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:36.4606644Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:36.4607097Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:36.4607712Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:36.4608225Z DEVICE_NAME: 2025-09-07T13:37:36.4608449Z DEVICE_TYPE: 2025-09-07T13:37:36.4608672Z ##[endgroup] 2025-09-07T13:37:36.8025233Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-09-07T13:37:36.8306610Z ##[group]Run # shellcheck disable=SC2156 2025-09-07T13:37:36.8306991Z # shellcheck disable=SC2156 2025-09-07T13:37:36.8307716Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-09-07T13:37:36.8321134Z shell: /usr/bin/bash -e {0} 2025-09-07T13:37:36.8321429Z env: 2025-09-07T13:37:36.8321655Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:36.8321990Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:36.8322469Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:36.8323078Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:36.8323592Z DEVICE_NAME: 2025-09-07T13:37:36.8323825Z DEVICE_TYPE: 2025-09-07T13:37:36.8324040Z ##[endgroup] 2025-09-07T13:37:37.5125422Z Prepare all required actions 2025-09-07T13:37:37.5125824Z Getting action download info 2025-09-07T13:37:37.7088749Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-09-07T13:37:37.7089129Z with: 2025-09-07T13:37:37.7089341Z job_id: 49775768421 2025-09-07T13:37:37.7089795Z job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T13:37:37.7090323Z workflow_name: inductor-A100-perf-nightly 2025-09-07T13:37:37.7090659Z workflow_run_id: 17525309334 2025-09-07T13:37:37.7090938Z workflow_attempt: 1 2025-09-07T13:37:37.7091179Z env: 2025-09-07T13:37:37.7091375Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:37.7091708Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:37.7092174Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:37.7092937Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:37.7093456Z DEVICE_NAME: 2025-09-07T13:37:37.7093727Z DEVICE_TYPE: 2025-09-07T13:37:37.7093942Z ##[endgroup] 2025-09-07T13:37:37.7233549Z ##[group]Run echo "workflow_id: 17525309334" 2025-09-07T13:37:37.7234101Z echo "workflow_id: 17525309334" 2025-09-07T13:37:37.7234438Z echo "workflow_attempt: 1" 2025-09-07T13:37:37.7234841Z echo "workflow_Name: inductor-A100-perf-nightly" 2025-09-07T13:37:37.7235242Z echo "job_id: 49775768421" 2025-09-07T13:37:37.7235782Z echo "job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)" 2025-09-07T13:37:37.7236354Z echo "artifact_prefix: " 2025-09-07T13:37:37.7236665Z python3 --version 2025-09-07T13:37:37.7249483Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:37.7249871Z env: 2025-09-07T13:37:37.7250080Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:37.7250419Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:37.7250894Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:37.7251497Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:37.7252013Z DEVICE_NAME: 2025-09-07T13:37:37.7252234Z DEVICE_TYPE: 2025-09-07T13:37:37.7252460Z ##[endgroup] 2025-09-07T13:37:37.7303999Z workflow_id: 17525309334 2025-09-07T13:37:37.7304321Z workflow_attempt: 1 2025-09-07T13:37:37.7304610Z workflow_Name: inductor-A100-perf-nightly 2025-09-07T13:37:37.7304988Z job_id: 49775768421 2025-09-07T13:37:37.7305433Z job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100) 2025-09-07T13:37:37.7305949Z artifact_prefix: 2025-09-07T13:37:37.7318940Z Python 3.10.12 2025-09-07T13:37:37.7378438Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T13:37:37.7378831Z with: 2025-09-07T13:37:37.7379121Z shell: bash 2025-09-07T13:37:37.7379503Z timeout_minutes: 5 2025-09-07T13:37:37.7379858Z max_attempts: 5 2025-09-07T13:37:37.7380146Z retry_wait_seconds: 30 2025-09-07T13:37:37.7380861Z 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 2025-09-07T13:37:37.7381598Z polling_interval_seconds: 1 2025-09-07T13:37:37.7381997Z warning_on_retry: true 2025-09-07T13:37:37.7382527Z continue_on_error: false 2025-09-07T13:37:37.7382844Z env: 2025-09-07T13:37:37.7383173Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:37.7383645Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:37.7384215Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:37.7385005Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:37.7385674Z DEVICE_NAME: 2025-09-07T13:37:37.7386004Z DEVICE_TYPE: 2025-09-07T13:37:37.7386373Z ##[endgroup] 2025-09-07T13:37:38.1249487Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T13:37:38.3481141Z Collecting python-dateutil==2.8.2 2025-09-07T13:37:38.4267392Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-09-07T13:37:38.6112965Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 247.7/247.7 KB 1.3 MB/s eta 0:00:00 2025-09-07T13:37:39.3433985Z Collecting boto3==1.35.42 2025-09-07T13:37:39.3561965Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-09-07T13:37:39.4656622Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.2/139.2 KB 1.2 MB/s eta 0:00:00 2025-09-07T13:37:39.8478285Z Collecting pandas==2.1.3 2025-09-07T13:37:39.8606143Z Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-09-07T13:37:40.6123554Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.3/12.3 MB 17.6 MB/s eta 0:00:00 2025-09-07T13:37:40.6741906Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/bob/.local/lib/python3.10/site-packages (0.6.7) 2025-09-07T13:37:40.6760288Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil==2.8.2) (1.16.0) 2025-09-07T13:37:40.6810295Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/bob/.local/lib/python3.10/site-packages (from boto3==1.35.42) (0.10.4) 2025-09-07T13:37:40.6816109Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/bob/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.0.1) 2025-09-07T13:37:40.6821529Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/bob/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.35.99) 2025-09-07T13:37:40.9155949Z Collecting pytz>=2020.1 2025-09-07T13:37:40.9281905Z Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) 2025-09-07T13:37:41.0781027Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 509.2/509.2 KB 3.4 MB/s eta 0:00:00 2025-09-07T13:37:41.6230823Z Collecting numpy<2,>=1.22.4 2025-09-07T13:37:41.6359606Z Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-09-07T13:37:42.2134509Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 21.3 MB/s eta 0:00:00 2025-09-07T13:37:42.4042904Z Collecting tzdata>=2022.1 2025-09-07T13:37:42.4171749Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-09-07T13:37:42.5357931Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 347.8/347.8 KB 2.9 MB/s eta 0:00:00 2025-09-07T13:37:42.5469895Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/bob/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-09-07T13:37:42.5475687Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/bob/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-09-07T13:37:42.5539120Z 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) 2025-09-07T13:37:42.5655419Z Requirement already satisfied: packaging>=17.0 in /home/bob/.local/lib/python3.10/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-09-07T13:37:42.5769507Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/bob/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-09-07T13:37:42.5775206Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/bob/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0) 2025-09-07T13:37:42.9070995Z Installing collected packages: pytz, tzdata, python-dateutil, numpy, pandas, boto3 2025-09-07T13:37:45.5236249Z WARNING: The script f2py is installed in '/home/bob/.local/bin' which is not on PATH. 2025-09-07T13:37:45.5249663Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:37:49.4087022Z Attempting uninstall: boto3 2025-09-07T13:37:49.4094280Z Found existing installation: boto3 1.35.33 2025-09-07T13:37:49.4287171Z Uninstalling boto3-1.35.33: 2025-09-07T13:37:49.4304976Z Successfully uninstalled boto3-1.35.33 2025-09-07T13:37:49.7008634Z 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 2025-09-07T13:37:50.8233911Z Command completed after 1 attempt(s). 2025-09-07T13:37:50.8357634Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T13:37:50.8361589Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T13:37:50.8362548Z  --workflow-run-id "17525309334" \ 2025-09-07T13:37:50.8363304Z  --workflow-name "inductor-A100-perf-nightly" \ 2025-09-07T13:37:50.8364050Z  --workflow-run-attempt "1" \ 2025-09-07T13:37:50.8364641Z  --job-id "49775768421" \ 2025-09-07T13:37:50.8365624Z  --job-name "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)" \ 2025-09-07T13:37:50.8366683Z  --local-path "" \ 2025-09-07T13:37:50.8367225Z  --artifact-prefix "" 2025-09-07T13:37:50.8387885Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:37:50.8388593Z env: 2025-09-07T13:37:50.8388993Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:37:50.8389624Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:37:50.8390479Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5228 2025-09-07T13:37:50.8391634Z DOCKER_CONTAINER_ID: 31b9433f3a80a532b1476b78acd2cbfd4e0bc02d71d5da2cfc9f9aa84f6addea 2025-09-07T13:37:50.8392587Z DEVICE_NAME: 2025-09-07T13:37:50.8392994Z DEVICE_TYPE: 2025-09-07T13:37:50.8393383Z ##[endgroup] 2025-09-07T13:37:54.3642648Z repo: pytorch/pytorch 2025-09-07T13:37:54.3643274Z Search for test log in s3 bucket: ossci-utilization 2025-09-07T13:37:54.3644231Z Downloading logs-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:54.3645689Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf-5-6-linux.aws.a100_49775768421.zip 2025-09-07T13:37:54.3646847Z Converted Log Model: UtilizationMetadata: 2025-09-07T13:37:54.3649617Z UtilizationMetadata(level='metadata', workflow_id='17525309334', job_id='49775768421', workflow_name='inductor-A100-perf-nightly', job_name='cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757235089, gpu_count=1, cpu_count=96, gpu_type='pynvml', error=None) 2025-09-07T13:37:54.3652566Z [Db Segments] detected pytest cmd: 4, generated segments: 4 2025-09-07T13:37:54.3653640Z [db model] Peek db timeseries 2025-09-07T13:37:54.3654134Z :{ 2025-09-07T13:37:54.3654475Z "created_at": 1757252273, 2025-09-07T13:37:54.3654980Z "type": "utilization", 2025-09-07T13:37:54.3655445Z "tags": [ 2025-09-07T13:37:54.3655817Z "record" 2025-09-07T13:37:54.3656150Z ], 2025-09-07T13:37:54.3656494Z "time_stamp": 1757235089, 2025-09-07T13:37:54.3656973Z "repo": "pytorch/pytorch", 2025-09-07T13:37:54.3657442Z "workflow_id": 17525309334, 2025-09-07T13:37:54.3657880Z "run_attempt": 1, 2025-09-07T13:37:54.3658282Z "job_id": 49775768421, 2025-09-07T13:37:54.3658790Z "workflow_name": "inductor-A100-perf-nightly", 2025-09-07T13:37:54.3659793Z "job_name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 5, 6, linux.aws.a100)", 2025-09-07T13:37:54.3661069Z "json_data": "{}" 2025-09-07T13:37:54.3661485Z } 2025-09-07T13:37:54.3662428Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525309334/1/49775768421/metadata 2025-09-07T13:37:54.3664194Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525309334/1/49775768421/metadata 2025-09-07T13:37:54.3666021Z Writing 1143 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525309334/1/49775768421/time_series 2025-09-07T13:37:54.3667726Z Done! 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http.https://github.com/.extraheader 2025-09-07T13:37:55.2188897Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T13:37:55.2213308Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2255151Z Entering 'third_party/ittapi' 2025-09-07T13:37:55.2279931Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2311981Z Entering 'third_party/kineto' 2025-09-07T13:37:55.2337010Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2369007Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T13:37:55.2394198Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2425818Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T13:37:55.2449854Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2486737Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T13:37:55.2511327Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2542409Z Entering 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http.https://github.com/.extraheader 2025-09-07T13:37:55.2878566Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T13:37:55.2902493Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2936029Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T13:37:55.2959598Z http.https://github.com/.extraheader 2025-09-07T13:37:55.2992235Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T13:37:55.3016923Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3050622Z Entering 'third_party/kleidiai' 2025-09-07T13:37:55.3076446Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3112590Z Entering 'third_party/mimalloc' 2025-09-07T13:37:55.3137248Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3169941Z Entering 'third_party/nlohmann' 2025-09-07T13:37:55.3195337Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3230408Z Entering 'third_party/onnx' 2025-09-07T13:37:55.3255203Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3305959Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T13:37:55.3330446Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3365901Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T13:37:55.3392862Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3426121Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T13:37:55.3449947Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3480132Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T13:37:55.3505501Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3540431Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T13:37:55.3564461Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3596269Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T13:37:55.3621393Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3655436Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T13:37:55.3680278Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3711461Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T13:37:55.3736507Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3767888Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T13:37:55.3792769Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3823711Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T13:37:55.3848301Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3884209Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T13:37:55.3908836Z http.https://github.com/.extraheader 2025-09-07T13:37:55.3945056Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T13:37:55.3969761Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4023757Z Entering 'third_party/pocketfft' 2025-09-07T13:37:55.4050677Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4082489Z Entering 'third_party/protobuf' 2025-09-07T13:37:55.4107676Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4144867Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T13:37:55.4168222Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4199116Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T13:37:55.4224946Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4259363Z Entering 'third_party/psimd' 2025-09-07T13:37:55.4284866Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4318373Z Entering 'third_party/pthreadpool' 2025-09-07T13:37:55.4343368Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4375730Z Entering 'third_party/pybind11' 2025-09-07T13:37:55.4400995Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4434499Z Entering 'third_party/python-peachpy' 2025-09-07T13:37:55.4462045Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4495970Z Entering 'third_party/sleef' 2025-09-07T13:37:55.4523591Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4557272Z Entering 'third_party/tensorpipe' 2025-09-07T13:37:55.4583721Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4616504Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T13:37:55.4641120Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4676637Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T13:37:55.4701828Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4733266Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T13:37:55.4757589Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4792509Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T13:37:55.4816569Z http.https://github.com/.extraheader 2025-09-07T13:37:55.4847642Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T13:37:55.4872406Z http.https://github.com/.extraheader 2025-09-07T13:37:55.5069565Z Post job cleanup. 2025-09-07T13:37:55.6056306Z [command]/usr/bin/git version 2025-09-07T13:37:55.6091244Z git version 2.51.0 2025-09-07T13:37:55.6131064Z Temporarily overriding HOME='/home/bob/_work/_temp/6ebac8c1-1707-441c-8086-dbbaa8a6fbfb' before making global git config changes 2025-09-07T13:37:55.6132696Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T13:37:55.6136081Z [command]/usr/bin/git config --global --add safe.directory /home/bob/_work/pytorch/pytorch 2025-09-07T13:37:55.6168279Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T13:37:55.6206920Z [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' || :" 2025-09-07T13:37:55.6439575Z Entering 'android/libs/fbjni' 2025-09-07T13:37:55.6483429Z Entering 'third_party/FP16' 2025-09-07T13:37:55.6526558Z Entering 'third_party/FXdiv' 2025-09-07T13:37:55.6569061Z Entering 'third_party/NNPACK' 2025-09-07T13:37:55.6611454Z Entering 'third_party/NVTX' 2025-09-07T13:37:55.6654638Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T13:37:55.6698360Z Entering 'third_party/XNNPACK' 2025-09-07T13:37:55.6757164Z Entering 'third_party/aiter' 2025-09-07T13:37:55.6800560Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T13:37:55.6851645Z Entering 'third_party/benchmark' 2025-09-07T13:37:55.6894925Z Entering 'third_party/composable_kernel' 2025-09-07T13:37:55.6947096Z Entering 'third_party/cpp-httplib' 2025-09-07T13:37:55.6989543Z Entering 'third_party/cpuinfo' 2025-09-07T13:37:55.7034298Z Entering 'third_party/cudnn_frontend' 2025-09-07T13:37:55.7077972Z Entering 'third_party/cutlass' 2025-09-07T13:37:55.7130226Z Entering 'third_party/fbgemm' 2025-09-07T13:37:55.7176694Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T13:37:55.7219717Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T13:37:55.7271841Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T13:37:55.7313749Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T13:37:55.7364425Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T13:37:55.7406767Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T13:37:55.7448250Z Entering 'third_party/fbgemm/external/json' 2025-09-07T13:37:55.7494036Z Entering 'third_party/flash-attention' 2025-09-07T13:37:55.7538536Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T13:37:55.7587321Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T13:37:55.7640125Z Entering 'third_party/flatbuffers' 2025-09-07T13:37:55.7686147Z Entering 'third_party/fmt' 2025-09-07T13:37:55.7729083Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T13:37:55.7771216Z Entering 'third_party/gloo' 2025-09-07T13:37:55.7814694Z Entering 'third_party/googletest' 2025-09-07T13:37:55.7857745Z Entering 'third_party/ideep' 2025-09-07T13:37:55.7899792Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T13:37:55.7950912Z Entering 'third_party/ittapi' 2025-09-07T13:37:55.7995203Z Entering 'third_party/kineto' 2025-09-07T13:37:55.8037789Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T13:37:55.8079048Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T13:37:55.8122178Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T13:37:55.8164604Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T13:37:55.8207674Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T13:37:55.8248548Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T13:37:55.8291895Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T13:37:55.8334715Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T13:37:55.8376117Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T13:37:55.8418410Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T13:37:55.8462948Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T13:37:55.8505193Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T13:37:55.8548393Z Entering 'third_party/kleidiai' 2025-09-07T13:37:55.8592292Z Entering 'third_party/mimalloc' 2025-09-07T13:37:55.8635454Z Entering 'third_party/nlohmann' 2025-09-07T13:37:55.8679749Z Entering 'third_party/onnx' 2025-09-07T13:37:55.8742202Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T13:37:55.8788821Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T13:37:55.8835672Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T13:37:55.8876959Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T13:37:55.8917673Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T13:37:55.8958600Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T13:37:55.9001306Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T13:37:55.9041389Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T13:37:55.9082721Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T13:37:55.9122941Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T13:37:55.9166930Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T13:37:55.9211134Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T13:37:55.9274735Z Entering 'third_party/pocketfft' 2025-09-07T13:37:55.9318449Z Entering 'third_party/protobuf' 2025-09-07T13:37:55.9364317Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T13:37:55.9405011Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T13:37:55.9448631Z Entering 'third_party/psimd' 2025-09-07T13:37:55.9491502Z Entering 'third_party/pthreadpool' 2025-09-07T13:37:55.9534537Z Entering 'third_party/pybind11' 2025-09-07T13:37:55.9577320Z Entering 'third_party/python-peachpy' 2025-09-07T13:37:55.9620039Z Entering 'third_party/sleef' 2025-09-07T13:37:55.9664069Z Entering 'third_party/tensorpipe' 2025-09-07T13:37:55.9706909Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T13:37:55.9747610Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T13:37:55.9788811Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T13:37:55.9830579Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T13:37:55.9870946Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T13:37:55.9945241Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T13:37:55.9963986Z [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' || :" 2025-09-07T13:37:56.0194458Z Entering 'android/libs/fbjni' 2025-09-07T13:37:56.0238582Z Entering 'third_party/FP16' 2025-09-07T13:37:56.0280766Z Entering 'third_party/FXdiv' 2025-09-07T13:37:56.0323701Z Entering 'third_party/NNPACK' 2025-09-07T13:37:56.0365516Z Entering 'third_party/NVTX' 2025-09-07T13:37:56.0408368Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T13:37:56.0451062Z Entering 'third_party/XNNPACK' 2025-09-07T13:37:56.0509727Z Entering 'third_party/aiter' 2025-09-07T13:37:56.0552818Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T13:37:56.0604617Z Entering 'third_party/benchmark' 2025-09-07T13:37:56.0647398Z Entering 'third_party/composable_kernel' 2025-09-07T13:37:56.0699070Z Entering 'third_party/cpp-httplib' 2025-09-07T13:37:56.0741643Z Entering 'third_party/cpuinfo' 2025-09-07T13:37:56.0785367Z Entering 'third_party/cudnn_frontend' 2025-09-07T13:37:56.0827837Z Entering 'third_party/cutlass' 2025-09-07T13:37:56.0879889Z Entering 'third_party/fbgemm' 2025-09-07T13:37:56.0925338Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T13:37:56.0966644Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T13:37:56.1017035Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T13:37:56.1058965Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T13:37:56.1111546Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T13:37:56.1152683Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T13:37:56.1193628Z Entering 'third_party/fbgemm/external/json' 2025-09-07T13:37:56.1237589Z Entering 'third_party/flash-attention' 2025-09-07T13:37:56.1282586Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T13:37:56.1330612Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T13:37:56.1384310Z Entering 'third_party/flatbuffers' 2025-09-07T13:37:56.1430527Z Entering 'third_party/fmt' 2025-09-07T13:37:56.1474205Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T13:37:56.1517572Z Entering 'third_party/gloo' 2025-09-07T13:37:56.1559354Z Entering 'third_party/googletest' 2025-09-07T13:37:56.1601609Z Entering 'third_party/ideep' 2025-09-07T13:37:56.1643376Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T13:37:56.1693901Z Entering 'third_party/ittapi' 2025-09-07T13:37:56.1736167Z Entering 'third_party/kineto' 2025-09-07T13:37:56.1778404Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T13:37:56.1820034Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T13:37:56.1862815Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T13:37:56.1905103Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T13:37:56.1946558Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T13:37:56.1986982Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T13:37:56.2029981Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T13:37:56.2071129Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T13:37:56.2112809Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T13:37:56.2154546Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T13:37:56.2198046Z Entering 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