2025-09-07T07:44:40.2027349Z Current runner version: '2.328.0' 2025-09-07T07:44:40.2033798Z Runner name: 'i-01a21955dc3821a00-1004' 2025-09-07T07:44:40.2034635Z Runner group name: 'default' 2025-09-07T07:44:40.2035624Z Machine name: 'c3fe6811bb8d' 2025-09-07T07:44:40.2038394Z ##[group]GITHUB_TOKEN Permissions 2025-09-07T07:44:40.2040733Z Contents: read 2025-09-07T07:44:40.2041282Z Metadata: read 2025-09-07T07:44:40.2041852Z ##[endgroup] 2025-09-07T07:44:40.2044320Z Secret source: Actions 2025-09-07T07:44:40.2045066Z Prepare workflow directory 2025-09-07T07:44:40.2575261Z Prepare all required actions 2025-09-07T07:44:40.2617475Z Getting action download info 2025-09-07T07:44:40.6879899Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd) 2025-09-07T07:44:43.6894958Z Download action repository 'pytorch/pytorch@main' (SHA:ada43ed39c80b746b4822c92640a1882619e2795) 2025-09-07T07:45:20.0941962Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-09-07T07:45:21.3733764Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-09-07T07:45:22.1037547Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-09-07T07:45:22.6133122Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T07:45:23.4534300Z Getting action download info 2025-09-07T07:45:23.5808005Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-09-07T07:45:24.4387601Z Getting action download info 2025-09-07T07:45:24.5546739Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-09-07T07:45:25.1406396Z Getting action download info 2025-09-07T07:45:25.2720246Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-09-07T07:45:25.7555803Z Getting action download info 2025-09-07T07:45:25.9035063Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634) 2025-09-07T07:45:25.9039033Z ##[group] Inputs 2025-09-07T07:45:25.9039449Z build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T07:45:25.9045734Z 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"}]} 2025-09-07T07:45:25.9052602Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:45:25.9053811Z sync-tag: 2025-09-07T07:45:25.9054688Z timeout-minutes: 1440 2025-09-07T07:45:25.9054954Z use-gha: 2025-09-07T07:45:25.9056222Z 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 2025-09-07T07:45:25.9057579Z s3-bucket: gha-artifacts 2025-09-07T07:45:25.9057867Z aws-role-to-assume: 2025-09-07T07:45:25.9058485Z disable-monitor: false 2025-09-07T07:45:25.9058829Z monitor-log-interval: 15 2025-09-07T07:45:25.9059141Z monitor-data-collect-interval: 4 2025-09-07T07:45:25.9059469Z ##[endgroup] 2025-09-07T07:45:25.9059926Z Complete job name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T07:45:25.9668841Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-09-07T07:45:25.9669604Z with: 2025-09-07T07:45:25.9670162Z github-secret: *** 2025-09-07T07:45:25.9670904Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-09-07T07:45:25.9671701Z activate-with-label: false 2025-09-07T07:45:25.9671982Z label: with-ssh 2025-09-07T07:45:25.9672222Z remove-existing-keys: true 2025-09-07T07:45:25.9672513Z fail-silently: true 2025-09-07T07:45:25.9672977Z env: 2025-09-07T07:45:25.9673206Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:25.9673465Z ##[endgroup] 2025-09-07T07:45:26.0823209Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-09-07T07:45:26.0824203Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-09-07T07:45:26.1162189Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-09-07T07:45:26.1162643Z with: 2025-09-07T07:45:26.1162873Z no-sudo: true 2025-09-07T07:45:26.1163118Z submodules: recursive 2025-09-07T07:45:26.1163383Z fetch-depth: 0 2025-09-07T07:45:26.1163606Z env: 2025-09-07T07:45:26.1163827Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:26.1164096Z ##[endgroup] 2025-09-07T07:45:26.1410271Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:26.1411295Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:26.1428921Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:45:26.1429342Z env: 2025-09-07T07:45:26.1429567Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:26.1429829Z ##[endgroup] 2025-09-07T07:45:26.1712051Z ##[group]Run actions/checkout@v4 2025-09-07T07:45:26.1712358Z with: 2025-09-07T07:45:26.1712613Z ref: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:45:26.1712959Z fetch-depth: 0 2025-09-07T07:45:26.1713205Z submodules: recursive 2025-09-07T07:45:26.1713463Z show-progress: false 2025-09-07T07:45:26.1713734Z repository: pytorch/pytorch 2025-09-07T07:45:26.1714157Z token: *** 2025-09-07T07:45:26.1714387Z ssh-strict: true 2025-09-07T07:45:26.1714626Z ssh-user: git 2025-09-07T07:45:26.1714859Z persist-credentials: true 2025-09-07T07:45:26.1715133Z clean: true 2025-09-07T07:45:26.1715385Z sparse-checkout-cone-mode: true 2025-09-07T07:45:26.1715689Z fetch-tags: false 2025-09-07T07:45:26.1715918Z lfs: false 2025-09-07T07:45:26.1716152Z set-safe-directory: true 2025-09-07T07:45:26.1716646Z env: 2025-09-07T07:45:26.1716931Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:26.1717184Z ##[endgroup] 2025-09-07T07:45:26.2754031Z Syncing repository: pytorch/pytorch 2025-09-07T07:45:26.2755422Z ##[group]Getting Git version info 2025-09-07T07:45:26.2755854Z Working directory is '/home/david/_work/pytorch/pytorch' 2025-09-07T07:45:26.2756462Z [command]/usr/bin/git version 2025-09-07T07:45:26.2756788Z git version 2.51.0 2025-09-07T07:45:26.2778335Z ##[endgroup] 2025-09-07T07:45:26.2789905Z Temporarily overriding HOME='/home/david/_work/_temp/902b80d3-b5f4-4bad-80c3-a33cfb6630ec' before making global git config changes 2025-09-07T07:45:26.2790846Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T07:45:26.2795004Z [command]/usr/bin/git config --global --add safe.directory /home/david/_work/pytorch/pytorch 2025-09-07T07:45:26.2829133Z Deleting the contents of '/home/david/_work/pytorch/pytorch' 2025-09-07T07:45:26.2832063Z ##[group]Initializing the repository 2025-09-07T07:45:26.2835180Z [command]/usr/bin/git init /home/david/_work/pytorch/pytorch 2025-09-07T07:45:26.2979405Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-09-07T07:45:26.2980080Z hint: is subject to change. To configure the initial branch name to use in all 2025-09-07T07:45:26.2980679Z hint: of your new repositories, which will suppress this warning, call: 2025-09-07T07:45:26.2981096Z hint: 2025-09-07T07:45:26.2981406Z hint: git config --global init.defaultBranch 2025-09-07T07:45:26.2981770Z hint: 2025-09-07T07:45:26.2982115Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-09-07T07:45:26.2982690Z hint: 'development'. The just-created branch can be renamed via this command: 2025-09-07T07:45:26.2983141Z hint: 2025-09-07T07:45:26.2983370Z hint: git branch -m 2025-09-07T07:45:26.2983638Z hint: 2025-09-07T07:45:26.2984002Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-09-07T07:45:26.2984735Z Initialized empty Git repository in /home/david/_work/pytorch/pytorch/.git/ 2025-09-07T07:45:26.2989116Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-09-07T07:45:26.3026674Z ##[endgroup] 2025-09-07T07:45:26.3027134Z ##[group]Disabling automatic garbage collection 2025-09-07T07:45:26.3029879Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:45:26.3054853Z ##[endgroup] 2025-09-07T07:45:26.3055247Z ##[group]Setting up auth 2025-09-07T07:45:26.3061025Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:45:26.3086353Z [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' || :" 2025-09-07T07:45:26.3293657Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T07:45:26.3318070Z [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' || :" 2025-09-07T07:45:26.3521967Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:45:26.3552792Z ##[endgroup] 2025-09-07T07:45:26.3553233Z ##[group]Fetching the repository 2025-09-07T07:45:26.3560159Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:46:41.3137025Z From https://github.com/pytorch/pytorch 2025-09-07T07:46:41.3137685Z * [new branch] 160583 -> origin/160583 2025-09-07T07:46:41.3138322Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-09-07T07:46:41.3138946Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-09-07T07:46:41.3139677Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-09-07T07:46:41.3143490Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-09-07T07:46:41.3144252Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-09-07T07:46:41.3145159Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-09-07T07:46:41.3145953Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-09-07T07:46:41.3146625Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-09-07T07:46:41.3147524Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-09-07T07:46:41.3148194Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-09-07T07:46:41.3148876Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-09-07T07:46:41.3149536Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-09-07T07:46:41.3150225Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-09-07T07:46:41.3150887Z * [new branch] VLA_exp -> origin/VLA_exp 2025-09-07T07:46:41.3151540Z * [new branch] actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor 2025-09-07T07:46:41.3152363Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-09-07T07:46:41.3153151Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-09-07T07:46:41.3153861Z * [new branch] add-vllm-nightly-build -> origin/add-vllm-nightly-build 2025-09-07T07:46:41.3154562Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-09-07T07:46:41.3155192Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-09-07T07:46:41.3155795Z * [new branch] addsimde -> origin/addsimde 2025-09-07T07:46:41.3156591Z * [new branch] addvllmtest -> origin/addvllmtest 2025-09-07T07:46:41.3157218Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-09-07T07:46:41.3157775Z * [new branch] adi/test -> origin/adi/test 2025-09-07T07:46:41.3158361Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-09-07T07:46:41.3158977Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-09-07T07:46:41.3159620Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-09-07T07:46:41.3160395Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-09-07T07:46:41.3161051Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-09-07T07:46:41.3161704Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-09-07T07:46:41.3162393Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-09-07T07:46:41.3163085Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-09-07T07:46:41.3163740Z * [new branch] alt-disable -> origin/alt-disable 2025-09-07T07:46:41.3164398Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-09-07T07:46:41.3165155Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-09-07T07:46:41.3165839Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-09-07T07:46:41.3166500Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-09-07T07:46:41.3167421Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-09-07T07:46:41.3168168Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-09-07T07:46:41.3168869Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-09-07T07:46:41.3169568Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-09-07T07:46:41.3170253Z * [new branch] angelayi/fake_cache_empty -> origin/angelayi/fake_cache_empty 2025-09-07T07:46:41.3170986Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-09-07T07:46:41.3171623Z * [new branch] angelayi/item -> origin/angelayi/item 2025-09-07T07:46:41.3172264Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-09-07T07:46:41.3173271Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-09-07T07:46:41.3173925Z * [new branch] angelayi/pattern -> origin/angelayi/pattern 2025-09-07T07:46:41.3216059Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-09-07T07:46:41.3216720Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-09-07T07:46:41.3217434Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-09-07T07:46:41.3218108Z * [new branch] 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2025-09-07T07:46:41.4840461Z * [new branch] xmfan/ca_fix_polyfills -> origin/xmfan/ca_fix_polyfills 2025-09-07T07:46:41.4840734Z * [new branch] xmfan/ca_jan3 -> origin/xmfan/ca_jan3 2025-09-07T07:46:41.4840946Z * [new branch] xmfan/ca_jun18 -> origin/xmfan/ca_jun18 2025-09-07T07:46:41.4841140Z * [new branch] xmfan/ca_jun24 -> origin/xmfan/ca_jun24 2025-09-07T07:46:41.4841362Z * [new branch] xmfan/ca_mem_base -> origin/xmfan/ca_mem_base 2025-09-07T07:46:41.4841567Z * [new branch] xmfan/ca_mem_fix -> origin/xmfan/ca_mem_fix 2025-09-07T07:46:41.4841784Z * [new branch] xmfan/ca_memory_fix -> origin/xmfan/ca_memory_fix 2025-09-07T07:46:41.4842046Z * [new branch] xmfan/ca_memory_fix_rebased -> origin/xmfan/ca_memory_fix_rebased 2025-09-07T07:46:41.4842305Z * [new branch] xmfan/ca_memory_fix_rebased2 -> origin/xmfan/ca_memory_fix_rebased2 2025-09-07T07:46:41.4842543Z * [new branch] xmfan/ca_move_to_cuda -> origin/xmfan/ca_move_to_cuda 2025-09-07T07:46:41.4842748Z * [new branch] xmfan/ca_nested -> origin/xmfan/ca_nested 2025-09-07T07:46:41.4842963Z * [new branch] xmfan/ca_overhead -> origin/xmfan/ca_overhead 2025-09-07T07:46:41.4843243Z * [new branch] xmfan/ca_overhead_0eba7e5451 -> origin/xmfan/ca_overhead_0eba7e5451 2025-09-07T07:46:41.4843445Z * [new branch] xmfan/ca_scalar -> origin/xmfan/ca_scalar 2025-09-07T07:46:41.4843706Z * [new branch] xmfan/ca_subclass_mem_fix -> origin/xmfan/ca_subclass_mem_fix 2025-09-07T07:46:41.4843916Z * [new branch] xmfan/ca_warm_mem -> origin/xmfan/ca_warm_mem 2025-09-07T07:46:41.4844158Z * [new branch] xmfan/ca_warm_mem_base -> origin/xmfan/ca_warm_mem_base 2025-09-07T07:46:41.4844366Z * [new branch] xmfan/cacu_jun18 -> origin/xmfan/cacu_jun18 2025-09-07T07:46:41.4844576Z * [new branch] xmfan/cacu_jun19 -> origin/xmfan/cacu_jun19 2025-09-07T07:46:41.4844794Z * [new branch] xmfan/cacu_jun4 -> origin/xmfan/cacu_jun4 2025-09-07T07:46:41.4845083Z * [new branch] xmfan/cacu_may27 -> origin/xmfan/cacu_may27 2025-09-07T07:46:41.4845350Z * [new branch] xmfan/disable_duck_shape -> origin/xmfan/disable_duck_shape 2025-09-07T07:46:41.4845640Z * [new branch] xmfan/fca_cpp_node_passthrough -> origin/xmfan/fca_cpp_node_passthrough 2025-09-07T07:46:41.4845855Z * [new branch] xmfan/issue_123374 -> origin/xmfan/issue_123374 2025-09-07T07:46:41.4846326Z * [new branch] xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T07:46:41.4846773Z * [new branch] xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T07:46:41.4847014Z * [new branch] xmfan/segfault_test -> origin/xmfan/segfault_test 2025-09-07T07:46:41.4847230Z * [new branch] xmfan/single_step -> origin/xmfan/single_step 2025-09-07T07:46:41.4847445Z * [new branch] xmfan/sth_0829 -> origin/xmfan/sth_0829 2025-09-07T07:46:41.4847631Z * [new branch] xmfan/test -> origin/xmfan/test 2025-09-07T07:46:41.4847888Z * [new branch] yguo/debug-0226-constexpr -> origin/yguo/debug-0226-constexpr 2025-09-07T07:46:41.4848135Z * [new branch] yguo/new_latest_changes -> origin/yguo/new_latest_changes 2025-09-07T07:46:41.4848414Z * [new branch] yguo/patch_constexpr_changes -> origin/yguo/patch_constexpr_changes 2025-09-07T07:46:41.4848647Z * [new branch] yihan_quantization -> origin/yihan_quantization 2025-09-07T07:46:41.4848928Z * [new branch] yiming/add_jit_trace_benchmark -> origin/yiming/add_jit_trace_benchmark 2025-09-07T07:46:41.4849317Z * [new branch] yiming/add_nativert_benchmark -> origin/yiming/add_nativert_benchmark 2025-09-07T07:46:41.4849532Z * [new branch] yiming/bootcamp -> origin/yiming/bootcamp 2025-09-07T07:46:41.4849752Z * [new branch] zainr/canary-test -> origin/zainr/canary-test 2025-09-07T07:46:41.4850037Z * [new branch] zainr/cleanup-gh-runners -> origin/zainr/cleanup-gh-runners 2025-09-07T07:46:41.4850251Z * [new branch] zainr/git-push-v2 -> origin/zainr/git-push-v2 2025-09-07T07:46:41.4850513Z * [new branch] zainr/pull-migration-c -> origin/zainr/pull-migration-c 2025-09-07T07:46:41.4850699Z * [new branch] zainr/test -> origin/zainr/test 2025-09-07T07:46:41.4850901Z * [new branch] zainr/test2 -> origin/zainr/test2 2025-09-07T07:46:41.4851103Z * [new branch] zainr/unstable -> origin/zainr/unstable 2025-09-07T07:46:41.4851329Z * [new branch] zainr/unstable-xla -> origin/zainr/unstable-xla 2025-09-07T07:46:41.4851569Z * [new branch] zasdfgbnm-patch-3 -> origin/zasdfgbnm-patch-3 2025-09-07T07:46:41.4851735Z * [new branch] zb2p -> origin/zb2p 2025-09-07T07:46:41.4851984Z * [new branch] zero_grad_optimization -> origin/zero_grad_optimization 2025-09-07T07:46:41.4852234Z * [new branch] zeros-and-scatter-part2 -> origin/zeros-and-scatter-part2 2025-09-07T07:46:41.4852458Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-09-07T07:46:41.4852707Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-09-07T07:46:41.4853037Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-09-07T07:46:41.4853553Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-09-07T07:46:41.4853735Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-09-07T07:46:41.4854039Z * [new tag] ciflow/binaries/156049 -> ciflow/binaries/156049 2025-09-07T07:46:41.4854232Z * [new tag] ciflow/binaries/156712 -> ciflow/binaries/156712 2025-09-07T07:46:41.4854425Z * [new tag] ciflow/binaries/157432 -> ciflow/binaries/157432 2025-09-07T07:46:41.4854628Z * [new tag] ciflow/binaries/157685 -> ciflow/binaries/157685 2025-09-07T07:46:41.4854820Z * [new tag] ciflow/binaries/157689 -> ciflow/binaries/157689 2025-09-07T07:46:41.4855025Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-09-07T07:46:41.4855216Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-09-07T07:46:41.4855410Z * [new tag] ciflow/binaries/160720 -> ciflow/binaries/160720 2025-09-07T07:46:41.4855615Z * [new tag] ciflow/binaries/162080 -> ciflow/binaries/162080 2025-09-07T07:46:41.4855810Z * [new tag] ciflow/binaries/162329 -> ciflow/binaries/162329 2025-09-07T07:46:41.4856086Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-09-07T07:46:41.4856335Z * [new tag] ciflow/binaries_libtorch/156711 -> ciflow/binaries_libtorch/156711 2025-09-07T07:46:41.4856596Z * [new tag] ciflow/binaries_libtorch/157432 -> ciflow/binaries_libtorch/157432 2025-09-07T07:46:41.4856816Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-09-07T07:46:41.4857038Z * [new tag] ciflow/binaries_wheel/156711 -> ciflow/binaries_wheel/156711 2025-09-07T07:46:41.4857266Z * [new tag] ciflow/binaries_wheel/157432 -> ciflow/binaries_wheel/157432 2025-09-07T07:46:41.4857582Z * [new tag] ciflow/binaries_wheel/162136 -> ciflow/binaries_wheel/162136 2025-09-07T07:46:41.4857817Z * [new tag] ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252 2025-09-07T07:46:41.4858034Z * [new tag] ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325 2025-09-07T07:46:41.4858287Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-09-07T07:46:41.4858498Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-09-07T07:46:41.4858704Z * [new tag] ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984 2025-09-07T07:46:41.4858922Z * [new tag] ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003 2025-09-07T07:46:41.4859126Z * [new tag] ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011 2025-09-07T07:46:41.4859345Z * [new tag] ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026 2025-09-07T07:46:41.4859555Z * [new tag] ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033 2025-09-07T07:46:41.4859763Z * [new tag] ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040 2025-09-07T07:46:41.4859985Z * [new tag] ciflow/h100-symm-mem/162041 -> ciflow/h100-symm-mem/162041 2025-09-07T07:46:41.4860190Z * [new tag] ciflow/h100-symm-mem/162142 -> ciflow/h100-symm-mem/162142 2025-09-07T07:46:41.4860409Z * [new tag] ciflow/h100-symm-mem/162150 -> ciflow/h100-symm-mem/162150 2025-09-07T07:46:41.4860611Z * [new tag] ciflow/h100-symm-mem/162243 -> ciflow/h100-symm-mem/162243 2025-09-07T07:46:41.4860827Z * [new tag] ciflow/h100-symm-mem/162320 -> ciflow/h100-symm-mem/162320 2025-09-07T07:46:41.4860995Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-09-07T07:46:41.4861164Z * [new tag] ciflow/h100/160480 -> ciflow/h100/160480 2025-09-07T07:46:41.4861341Z * [new tag] ciflow/h100/161749 -> ciflow/h100/161749 2025-09-07T07:46:41.4861585Z * [new tag] ciflow/h100/162022 -> ciflow/h100/162022 2025-09-07T07:46:41.4861763Z * [new tag] ciflow/h100/162278 -> ciflow/h100/162278 2025-09-07T07:46:41.4862167Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592 2025-09-07T07:46:41.4862525Z * [new tag] ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592 2025-09-07T07:46:41.4862787Z * [new tag] ciflow/inductor-periodic/162063 -> ciflow/inductor-periodic/162063 2025-09-07T07:46:41.4863044Z * [new tag] ciflow/inductor-periodic/162227 -> ciflow/inductor-periodic/162227 2025-09-07T07:46:41.4863311Z * [new tag] ciflow/inductor-periodic/162323 -> ciflow/inductor-periodic/162323 2025-09-07T07:46:41.4863529Z * [new tag] ciflow/inductor-rocm/154170 -> ciflow/inductor-rocm/154170 2025-09-07T07:46:41.4863761Z * [new tag] ciflow/inductor-rocm/159146 -> ciflow/inductor-rocm/159146 2025-09-07T07:46:41.4863973Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-09-07T07:46:41.4864184Z * [new tag] ciflow/inductor-rocm/161715 -> ciflow/inductor-rocm/161715 2025-09-07T07:46:41.4864414Z * [new tag] ciflow/inductor-rocm/162053 -> ciflow/inductor-rocm/162053 2025-09-07T07:46:41.4864626Z * [new tag] ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056 2025-09-07T07:46:41.4864907Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-09-07T07:46:41.4865109Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-09-07T07:46:41.4865312Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-09-07T07:46:41.4865600Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-09-07T07:46:41.4865796Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-09-07T07:46:41.4865998Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-09-07T07:46:41.4866189Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-09-07T07:46:41.4866395Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-09-07T07:46:41.4866584Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-09-07T07:46:41.4866775Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-09-07T07:46:41.4866978Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-09-07T07:46:41.4867168Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-09-07T07:46:41.4867375Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-09-07T07:46:41.4867567Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-09-07T07:46:41.4867768Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-09-07T07:46:41.4867954Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-09-07T07:46:41.4868145Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-09-07T07:46:41.4868347Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-09-07T07:46:41.4868535Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-09-07T07:46:41.4868738Z * [new tag] ciflow/inductor/158647 -> ciflow/inductor/158647 2025-09-07T07:46:41.4868929Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-09-07T07:46:41.4869135Z * [new tag] ciflow/inductor/159146 -> ciflow/inductor/159146 2025-09-07T07:46:41.4869425Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-09-07T07:46:41.4869618Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-09-07T07:46:41.4869824Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-09-07T07:46:41.4870015Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-09-07T07:46:41.4870221Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-09-07T07:46:41.4870411Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-09-07T07:46:41.4870603Z * [new tag] ciflow/inductor/160161 -> ciflow/inductor/160161 2025-09-07T07:46:41.4870809Z * [new tag] ciflow/inductor/160174 -> ciflow/inductor/160174 2025-09-07T07:46:41.4871006Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-09-07T07:46:41.4871211Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-09-07T07:46:41.4871406Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-09-07T07:46:41.4871612Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-09-07T07:46:41.4871801Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-09-07T07:46:41.4871991Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-09-07T07:46:41.4872194Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-09-07T07:46:41.4872383Z * [new tag] ciflow/inductor/160480 -> ciflow/inductor/160480 2025-09-07T07:46:41.4872587Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-09-07T07:46:41.4872859Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-09-07T07:46:41.4873050Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-09-07T07:46:41.4873252Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-09-07T07:46:41.4873445Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-09-07T07:46:41.4873647Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-09-07T07:46:41.4873834Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-09-07T07:46:41.4874039Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-09-07T07:46:41.4874227Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-09-07T07:46:41.4874416Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-09-07T07:46:41.4874618Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-09-07T07:46:41.4874807Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-09-07T07:46:41.4875015Z * [new tag] ciflow/inductor/160843 -> ciflow/inductor/160843 2025-09-07T07:46:41.4875203Z * [new tag] ciflow/inductor/160869 -> ciflow/inductor/160869 2025-09-07T07:46:41.4875397Z * [new tag] ciflow/inductor/160920 -> ciflow/inductor/160920 2025-09-07T07:46:41.4875595Z * [new tag] ciflow/inductor/160928 -> ciflow/inductor/160928 2025-09-07T07:46:41.4875783Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-09-07T07:46:41.4875989Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-09-07T07:46:41.4876175Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-09-07T07:46:41.4876375Z * [new tag] ciflow/inductor/161109 -> ciflow/inductor/161109 2025-09-07T07:46:41.4876565Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-09-07T07:46:41.4876838Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-09-07T07:46:41.4877042Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-09-07T07:46:41.4877231Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-09-07T07:46:41.4877433Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-09-07T07:46:41.4877618Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-09-07T07:46:41.4877807Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-09-07T07:46:41.4878007Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-09-07T07:46:41.4878200Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-09-07T07:46:41.4878409Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-09-07T07:46:41.4878603Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-09-07T07:46:41.4878809Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-09-07T07:46:41.4879001Z * [new tag] ciflow/inductor/161442 -> ciflow/inductor/161442 2025-09-07T07:46:41.4879190Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-09-07T07:46:41.4879389Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-09-07T07:46:41.4879579Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-09-07T07:46:41.4879782Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-09-07T07:46:41.4879970Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-09-07T07:46:41.4880244Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-09-07T07:46:41.4880447Z * [new tag] ciflow/inductor/161595 -> ciflow/inductor/161595 2025-09-07T07:46:41.4880639Z * [new tag] ciflow/inductor/161596 -> ciflow/inductor/161596 2025-09-07T07:46:41.4880841Z * [new tag] ciflow/inductor/161630 -> ciflow/inductor/161630 2025-09-07T07:46:41.4881031Z * [new tag] ciflow/inductor/161667 -> ciflow/inductor/161667 2025-09-07T07:46:41.4881236Z * [new tag] ciflow/inductor/161670 -> ciflow/inductor/161670 2025-09-07T07:46:41.4881424Z * [new tag] ciflow/inductor/161673 -> ciflow/inductor/161673 2025-09-07T07:46:41.4881615Z * [new tag] ciflow/inductor/161674 -> ciflow/inductor/161674 2025-09-07T07:46:41.4881818Z * [new tag] ciflow/inductor/161675 -> ciflow/inductor/161675 2025-09-07T07:46:41.4882012Z * [new tag] ciflow/inductor/161693 -> ciflow/inductor/161693 2025-09-07T07:46:41.4882222Z * [new tag] ciflow/inductor/161695 -> ciflow/inductor/161695 2025-09-07T07:46:41.4882410Z * [new tag] ciflow/inductor/161715 -> ciflow/inductor/161715 2025-09-07T07:46:41.4882600Z * [new tag] ciflow/inductor/161730 -> ciflow/inductor/161730 2025-09-07T07:46:41.4882797Z * [new tag] ciflow/inductor/161732 -> ciflow/inductor/161732 2025-09-07T07:46:41.4882988Z * [new tag] ciflow/inductor/161744 -> ciflow/inductor/161744 2025-09-07T07:46:41.4883190Z * [new tag] ciflow/inductor/161746 -> ciflow/inductor/161746 2025-09-07T07:46:41.4883378Z * [new tag] ciflow/inductor/161747 -> ciflow/inductor/161747 2025-09-07T07:46:41.4883584Z * [new tag] ciflow/inductor/161819 -> ciflow/inductor/161819 2025-09-07T07:46:41.4883776Z * [new tag] ciflow/inductor/161821 -> ciflow/inductor/161821 2025-09-07T07:46:41.4883970Z * [new tag] ciflow/inductor/161828 -> ciflow/inductor/161828 2025-09-07T07:46:41.4884253Z * [new tag] ciflow/inductor/161879 -> ciflow/inductor/161879 2025-09-07T07:46:41.4884445Z * [new tag] ciflow/inductor/161880 -> ciflow/inductor/161880 2025-09-07T07:46:41.4884650Z * [new tag] ciflow/inductor/161881 -> ciflow/inductor/161881 2025-09-07T07:46:41.4884840Z * [new tag] ciflow/inductor/161907 -> ciflow/inductor/161907 2025-09-07T07:46:41.4885029Z * [new tag] ciflow/inductor/161914 -> ciflow/inductor/161914 2025-09-07T07:46:41.4885230Z * [new tag] ciflow/inductor/161924 -> ciflow/inductor/161924 2025-09-07T07:46:41.4885418Z * [new tag] ciflow/inductor/161936 -> ciflow/inductor/161936 2025-09-07T07:46:41.4885624Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-09-07T07:46:41.4885813Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-09-07T07:46:41.4886020Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-09-07T07:46:41.4886208Z * [new tag] ciflow/inductor/161955 -> ciflow/inductor/161955 2025-09-07T07:46:41.4886396Z * [new tag] ciflow/inductor/161957 -> ciflow/inductor/161957 2025-09-07T07:46:41.4886594Z * [new tag] ciflow/inductor/161975 -> ciflow/inductor/161975 2025-09-07T07:46:41.4886783Z * [new tag] ciflow/inductor/161977 -> ciflow/inductor/161977 2025-09-07T07:46:41.4886984Z * [new tag] ciflow/inductor/161978 -> ciflow/inductor/161978 2025-09-07T07:46:41.4887173Z * [new tag] ciflow/inductor/161979 -> ciflow/inductor/161979 2025-09-07T07:46:41.4887456Z * [new tag] ciflow/inductor/161980 -> ciflow/inductor/161980 2025-09-07T07:46:41.4887645Z * [new tag] ciflow/inductor/161988 -> ciflow/inductor/161988 2025-09-07T07:46:41.4887841Z * [new tag] ciflow/inductor/161994 -> ciflow/inductor/161994 2025-09-07T07:46:41.4888041Z * [new tag] ciflow/inductor/162013 -> ciflow/inductor/162013 2025-09-07T07:46:41.4888233Z * [new tag] ciflow/inductor/162014 -> ciflow/inductor/162014 2025-09-07T07:46:41.4888435Z * [new tag] ciflow/inductor/162017 -> ciflow/inductor/162017 2025-09-07T07:46:41.4888623Z * [new tag] ciflow/inductor/162021 -> ciflow/inductor/162021 2025-09-07T07:46:41.4888817Z * [new tag] ciflow/inductor/162023 -> ciflow/inductor/162023 2025-09-07T07:46:41.4889020Z * [new tag] ciflow/inductor/162027 -> ciflow/inductor/162027 2025-09-07T07:46:41.4889212Z * [new tag] ciflow/inductor/162029 -> ciflow/inductor/162029 2025-09-07T07:46:41.4889422Z * [new tag] ciflow/inductor/162030 -> ciflow/inductor/162030 2025-09-07T07:46:41.4889619Z * [new tag] ciflow/inductor/162031 -> ciflow/inductor/162031 2025-09-07T07:46:41.4889822Z * [new tag] ciflow/inductor/162033 -> ciflow/inductor/162033 2025-09-07T07:46:41.4890011Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-09-07T07:46:41.4890200Z * [new tag] ciflow/inductor/162053 -> ciflow/inductor/162053 2025-09-07T07:46:41.4890400Z * [new tag] ciflow/inductor/162056 -> ciflow/inductor/162056 2025-09-07T07:46:41.4890590Z * [new tag] ciflow/inductor/162063 -> ciflow/inductor/162063 2025-09-07T07:46:41.4890794Z * [new tag] ciflow/inductor/162066 -> ciflow/inductor/162066 2025-09-07T07:46:41.4890988Z * [new tag] ciflow/inductor/162068 -> ciflow/inductor/162068 2025-09-07T07:46:41.4891183Z * [new tag] ciflow/inductor/162081 -> ciflow/inductor/162081 2025-09-07T07:46:41.4891461Z * [new tag] ciflow/inductor/162088 -> ciflow/inductor/162088 2025-09-07T07:46:41.4891656Z * [new tag] ciflow/inductor/162089 -> ciflow/inductor/162089 2025-09-07T07:46:41.4891858Z * [new tag] ciflow/inductor/162094 -> ciflow/inductor/162094 2025-09-07T07:46:41.4892048Z * [new tag] ciflow/inductor/162098 -> ciflow/inductor/162098 2025-09-07T07:46:41.4892251Z * [new tag] ciflow/inductor/162101 -> ciflow/inductor/162101 2025-09-07T07:46:41.4892444Z * [new tag] ciflow/inductor/162102 -> ciflow/inductor/162102 2025-09-07T07:46:41.4892634Z * [new tag] ciflow/inductor/162104 -> ciflow/inductor/162104 2025-09-07T07:46:41.4893020Z * [new tag] ciflow/inductor/162106 -> ciflow/inductor/162106 2025-09-07T07:46:41.4893221Z * [new tag] ciflow/inductor/162108 -> ciflow/inductor/162108 2025-09-07T07:46:41.4893429Z * [new tag] ciflow/inductor/162126 -> ciflow/inductor/162126 2025-09-07T07:46:41.4893621Z * [new tag] ciflow/inductor/162149 -> ciflow/inductor/162149 2025-09-07T07:46:41.4893812Z * [new tag] ciflow/inductor/162164 -> ciflow/inductor/162164 2025-09-07T07:46:41.4894016Z * [new tag] ciflow/inductor/162166 -> ciflow/inductor/162166 2025-09-07T07:46:41.4894210Z * [new tag] ciflow/inductor/162169 -> ciflow/inductor/162169 2025-09-07T07:46:41.4894413Z * [new tag] ciflow/inductor/162170 -> ciflow/inductor/162170 2025-09-07T07:46:41.4894605Z * [new tag] ciflow/inductor/162171 -> ciflow/inductor/162171 2025-09-07T07:46:41.4894807Z * [new tag] ciflow/inductor/162183 -> ciflow/inductor/162183 2025-09-07T07:46:41.4895119Z * [new tag] ciflow/inductor/162189 -> ciflow/inductor/162189 2025-09-07T07:46:41.4895317Z * [new tag] ciflow/inductor/162190 -> ciflow/inductor/162190 2025-09-07T07:46:41.4895523Z * [new tag] ciflow/inductor/162191 -> ciflow/inductor/162191 2025-09-07T07:46:41.4895712Z * [new tag] ciflow/inductor/162194 -> ciflow/inductor/162194 2025-09-07T07:46:41.4895912Z * [new tag] ciflow/inductor/162200 -> ciflow/inductor/162200 2025-09-07T07:46:41.4896104Z * [new tag] ciflow/inductor/162201 -> ciflow/inductor/162201 2025-09-07T07:46:41.4896294Z * [new tag] ciflow/inductor/162208 -> ciflow/inductor/162208 2025-09-07T07:46:41.4896493Z * [new tag] ciflow/inductor/162211 -> ciflow/inductor/162211 2025-09-07T07:46:41.4896682Z * [new tag] ciflow/inductor/162216 -> ciflow/inductor/162216 2025-09-07T07:46:41.4896882Z * [new tag] ciflow/inductor/162220 -> ciflow/inductor/162220 2025-09-07T07:46:41.4897075Z * [new tag] ciflow/inductor/162222 -> ciflow/inductor/162222 2025-09-07T07:46:41.4897282Z * [new tag] ciflow/inductor/162227 -> ciflow/inductor/162227 2025-09-07T07:46:41.4897473Z * [new tag] ciflow/inductor/162238 -> ciflow/inductor/162238 2025-09-07T07:46:41.4897662Z * [new tag] ciflow/inductor/162239 -> ciflow/inductor/162239 2025-09-07T07:46:41.4897865Z * [new tag] ciflow/inductor/162240 -> ciflow/inductor/162240 2025-09-07T07:46:41.4898053Z * [new tag] ciflow/inductor/162244 -> ciflow/inductor/162244 2025-09-07T07:46:41.4898251Z * [new tag] ciflow/inductor/162245 -> ciflow/inductor/162245 2025-09-07T07:46:41.4898439Z * [new tag] ciflow/inductor/162262 -> ciflow/inductor/162262 2025-09-07T07:46:41.4898633Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-09-07T07:46:41.4898833Z * [new tag] ciflow/inductor/162278 -> ciflow/inductor/162278 2025-09-07T07:46:41.4899118Z * [new tag] ciflow/inductor/162284 -> ciflow/inductor/162284 2025-09-07T07:46:41.4899318Z * [new tag] ciflow/inductor/162286 -> ciflow/inductor/162286 2025-09-07T07:46:41.4899508Z * [new tag] ciflow/inductor/162288 -> ciflow/inductor/162288 2025-09-07T07:46:41.4899708Z * [new tag] ciflow/inductor/162293 -> ciflow/inductor/162293 2025-09-07T07:46:41.4899894Z * [new tag] ciflow/inductor/162294 -> ciflow/inductor/162294 2025-09-07T07:46:41.4900082Z * [new tag] ciflow/inductor/162295 -> ciflow/inductor/162295 2025-09-07T07:46:41.4900280Z * [new tag] ciflow/inductor/162296 -> ciflow/inductor/162296 2025-09-07T07:46:41.4900471Z * [new tag] ciflow/inductor/162298 -> ciflow/inductor/162298 2025-09-07T07:46:41.4900669Z * [new tag] ciflow/inductor/162307 -> ciflow/inductor/162307 2025-09-07T07:46:41.4900861Z * [new tag] ciflow/inductor/162309 -> ciflow/inductor/162309 2025-09-07T07:46:41.4901051Z * [new tag] ciflow/inductor/162311 -> ciflow/inductor/162311 2025-09-07T07:46:41.4901253Z * [new tag] ciflow/inductor/162312 -> ciflow/inductor/162312 2025-09-07T07:46:41.4901445Z * [new tag] ciflow/inductor/162315 -> ciflow/inductor/162315 2025-09-07T07:46:41.4901643Z * [new tag] ciflow/inductor/162316 -> ciflow/inductor/162316 2025-09-07T07:46:41.4901832Z * [new tag] ciflow/inductor/162318 -> ciflow/inductor/162318 2025-09-07T07:46:41.4902033Z * [new tag] ciflow/inductor/162323 -> ciflow/inductor/162323 2025-09-07T07:46:41.4902223Z * [new tag] ciflow/inductor/162341 -> ciflow/inductor/162341 2025-09-07T07:46:41.4902497Z * [new tag] ciflow/inductor/162345 -> ciflow/inductor/162345 2025-09-07T07:46:41.4902712Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-09-07T07:46:41.4902910Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-09-07T07:46:41.4903116Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-09-07T07:46:41.4903329Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-09-07T07:46:41.4903542Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-09-07T07:46:41.4903760Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-09-07T07:46:41.4903935Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-09-07T07:46:41.4904116Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-09-07T07:46:41.4904290Z * [new tag] ciflow/mps/161988 -> ciflow/mps/161988 2025-09-07T07:46:41.4904470Z * [new tag] ciflow/mps/162108 -> ciflow/mps/162108 2025-09-07T07:46:41.4904634Z * [new tag] ciflow/mps/162153 -> ciflow/mps/162153 2025-09-07T07:46:41.4904804Z * [new tag] ciflow/mps/162281 -> ciflow/mps/162281 2025-09-07T07:46:41.4905079Z * [new tag] ciflow/nightly/156049 -> ciflow/nightly/156049 2025-09-07T07:46:41.4905270Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-09-07T07:46:41.4905494Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-09-07T07:46:41.4905775Z * [new tag] ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529 2025-09-07T07:46:41.4906061Z * [new tag] ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715 2025-09-07T07:46:41.4906269Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-09-07T07:46:41.4906637Z * [new tag] ciflow/periodic/156703 -> ciflow/periodic/156703 2025-09-07T07:46:41.4906848Z * [new tag] ciflow/periodic/161715 -> ciflow/periodic/161715 2025-09-07T07:46:41.4907040Z * [new tag] ciflow/periodic/162021 -> ciflow/periodic/162021 2025-09-07T07:46:41.4907246Z * [new tag] ciflow/periodic/162323 -> ciflow/periodic/162323 2025-09-07T07:46:41.4907451Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-09-07T07:46:41.4907653Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-09-07T07:46:41.4907855Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-09-07T07:46:41.4908055Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-09-07T07:46:41.4908295Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-09-07T07:46:41.4908540Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-09-07T07:46:41.4908788Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-09-07T07:46:41.4909024Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-09-07T07:46:41.4909253Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-09-07T07:46:41.4909513Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-09-07T07:46:41.4909732Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-09-07T07:46:41.4909941Z * [new tag] ciflow/rocm-mi300/154170 -> ciflow/rocm-mi300/154170 2025-09-07T07:46:41.4910217Z * [new tag] ciflow/rocm-mi300/158747 -> ciflow/rocm-mi300/158747 2025-09-07T07:46:41.4910408Z * [new tag] ciflow/rocm-mi300/159146 -> ciflow/rocm-mi300/159146 2025-09-07T07:46:41.4910609Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-09-07T07:46:41.4910803Z * [new tag] ciflow/rocm-mi300/161715 -> ciflow/rocm-mi300/161715 2025-09-07T07:46:41.4911004Z * [new tag] ciflow/rocm-mi300/161957 -> ciflow/rocm-mi300/161957 2025-09-07T07:46:41.4911194Z * [new tag] ciflow/rocm-mi300/162053 -> ciflow/rocm-mi300/162053 2025-09-07T07:46:41.4911393Z * [new tag] ciflow/rocm-mi300/162056 -> ciflow/rocm-mi300/162056 2025-09-07T07:46:41.4911588Z * [new tag] ciflow/rocm-mi300/162112 -> ciflow/rocm-mi300/162112 2025-09-07T07:46:41.4911779Z * [new tag] ciflow/rocm-mi300/162245 -> ciflow/rocm-mi300/162245 2025-09-07T07:46:41.4911983Z * [new tag] ciflow/rocm-mi300/162278 -> ciflow/rocm-mi300/162278 2025-09-07T07:46:41.4912176Z * [new tag] ciflow/rocm-mi300/162288 -> ciflow/rocm-mi300/162288 2025-09-07T07:46:41.4912379Z * [new tag] ciflow/rocm-mi355/162053 -> ciflow/rocm-mi355/162053 2025-09-07T07:46:41.4912571Z * [new tag] ciflow/rocm-mi355/162056 -> ciflow/rocm-mi355/162056 2025-09-07T07:46:41.4912744Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-09-07T07:46:41.4912924Z * [new tag] ciflow/rocm/154170 -> ciflow/rocm/154170 2025-09-07T07:46:41.4913099Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-09-07T07:46:41.4913275Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-09-07T07:46:41.4913448Z * [new tag] ciflow/rocm/158747 -> ciflow/rocm/158747 2025-09-07T07:46:41.4913627Z * [new tag] ciflow/rocm/159146 -> ciflow/rocm/159146 2025-09-07T07:46:41.4913797Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-09-07T07:46:41.4914052Z * [new tag] ciflow/rocm/161715 -> ciflow/rocm/161715 2025-09-07T07:46:41.4914233Z * [new tag] ciflow/rocm/161972 -> ciflow/rocm/161972 2025-09-07T07:46:41.4914400Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-09-07T07:46:41.4914577Z * [new tag] ciflow/rocm/162053 -> ciflow/rocm/162053 2025-09-07T07:46:41.4914747Z * [new tag] ciflow/rocm/162056 -> ciflow/rocm/162056 2025-09-07T07:46:41.4914922Z * [new tag] ciflow/rocm/162112 -> ciflow/rocm/162112 2025-09-07T07:46:41.4915106Z * [new tag] ciflow/rocm/162278 -> ciflow/rocm/162278 2025-09-07T07:46:41.4915277Z * [new tag] ciflow/rocm/162288 -> ciflow/rocm/162288 2025-09-07T07:46:41.4915461Z * [new tag] ciflow/rocm/162305 -> ciflow/rocm/162305 2025-09-07T07:46:41.4915640Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-09-07T07:46:41.4915828Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-09-07T07:46:41.4916362Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-09-07T07:46:41.4916542Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-09-07T07:46:41.4916727Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-09-07T07:46:41.4916899Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-09-07T07:46:41.4917085Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-09-07T07:46:41.4917263Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-09-07T07:46:41.4917523Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-09-07T07:46:41.4917709Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-09-07T07:46:41.4917884Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-09-07T07:46:41.4918066Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-09-07T07:46:41.4918242Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-09-07T07:46:41.4918745Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-09-07T07:46:41.4918925Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-09-07T07:46:41.4919101Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-09-07T07:46:41.4919285Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-09-07T07:46:41.4919463Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-09-07T07:46:41.4919648Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-09-07T07:46:41.4920171Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-09-07T07:46:41.4920419Z * [new tag] ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329 2025-09-07T07:46:41.4920596Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-09-07T07:46:41.4920771Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-09-07T07:46:41.4920957Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-09-07T07:46:41.4921132Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-09-07T07:46:41.4921321Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-09-07T07:46:41.4921491Z * [new tag] ciflow/trunk/148919 -> ciflow/trunk/148919 2025-09-07T07:46:41.4921754Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-09-07T07:46:41.4921936Z * [new tag] ciflow/trunk/154170 -> ciflow/trunk/154170 2025-09-07T07:46:41.4922109Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-09-07T07:46:41.4922289Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-09-07T07:46:41.4922463Z * [new tag] ciflow/trunk/156703 -> ciflow/trunk/156703 2025-09-07T07:46:41.4922649Z * [new tag] ciflow/trunk/156711 -> ciflow/trunk/156711 2025-09-07T07:46:41.4922823Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-09-07T07:46:41.4922995Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-09-07T07:46:41.4923183Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-09-07T07:46:41.4923356Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-09-07T07:46:41.4923539Z * [new tag] ciflow/trunk/157813 -> ciflow/trunk/157813 2025-09-07T07:46:41.4923713Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-09-07T07:46:41.4923887Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-09-07T07:46:41.4924067Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-09-07T07:46:41.4924240Z * [new tag] ciflow/trunk/158404 -> ciflow/trunk/158404 2025-09-07T07:46:41.4924425Z * [new tag] ciflow/trunk/158647 -> ciflow/trunk/158647 2025-09-07T07:46:41.4924599Z * [new tag] ciflow/trunk/158846 -> ciflow/trunk/158846 2025-09-07T07:46:41.4924887Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-09-07T07:46:41.4925062Z * [new tag] ciflow/trunk/159682 -> ciflow/trunk/159682 2025-09-07T07:46:41.4925248Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-09-07T07:46:41.4925439Z * [new tag] ciflow/trunk/160161 -> ciflow/trunk/160161 2025-09-07T07:46:41.4925615Z * [new tag] ciflow/trunk/160236 -> ciflow/trunk/160236 2025-09-07T07:46:41.4925806Z * [new tag] ciflow/trunk/160329 -> ciflow/trunk/160329 2025-09-07T07:46:41.4925982Z * [new tag] ciflow/trunk/160480 -> ciflow/trunk/160480 2025-09-07T07:46:41.4926157Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-09-07T07:46:41.4926345Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-09-07T07:46:41.4926521Z * [new tag] ciflow/trunk/160843 -> ciflow/trunk/160843 2025-09-07T07:46:41.4926715Z * [new tag] ciflow/trunk/160869 -> ciflow/trunk/160869 2025-09-07T07:46:41.4926894Z * [new tag] ciflow/trunk/160928 -> ciflow/trunk/160928 2025-09-07T07:46:41.4927083Z * [new tag] ciflow/trunk/160940 -> ciflow/trunk/160940 2025-09-07T07:46:41.4927257Z * [new tag] ciflow/trunk/160943 -> ciflow/trunk/160943 2025-09-07T07:46:41.4927430Z * [new tag] ciflow/trunk/160953 -> ciflow/trunk/160953 2025-09-07T07:46:41.4927618Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-09-07T07:46:41.4927792Z * [new tag] ciflow/trunk/161178 -> ciflow/trunk/161178 2025-09-07T07:46:41.4927980Z * [new tag] ciflow/trunk/161349 -> ciflow/trunk/161349 2025-09-07T07:46:41.4928157Z * [new tag] ciflow/trunk/161350 -> ciflow/trunk/161350 2025-09-07T07:46:41.4928338Z * [new tag] ciflow/trunk/161351 -> ciflow/trunk/161351 2025-09-07T07:46:41.4928610Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-09-07T07:46:41.4928786Z * [new tag] ciflow/trunk/161405 -> ciflow/trunk/161405 2025-09-07T07:46:41.4928973Z * [new tag] ciflow/trunk/161406 -> ciflow/trunk/161406 2025-09-07T07:46:41.4929150Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-09-07T07:46:41.4929338Z * [new tag] ciflow/trunk/161468 -> ciflow/trunk/161468 2025-09-07T07:46:41.4929515Z * [new tag] ciflow/trunk/161499 -> ciflow/trunk/161499 2025-09-07T07:46:41.4929689Z * [new tag] ciflow/trunk/161527 -> ciflow/trunk/161527 2025-09-07T07:46:41.4929877Z * [new tag] ciflow/trunk/161534 -> ciflow/trunk/161534 2025-09-07T07:46:41.4930053Z * [new tag] ciflow/trunk/161591 -> ciflow/trunk/161591 2025-09-07T07:46:41.4930241Z * [new tag] ciflow/trunk/161595 -> ciflow/trunk/161595 2025-09-07T07:46:41.4930418Z * [new tag] ciflow/trunk/161596 -> ciflow/trunk/161596 2025-09-07T07:46:41.4930594Z * [new tag] ciflow/trunk/161633 -> ciflow/trunk/161633 2025-09-07T07:46:41.4930781Z * [new tag] ciflow/trunk/161634 -> ciflow/trunk/161634 2025-09-07T07:46:41.4930956Z * [new tag] ciflow/trunk/161635 -> ciflow/trunk/161635 2025-09-07T07:46:41.4931141Z * [new tag] ciflow/trunk/161667 -> ciflow/trunk/161667 2025-09-07T07:46:41.4931316Z * [new tag] ciflow/trunk/161670 -> ciflow/trunk/161670 2025-09-07T07:46:41.4931491Z * [new tag] ciflow/trunk/161692 -> ciflow/trunk/161692 2025-09-07T07:46:41.4931680Z * [new tag] ciflow/trunk/161693 -> ciflow/trunk/161693 2025-09-07T07:46:41.4931944Z * [new tag] ciflow/trunk/161695 -> ciflow/trunk/161695 2025-09-07T07:46:41.4932139Z * [new tag] ciflow/trunk/161730 -> ciflow/trunk/161730 2025-09-07T07:46:41.4932315Z * [new tag] ciflow/trunk/161744 -> ciflow/trunk/161744 2025-09-07T07:46:41.4932507Z * [new tag] ciflow/trunk/161749 -> ciflow/trunk/161749 2025-09-07T07:46:41.4932685Z * [new tag] ciflow/trunk/161881 -> ciflow/trunk/161881 2025-09-07T07:46:41.4932989Z * [new tag] ciflow/trunk/161924 -> ciflow/trunk/161924 2025-09-07T07:46:41.4933184Z * [new tag] ciflow/trunk/161926 -> ciflow/trunk/161926 2025-09-07T07:46:41.4933360Z * [new tag] ciflow/trunk/161936 -> ciflow/trunk/161936 2025-09-07T07:46:41.4933549Z * [new tag] ciflow/trunk/161952 -> ciflow/trunk/161952 2025-09-07T07:46:41.4933727Z * [new tag] ciflow/trunk/161955 -> ciflow/trunk/161955 2025-09-07T07:46:41.4933901Z * [new tag] ciflow/trunk/161957 -> ciflow/trunk/161957 2025-09-07T07:46:41.4934091Z * [new tag] ciflow/trunk/161959 -> ciflow/trunk/161959 2025-09-07T07:46:41.4934266Z * [new tag] ciflow/trunk/161977 -> ciflow/trunk/161977 2025-09-07T07:46:41.4934453Z * [new tag] ciflow/trunk/161988 -> ciflow/trunk/161988 2025-09-07T07:46:41.4934628Z * [new tag] ciflow/trunk/161994 -> ciflow/trunk/161994 2025-09-07T07:46:41.4934813Z * [new tag] ciflow/trunk/162007 -> ciflow/trunk/162007 2025-09-07T07:46:41.4934985Z * [new tag] ciflow/trunk/162013 -> ciflow/trunk/162013 2025-09-07T07:46:41.4935160Z * [new tag] ciflow/trunk/162017 -> ciflow/trunk/162017 2025-09-07T07:46:41.4935351Z * [new tag] ciflow/trunk/162021 -> ciflow/trunk/162021 2025-09-07T07:46:41.4935526Z * [new tag] ciflow/trunk/162022 -> ciflow/trunk/162022 2025-09-07T07:46:41.4935810Z * [new tag] ciflow/trunk/162040 -> ciflow/trunk/162040 2025-09-07T07:46:41.4935986Z * [new tag] ciflow/trunk/162041 -> ciflow/trunk/162041 2025-09-07T07:46:41.4936159Z * [new tag] ciflow/trunk/162062 -> ciflow/trunk/162062 2025-09-07T07:46:41.4936347Z * [new tag] ciflow/trunk/162066 -> ciflow/trunk/162066 2025-09-07T07:46:41.4936521Z * [new tag] ciflow/trunk/162089 -> ciflow/trunk/162089 2025-09-07T07:46:41.4936707Z * [new tag] ciflow/trunk/162099 -> ciflow/trunk/162099 2025-09-07T07:46:41.4936882Z * [new tag] ciflow/trunk/162104 -> ciflow/trunk/162104 2025-09-07T07:46:41.4937068Z * [new tag] ciflow/trunk/162106 -> ciflow/trunk/162106 2025-09-07T07:46:41.4937248Z * [new tag] ciflow/trunk/162112 -> ciflow/trunk/162112 2025-09-07T07:46:41.4937426Z * [new tag] ciflow/trunk/162119 -> ciflow/trunk/162119 2025-09-07T07:46:41.4937613Z * [new tag] ciflow/trunk/162142 -> ciflow/trunk/162142 2025-09-07T07:46:41.4937787Z * [new tag] ciflow/trunk/162169 -> ciflow/trunk/162169 2025-09-07T07:46:41.4937972Z * [new tag] ciflow/trunk/162183 -> ciflow/trunk/162183 2025-09-07T07:46:41.4938146Z * [new tag] ciflow/trunk/162190 -> ciflow/trunk/162190 2025-09-07T07:46:41.4938321Z * [new tag] ciflow/trunk/162194 -> ciflow/trunk/162194 2025-09-07T07:46:41.4938501Z * [new tag] ciflow/trunk/162200 -> ciflow/trunk/162200 2025-09-07T07:46:41.4938673Z * [new tag] ciflow/trunk/162206 -> ciflow/trunk/162206 2025-09-07T07:46:41.4938951Z * [new tag] ciflow/trunk/162208 -> ciflow/trunk/162208 2025-09-07T07:46:41.4939126Z * [new tag] ciflow/trunk/162222 -> ciflow/trunk/162222 2025-09-07T07:46:41.4939318Z * [new tag] ciflow/trunk/162238 -> ciflow/trunk/162238 2025-09-07T07:46:41.4939494Z * [new tag] ciflow/trunk/162244 -> ciflow/trunk/162244 2025-09-07T07:46:41.4939667Z * [new tag] ciflow/trunk/162267 -> ciflow/trunk/162267 2025-09-07T07:46:41.4939855Z * [new tag] ciflow/trunk/162269 -> ciflow/trunk/162269 2025-09-07T07:46:41.4940027Z * [new tag] ciflow/trunk/162278 -> ciflow/trunk/162278 2025-09-07T07:46:41.4940215Z * [new tag] ciflow/trunk/162286 -> ciflow/trunk/162286 2025-09-07T07:46:41.4940389Z * [new tag] ciflow/trunk/162288 -> ciflow/trunk/162288 2025-09-07T07:46:41.4940562Z * [new tag] ciflow/trunk/162293 -> ciflow/trunk/162293 2025-09-07T07:46:41.4940752Z * [new tag] ciflow/trunk/162310 -> ciflow/trunk/162310 2025-09-07T07:46:41.4940929Z * [new tag] ciflow/trunk/162311 -> ciflow/trunk/162311 2025-09-07T07:46:41.4941115Z * [new tag] ciflow/trunk/162315 -> ciflow/trunk/162315 2025-09-07T07:46:41.4941289Z * [new tag] ciflow/trunk/162325 -> ciflow/trunk/162325 2025-09-07T07:46:41.4941477Z * [new tag] ciflow/trunk/162328 -> ciflow/trunk/162328 2025-09-07T07:46:41.4941653Z * [new tag] ciflow/trunk/162329 -> ciflow/trunk/162329 2025-09-07T07:46:41.4941833Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-09-07T07:46:41.4942022Z * [new tag] ciflow/vllm/162292 -> ciflow/vllm/162292 2025-09-07T07:46:41.4942218Z * [new tag] ciflow/win-arm64/156049 -> ciflow/win-arm64/156049 2025-09-07T07:46:41.4942423Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-09-07T07:46:41.4942596Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-09-07T07:46:41.4942850Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-09-07T07:46:41.4943035Z * [new tag] ciflow/xpu/159459 -> ciflow/xpu/159459 2025-09-07T07:46:41.4943203Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-09-07T07:46:41.4943384Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-09-07T07:46:41.4943554Z * [new tag] ciflow/xpu/160867 -> ciflow/xpu/160867 2025-09-07T07:46:41.4943735Z * [new tag] ciflow/xpu/160938 -> ciflow/xpu/160938 2025-09-07T07:46:41.4943904Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-09-07T07:46:41.4944072Z * [new tag] ciflow/xpu/160953 -> ciflow/xpu/160953 2025-09-07T07:46:41.4944257Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-09-07T07:46:41.4944429Z * [new tag] ciflow/xpu/161058 -> ciflow/xpu/161058 2025-09-07T07:46:41.4944614Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-09-07T07:46:41.4944784Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-09-07T07:46:41.4945047Z * [new tag] ciflow/xpu/161485 -> ciflow/xpu/161485 2025-09-07T07:46:41.4945233Z * [new tag] ciflow/xpu/161988 -> ciflow/xpu/161988 2025-09-07T07:46:41.4945402Z * [new tag] ciflow/xpu/162062 -> ciflow/xpu/162062 2025-09-07T07:46:41.4945571Z * [new tag] cslpull75 -> cslpull75 2025-09-07T07:46:41.4945727Z * [new tag] cslpull76 -> cslpull76 2025-09-07T07:46:41.4945971Z * [new tag] cslpull77 -> cslpull77 2025-09-07T07:46:41.4946131Z * [new tag] cslpull78 -> cslpull78 2025-09-07T07:46:41.4946284Z * [new tag] cslpull79 -> cslpull79 2025-09-07T07:46:41.4946448Z * [new tag] cslpull80 -> cslpull80 2025-09-07T07:46:41.4946598Z * [new tag] cslpull81 -> cslpull81 2025-09-07T07:46:41.4946761Z * [new tag] cslpull82 -> cslpull82 2025-09-07T07:46:41.4946910Z * [new tag] cslpull83 -> cslpull83 2025-09-07T07:46:41.4947063Z * [new tag] cslpull84 -> cslpull84 2025-09-07T07:46:41.4947228Z * [new tag] cslpull85 -> cslpull85 2025-09-07T07:46:41.4947378Z * [new tag] cslpull86 -> cslpull86 2025-09-07T07:46:41.4947542Z * [new tag] cslpull87 -> cslpull87 2025-09-07T07:46:41.4947695Z * [new tag] cslpull88 -> cslpull88 2025-09-07T07:46:41.4947850Z * [new tag] cslpull89 -> cslpull89 2025-09-07T07:46:41.4948011Z * [new tag] cslpull90 -> cslpull90 2025-09-07T07:46:41.4948161Z * [new tag] cslpull91 -> cslpull91 2025-09-07T07:46:41.4948325Z * [new tag] cslpull92 -> cslpull92 2025-09-07T07:46:41.4948476Z * [new tag] flight_5 -> flight_5 2025-09-07T07:46:41.4948627Z * [new tag] flight_5.1 -> flight_5.1 2025-09-07T07:46:41.4948791Z * [new tag] flight_5.2 -> flight_5.2 2025-09-07T07:46:41.4948941Z * [new tag] flight_5.3 -> flight_5.3 2025-09-07T07:46:41.4949104Z * [new tag] forpull1 -> forpull1 2025-09-07T07:46:41.4949288Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-09-07T07:46:41.4949478Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-09-07T07:46:41.4949757Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-09-07T07:46:41.4949933Z * [new tag] nightly-binary -> nightly-binary 2025-09-07T07:46:41.4950133Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-09-07T07:46:41.4950307Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-09-07T07:46:41.4950704Z * [new tag] trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608 2025-09-07T07:46:41.4951109Z * [new tag] trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 2025-09-07T07:46:41.4951515Z * [new tag] trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544 2025-09-07T07:46:41.4951931Z * [new tag] trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b 2025-09-07T07:46:41.4952320Z * [new tag] trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388 2025-09-07T07:46:41.4952730Z * [new tag] trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 2025-09-07T07:46:41.4953108Z * [new tag] trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4 2025-09-07T07:46:41.4953517Z * [new tag] trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 2025-09-07T07:46:41.4953905Z * [new tag] trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23 2025-09-07T07:46:41.4954392Z * [new tag] trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 2025-09-07T07:46:41.4954789Z * [new tag] trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 2025-09-07T07:46:41.4955173Z * [new tag] trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 2025-09-07T07:46:41.4955577Z * [new tag] trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 2025-09-07T07:46:41.4955962Z * [new tag] trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 2025-09-07T07:46:41.4956373Z * [new tag] trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 2025-09-07T07:46:41.4956771Z * [new tag] trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c 2025-09-07T07:46:41.4957189Z * [new tag] trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 2025-09-07T07:46:41.4957578Z * [new tag] trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e 2025-09-07T07:46:41.4957983Z * [new tag] trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 2025-09-07T07:46:41.4958390Z * [new tag] trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f 2025-09-07T07:46:41.4958776Z * [new tag] trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f 2025-09-07T07:46:41.4959178Z * [new tag] trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0 2025-09-07T07:46:41.4959573Z * [new tag] trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c 2025-09-07T07:46:41.4960077Z * [new tag] trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 2025-09-07T07:46:41.4960478Z * [new tag] trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 2025-09-07T07:46:41.4960877Z * [new tag] trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb 2025-09-07T07:46:41.4961272Z * [new tag] trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 2025-09-07T07:46:41.4961667Z * [new tag] trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 2025-09-07T07:46:41.4962070Z * [new tag] trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c 2025-09-07T07:46:41.4962470Z * [new tag] trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 2025-09-07T07:46:41.4962879Z * [new tag] trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 2025-09-07T07:46:41.4963271Z * [new tag] trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 2025-09-07T07:46:41.4963682Z * [new tag] trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a 2025-09-07T07:46:41.4964081Z * [new tag] trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 2025-09-07T07:46:41.4964493Z * [new tag] trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 2025-09-07T07:46:41.4964881Z * [new tag] trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a 2025-09-07T07:46:41.4965359Z * [new tag] trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b 2025-09-07T07:46:41.4965758Z * [new tag] trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc 2025-09-07T07:46:41.4966142Z * [new tag] trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05 2025-09-07T07:46:41.4966550Z * [new tag] trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 2025-09-07T07:46:41.4966942Z * [new tag] trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd 2025-09-07T07:46:41.4967352Z * [new tag] trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 2025-09-07T07:46:41.4967750Z * [new tag] trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f 2025-09-07T07:46:41.4968156Z * [new tag] trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23 2025-09-07T07:46:41.4968540Z * [new tag] trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 2025-09-07T07:46:41.4968924Z * [new tag] trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f 2025-09-07T07:46:41.4969334Z * [new tag] trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 2025-09-07T07:46:41.4969715Z * [new tag] trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9 2025-09-07T07:46:41.4970120Z * [new tag] trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 2025-09-07T07:46:41.4970518Z * [new tag] trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef 2025-09-07T07:46:41.4971004Z * [new tag] trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c 2025-09-07T07:46:41.4971390Z * [new tag] trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6 2025-09-07T07:46:41.4971788Z * [new tag] trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 2025-09-07T07:46:41.4972191Z * [new tag] trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a 2025-09-07T07:46:41.4972589Z * [new tag] trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 2025-09-07T07:46:41.4973146Z * [new tag] trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 2025-09-07T07:46:41.4973551Z * [new tag] trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 2025-09-07T07:46:41.4973955Z * [new tag] trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 2025-09-07T07:46:41.4974333Z * [new tag] trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176 2025-09-07T07:46:41.4974737Z * [new tag] trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 2025-09-07T07:46:41.4975138Z * [new tag] trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b 2025-09-07T07:46:41.4981160Z * [new tag] trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 2025-09-07T07:46:41.4981884Z * [new tag] trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287 2025-09-07T07:46:41.4982300Z * [new tag] trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f 2025-09-07T07:46:41.4982699Z * [new tag] trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 2025-09-07T07:46:41.4983105Z * [new tag] trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 2025-09-07T07:46:41.4983513Z * [new tag] trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f 2025-09-07T07:46:41.4983913Z * [new tag] trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf 2025-09-07T07:46:41.4984319Z * [new tag] trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 2025-09-07T07:46:41.4984715Z * [new tag] trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d 2025-09-07T07:46:41.4985245Z * [new tag] trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa 2025-09-07T07:46:41.4985642Z * [new tag] trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 2025-09-07T07:46:41.4986040Z * [new tag] trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336 2025-09-07T07:46:41.4986424Z * [new tag] trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63 2025-09-07T07:46:41.4986822Z * [new tag] trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3 2025-09-07T07:46:41.4987223Z * [new tag] trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c 2025-09-07T07:46:41.4987741Z * [new tag] trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 2025-09-07T07:46:41.4988148Z * [new tag] trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf 2025-09-07T07:46:41.4988559Z * [new tag] trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e 2025-09-07T07:46:41.4988977Z * [new tag] trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 2025-09-07T07:46:41.4989367Z * [new tag] trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215 2025-09-07T07:46:41.4989767Z * [new tag] trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d 2025-09-07T07:46:41.4990172Z * [new tag] trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 2025-09-07T07:46:41.4990568Z * [new tag] trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c 2025-09-07T07:46:41.4990983Z * [new tag] trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 2025-09-07T07:46:41.4991363Z * [new tag] trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b 2025-09-07T07:46:41.4991762Z * [new tag] trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 2025-09-07T07:46:41.4992140Z * [new tag] trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503 2025-09-07T07:46:41.4992636Z * [new tag] trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 2025-09-07T07:46:41.4993039Z * [new tag] trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 2025-09-07T07:46:41.4993439Z * [new tag] trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 2025-09-07T07:46:41.4993835Z * [new tag] trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 2025-09-07T07:46:41.4994223Z * [new tag] trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a 2025-09-07T07:46:41.4994622Z * [new tag] trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 2025-09-07T07:46:41.4995026Z * [new tag] trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 2025-09-07T07:46:41.4995437Z * [new tag] trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c 2025-09-07T07:46:41.4995836Z * [new tag] trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 2025-09-07T07:46:41.4996237Z * [new tag] trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806 2025-09-07T07:46:41.4996633Z * [new tag] trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 2025-09-07T07:46:41.4997024Z * [new tag] trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 2025-09-07T07:46:41.4997433Z * [new tag] trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 2025-09-07T07:46:41.4997811Z * [new tag] trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251 2025-09-07T07:46:41.4998313Z * [new tag] trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 2025-09-07T07:46:41.4998692Z * [new tag] trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c 2025-09-07T07:46:41.4999095Z * [new tag] trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a 2025-09-07T07:46:41.4999485Z * [new tag] trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db 2025-09-07T07:46:41.4999863Z * [new tag] trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536 2025-09-07T07:46:41.5000262Z * [new tag] trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f 2025-09-07T07:46:41.5000651Z * [new tag] trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 2025-09-07T07:46:41.5001051Z * [new tag] trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b 2025-09-07T07:46:41.5001436Z * [new tag] trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda 2025-09-07T07:46:41.5001836Z * [new tag] trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b 2025-09-07T07:46:41.5002226Z * [new tag] trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 2025-09-07T07:46:41.5002620Z * [new tag] trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8 2025-09-07T07:46:41.5003016Z * [new tag] trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b 2025-09-07T07:46:41.5003476Z * [new tag] trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab 2025-09-07T07:46:41.5003880Z * [new tag] trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 2025-09-07T07:46:41.5004260Z * [new tag] trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe 2025-09-07T07:46:41.5004670Z * [new tag] trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 2025-09-07T07:46:41.5005068Z * [new tag] trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 2025-09-07T07:46:41.5005467Z * [new tag] trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 2025-09-07T07:46:41.5005851Z * [new tag] trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c 2025-09-07T07:46:41.5006235Z * [new tag] trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d 2025-09-07T07:46:41.5006621Z * [new tag] trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429 2025-09-07T07:46:41.5007017Z * [new tag] trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 2025-09-07T07:46:41.5007414Z * [new tag] trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c 2025-09-07T07:46:41.5007803Z * [new tag] trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895 2025-09-07T07:46:41.5008208Z * [new tag] trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 2025-09-07T07:46:41.5008602Z * [new tag] trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435 2025-09-07T07:46:41.5009078Z * [new tag] trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965 2025-09-07T07:46:41.5009479Z * [new tag] trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 2025-09-07T07:46:41.5009873Z * [new tag] trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 2025-09-07T07:46:41.5010279Z * [new tag] trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 2025-09-07T07:46:41.5010680Z * [new tag] trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 2025-09-07T07:46:41.5011075Z * [new tag] trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 2025-09-07T07:46:41.5011468Z * [new tag] trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f 2025-09-07T07:46:41.5011873Z * [new tag] trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 2025-09-07T07:46:41.5012261Z * [new tag] trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610 2025-09-07T07:46:41.5012663Z * [new tag] trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 2025-09-07T07:46:41.5013230Z * [new tag] trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af 2025-09-07T07:46:41.5013635Z * [new tag] trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 2025-09-07T07:46:41.5014151Z * [new tag] trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d 2025-09-07T07:46:41.5014543Z * [new tag] trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 2025-09-07T07:46:41.5014948Z * [new tag] trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 2025-09-07T07:46:41.5015338Z * [new tag] trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab 2025-09-07T07:46:41.5015742Z * [new tag] trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d 2025-09-07T07:46:41.5016133Z * [new tag] trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:41.5016534Z * [new tag] trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c 2025-09-07T07:46:41.5016941Z * [new tag] trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e 2025-09-07T07:46:41.5017336Z * [new tag] trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 2025-09-07T07:46:41.5017734Z * [new tag] trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1 2025-09-07T07:46:41.5018126Z * [new tag] trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 2025-09-07T07:46:41.5018529Z * [new tag] trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a 2025-09-07T07:46:41.5018923Z * [new tag] trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500 2025-09-07T07:46:41.5019340Z * [new tag] trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 2025-09-07T07:46:41.5019826Z * [new tag] trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6 2025-09-07T07:46:41.5020226Z * [new tag] trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 2025-09-07T07:46:41.5020633Z * [new tag] trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd 2025-09-07T07:46:41.5021019Z * [new tag] trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57 2025-09-07T07:46:41.5021417Z * [new tag] trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4 2025-09-07T07:46:41.5021821Z * [new tag] trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e 2025-09-07T07:46:41.5022218Z * [new tag] trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839 2025-09-07T07:46:41.5022618Z * [new tag] trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60 2025-09-07T07:46:41.5023000Z * [new tag] trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 2025-09-07T07:46:41.5023408Z * [new tag] trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 2025-09-07T07:46:41.5023803Z * [new tag] trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 2025-09-07T07:46:41.5024206Z * [new tag] trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 2025-09-07T07:46:41.5024585Z * [new tag] trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d 2025-09-07T07:46:41.5025174Z * [new tag] trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 2025-09-07T07:46:41.5025568Z * [new tag] trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92 2025-09-07T07:46:41.5025961Z * [new tag] trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098 2025-09-07T07:46:41.5026363Z * [new tag] trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356 2025-09-07T07:46:41.5026751Z * [new tag] trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae 2025-09-07T07:46:41.5027170Z * [new tag] trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 2025-09-07T07:46:41.5027567Z * [new tag] trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e 2025-09-07T07:46:41.5027978Z * [new tag] trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 2025-09-07T07:46:41.5028373Z * [new tag] trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 2025-09-07T07:46:41.5028772Z * [new tag] trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c 2025-09-07T07:46:41.5029180Z * [new tag] trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 2025-09-07T07:46:41.5029583Z * [new tag] trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d 2025-09-07T07:46:41.5029983Z * [new tag] trunk/ada43ed39c80b746b4822c92640a1882619e2795 -> trunk/ada43ed39c80b746b4822c92640a1882619e2795 2025-09-07T07:46:41.5030381Z * [new tag] trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa 2025-09-07T07:46:41.5030892Z * [new tag] trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c 2025-09-07T07:46:41.5031284Z * [new tag] trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d 2025-09-07T07:46:41.5031676Z * [new tag] trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 2025-09-07T07:46:41.5032074Z * [new tag] trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f 2025-09-07T07:46:41.5032467Z * [new tag] trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 2025-09-07T07:46:41.5032864Z * [new tag] trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 2025-09-07T07:46:41.5033273Z * [new tag] trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de 2025-09-07T07:46:41.5033671Z * [new tag] trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b 2025-09-07T07:46:41.5034073Z * [new tag] trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 2025-09-07T07:46:41.5034475Z * [new tag] trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 2025-09-07T07:46:41.5034860Z * [new tag] trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b 2025-09-07T07:46:41.5035249Z * [new tag] trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde 2025-09-07T07:46:41.5035763Z * [new tag] trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c 2025-09-07T07:46:41.5036164Z * [new tag] trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 2025-09-07T07:46:41.5036561Z * [new tag] trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052 2025-09-07T07:46:41.5036948Z * [new tag] trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e 2025-09-07T07:46:41.5037353Z * [new tag] trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 2025-09-07T07:46:41.5037756Z * [new tag] trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 2025-09-07T07:46:41.5038147Z * [new tag] trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85 2025-09-07T07:46:41.5038556Z * [new tag] trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d 2025-09-07T07:46:41.5038968Z * [new tag] trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 2025-09-07T07:46:41.5039366Z * [new tag] trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865 2025-09-07T07:46:41.5039770Z * [new tag] trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 2025-09-07T07:46:41.5040183Z * [new tag] trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 2025-09-07T07:46:41.5040587Z * [new tag] trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 2025-09-07T07:46:41.5041002Z * [new tag] trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf 2025-09-07T07:46:41.5041472Z * [new tag] trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 2025-09-07T07:46:41.5041884Z * [new tag] trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad 2025-09-07T07:46:41.5042283Z * [new tag] trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 2025-09-07T07:46:41.5042670Z * [new tag] trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 2025-09-07T07:46:41.5043060Z * [new tag] trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76 2025-09-07T07:46:41.5043445Z * [new tag] trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5 2025-09-07T07:46:41.5043851Z * [new tag] trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 2025-09-07T07:46:41.5044255Z * [new tag] trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd 2025-09-07T07:46:41.5044649Z * [new tag] trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741 2025-09-07T07:46:41.5045044Z * [new tag] trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b 2025-09-07T07:46:41.5045433Z * [new tag] trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 2025-09-07T07:46:41.5045859Z * [new tag] trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 2025-09-07T07:46:41.5046256Z * [new tag] trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b 2025-09-07T07:46:41.5046749Z * [new tag] trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8 2025-09-07T07:46:41.5047148Z * [new tag] trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 2025-09-07T07:46:41.5047550Z * [new tag] trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7 2025-09-07T07:46:41.5047940Z * [new tag] trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87 2025-09-07T07:46:41.5048342Z * [new tag] trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e 2025-09-07T07:46:41.5048722Z * [new tag] trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e 2025-09-07T07:46:41.5049130Z * [new tag] trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d 2025-09-07T07:46:41.5049536Z * [new tag] trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 2025-09-07T07:46:41.5049936Z * [new tag] trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e 2025-09-07T07:46:41.5050336Z * [new tag] trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 2025-09-07T07:46:41.5050730Z * [new tag] trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 2025-09-07T07:46:41.5051126Z * [new tag] trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 2025-09-07T07:46:41.5051510Z * [new tag] trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462 2025-09-07T07:46:41.5051903Z * [new tag] trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 2025-09-07T07:46:41.5052379Z * [new tag] trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285 2025-09-07T07:46:41.5052762Z * [new tag] trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643 2025-09-07T07:46:41.5053302Z * [new tag] trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 2025-09-07T07:46:41.5053692Z * [new tag] trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661 2025-09-07T07:46:41.5054107Z * [new tag] trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab 2025-09-07T07:46:41.5054514Z * [new tag] trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 2025-09-07T07:46:41.5054937Z * [new tag] trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 2025-09-07T07:46:41.5055329Z * [new tag] trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061 2025-09-07T07:46:41.5055715Z * [new tag] trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a 2025-09-07T07:46:41.5056122Z * [new tag] trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 2025-09-07T07:46:41.5056527Z * [new tag] trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d 2025-09-07T07:46:41.5056934Z * [new tag] trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717 2025-09-07T07:46:41.5057514Z * [new tag] trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 2025-09-07T07:46:41.5057927Z * [new tag] trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 2025-09-07T07:46:41.5058322Z * [new tag] trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439 2025-09-07T07:46:41.5058723Z * [new tag] trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 2025-09-07T07:46:41.5059119Z * [new tag] trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 2025-09-07T07:46:41.5059516Z * [new tag] trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 2025-09-07T07:46:41.5059908Z * [new tag] trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b 2025-09-07T07:46:41.5060289Z * [new tag] trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090 2025-09-07T07:46:41.5060703Z * [new tag] trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087 2025-09-07T07:46:41.5061114Z * [new tag] trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 2025-09-07T07:46:41.5061519Z * [new tag] trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de 2025-09-07T07:46:41.5061919Z * [new tag] trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 2025-09-07T07:46:41.5062320Z * [new tag] trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 2025-09-07T07:46:41.5062730Z * [new tag] trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b 2025-09-07T07:46:41.5063206Z * [new tag] trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37 2025-09-07T07:46:41.5063610Z * [new tag] trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 2025-09-07T07:46:41.5063995Z * [new tag] trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd 2025-09-07T07:46:41.5064408Z * [new tag] trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb 2025-09-07T07:46:41.5064863Z * [new tag] trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c 2025-09-07T07:46:41.5065284Z * [new tag] trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8 2025-09-07T07:46:41.5065689Z * [new tag] trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c 2025-09-07T07:46:41.5066080Z * [new tag] trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c 2025-09-07T07:46:41.5066478Z * [new tag] trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 2025-09-07T07:46:41.5066885Z * [new tag] trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 2025-09-07T07:46:41.5067292Z * [new tag] trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa 2025-09-07T07:46:41.5067687Z * [new tag] trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab 2025-09-07T07:46:41.5068179Z * [new tag] trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd 2025-09-07T07:46:41.5068330Z * [new tag] v0.1.1 -> v0.1.1 2025-09-07T07:46:41.5068477Z * [new tag] v0.1.10 -> v0.1.10 2025-09-07T07:46:41.5068629Z * [new tag] v0.1.11 -> v0.1.11 2025-09-07T07:46:41.5068770Z * [new tag] v0.1.12 -> v0.1.12 2025-09-07T07:46:41.5068921Z * [new tag] v0.1.2 -> v0.1.2 2025-09-07T07:46:41.5069062Z * [new tag] v0.1.3 -> v0.1.3 2025-09-07T07:46:41.5069198Z * [new tag] v0.1.4 -> v0.1.4 2025-09-07T07:46:41.5069350Z * [new tag] v0.1.5 -> v0.1.5 2025-09-07T07:46:41.5069488Z * [new tag] v0.1.6 -> v0.1.6 2025-09-07T07:46:41.5069641Z * [new tag] v0.1.7 -> v0.1.7 2025-09-07T07:46:41.5069783Z * [new tag] v0.1.8 -> v0.1.8 2025-09-07T07:46:41.5069935Z * [new tag] v0.1.9 -> v0.1.9 2025-09-07T07:46:41.5070073Z * [new tag] v0.2.0 -> v0.2.0 2025-09-07T07:46:41.5070211Z * [new tag] v0.3.0 -> v0.3.0 2025-09-07T07:46:41.5070359Z * [new tag] v0.3.1 -> v0.3.1 2025-09-07T07:46:41.5070499Z * [new tag] v0.4.0 -> v0.4.0 2025-09-07T07:46:41.5070646Z * [new tag] v0.4.1 -> v0.4.1 2025-09-07T07:46:41.5070786Z * [new tag] v1.0.0 -> v1.0.0 2025-09-07T07:46:41.5070934Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-09-07T07:46:41.5071086Z * [new tag] v1.0.1 -> v1.0.1 2025-09-07T07:46:41.5071235Z * [new tag] v1.0rc0 -> v1.0rc0 2025-09-07T07:46:41.5071389Z * [new tag] v1.0rc1 -> v1.0rc1 2025-09-07T07:46:41.5071615Z * [new tag] v1.1.0 -> v1.1.0 2025-09-07T07:46:41.5071763Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-09-07T07:46:41.5071915Z * [new tag] v1.10.0 -> v1.10.0 2025-09-07T07:46:41.5072070Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-09-07T07:46:41.5072234Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-09-07T07:46:41.5072383Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-09-07T07:46:41.5072533Z * [new tag] v1.10.1 -> v1.10.1 2025-09-07T07:46:41.5072681Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-09-07T07:46:41.5072826Z * [new tag] v1.10.2 -> v1.10.2 2025-09-07T07:46:41.5072989Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-09-07T07:46:41.5073135Z * [new tag] v1.11.0 -> v1.11.0 2025-09-07T07:46:41.5073298Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-09-07T07:46:41.5073448Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-09-07T07:46:41.5073595Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-09-07T07:46:41.5073757Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-09-07T07:46:41.5073903Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-09-07T07:46:41.5074065Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-09-07T07:46:41.5074212Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-09-07T07:46:41.5074355Z * [new tag] v1.12.0 -> v1.12.0 2025-09-07T07:46:41.5074616Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-09-07T07:46:41.5074765Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-09-07T07:46:41.5074926Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-09-07T07:46:41.5075073Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-09-07T07:46:41.5075222Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-09-07T07:46:41.5075386Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-09-07T07:46:41.5075534Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-09-07T07:46:41.5075695Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-09-07T07:46:41.5075835Z * [new tag] v1.12.1 -> v1.12.1 2025-09-07T07:46:41.5075997Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-09-07T07:46:41.5076149Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-09-07T07:46:41.5076297Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-09-07T07:46:41.5076463Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-09-07T07:46:41.5076610Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-09-07T07:46:41.5076761Z * [new tag] v1.13.0 -> v1.13.0 2025-09-07T07:46:41.5076908Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-09-07T07:46:41.5077058Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-09-07T07:46:41.5077219Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-09-07T07:46:41.5077367Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-09-07T07:46:41.5077526Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-09-07T07:46:41.5077672Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-09-07T07:46:41.5077814Z * [new tag] v1.13.1 -> v1.13.1 2025-09-07T07:46:41.5078056Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-09-07T07:46:41.5078200Z * [new tag] v1.2.0 -> v1.2.0 2025-09-07T07:46:41.5078359Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-09-07T07:46:41.5078500Z * [new tag] v1.3.0 -> v1.3.0 2025-09-07T07:46:41.5078657Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-09-07T07:46:41.5078796Z * [new tag] v1.3.1 -> v1.3.1 2025-09-07T07:46:41.5078935Z * [new tag] v1.4.0 -> v1.4.0 2025-09-07T07:46:41.5079092Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-09-07T07:46:41.5079230Z * [new tag] v1.4.1 -> v1.4.1 2025-09-07T07:46:41.5079383Z * [new tag] v1.5.0 -> v1.5.0 2025-09-07T07:46:41.5079538Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-09-07T07:46:41.5079685Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-09-07T07:46:41.5079845Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-09-07T07:46:41.5079993Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-09-07T07:46:41.5080154Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-09-07T07:46:41.5080295Z * [new tag] v1.5.1 -> v1.5.1 2025-09-07T07:46:41.5080442Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-09-07T07:46:41.5080592Z * [new tag] v1.6.0 -> v1.6.0 2025-09-07T07:46:41.5080739Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-09-07T07:46:41.5080986Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-09-07T07:46:41.5081132Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-09-07T07:46:41.5081297Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-09-07T07:46:41.5081444Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-09-07T07:46:41.5081592Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-09-07T07:46:41.5081749Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-09-07T07:46:41.5081888Z * [new tag] v1.7.0 -> v1.7.0 2025-09-07T07:46:41.5082046Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-09-07T07:46:41.5082193Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-09-07T07:46:41.5082341Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-09-07T07:46:41.5082507Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-09-07T07:46:41.5082646Z * [new tag] v1.7.1 -> v1.7.1 2025-09-07T07:46:41.5082809Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-09-07T07:46:41.5082954Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-09-07T07:46:41.5083103Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-09-07T07:46:41.5083254Z * [new tag] v1.8.0 -> v1.8.0 2025-09-07T07:46:41.5083402Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-09-07T07:46:41.5083561Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-09-07T07:46:41.5083706Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-09-07T07:46:41.5083869Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-09-07T07:46:41.5084015Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-09-07T07:46:41.5084160Z * [new tag] v1.8.1 -> v1.8.1 2025-09-07T07:46:41.5084411Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-09-07T07:46:41.5084559Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-09-07T07:46:41.5084721Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-09-07T07:46:41.5084861Z * [new tag] v1.8.2 -> v1.8.2 2025-09-07T07:46:41.5085009Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-09-07T07:46:41.5085165Z * [new tag] v1.9.0 -> v1.9.0 2025-09-07T07:46:41.5085315Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-09-07T07:46:41.5085480Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-09-07T07:46:41.5085628Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-09-07T07:46:41.5085782Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-09-07T07:46:41.5085936Z * [new tag] v1.9.1 -> v1.9.1 2025-09-07T07:46:41.5086090Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-09-07T07:46:41.5086252Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-09-07T07:46:41.5086392Z * [new tag] v2.0.0 -> v2.0.0 2025-09-07T07:46:41.5086551Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-09-07T07:46:41.5086697Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-09-07T07:46:41.5086844Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-09-07T07:46:41.5087000Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-09-07T07:46:41.5087149Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-09-07T07:46:41.5087389Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-09-07T07:46:41.5087527Z * [new tag] v2.0.1 -> v2.0.1 2025-09-07T07:46:41.5087680Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-09-07T07:46:41.5087838Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-09-07T07:46:41.5087985Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-09-07T07:46:41.5088143Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-09-07T07:46:41.5088282Z * [new tag] v2.1.0 -> v2.1.0 2025-09-07T07:46:41.5088429Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-09-07T07:46:41.5088586Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-09-07T07:46:41.5088734Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-09-07T07:46:41.5088890Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-09-07T07:46:41.5089039Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-09-07T07:46:41.5089201Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-09-07T07:46:41.5089340Z * [new tag] v2.1.1 -> v2.1.1 2025-09-07T07:46:41.5089488Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-09-07T07:46:41.5089648Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-09-07T07:46:41.5089797Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-09-07T07:46:41.5089954Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-09-07T07:46:41.5090103Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-09-07T07:46:41.5090250Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-09-07T07:46:41.5090400Z * [new tag] v2.1.2 -> v2.1.2 2025-09-07T07:46:41.5090549Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-09-07T07:46:41.5090710Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-09-07T07:46:41.5090942Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-09-07T07:46:41.5091084Z * [new tag] v2.2.0 -> v2.2.0 2025-09-07T07:46:41.5091241Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-09-07T07:46:41.5091388Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-09-07T07:46:41.5091545Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-09-07T07:46:41.5091691Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-09-07T07:46:41.5091837Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-09-07T07:46:41.5091993Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-09-07T07:46:41.5092144Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-09-07T07:46:41.5092305Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-09-07T07:46:41.5092451Z * [new tag] v2.2.1 -> v2.2.1 2025-09-07T07:46:41.5092608Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-09-07T07:46:41.5092754Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-09-07T07:46:41.5093057Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-09-07T07:46:41.5093208Z * [new tag] v2.2.2 -> v2.2.2 2025-09-07T07:46:41.5093358Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-09-07T07:46:41.5093517Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-09-07T07:46:41.5093664Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-09-07T07:46:41.5093907Z * [new tag] v2.3.0 -> v2.3.0 2025-09-07T07:46:41.5094066Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-09-07T07:46:41.5094223Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-09-07T07:46:41.5094385Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-09-07T07:46:41.5094538Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-09-07T07:46:41.5094688Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-09-07T07:46:41.5094848Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-09-07T07:46:41.5094996Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-09-07T07:46:41.5095153Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-09-07T07:46:41.5095302Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-09-07T07:46:41.5095462Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-09-07T07:46:41.5095611Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-09-07T07:46:41.5095758Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-09-07T07:46:41.5095910Z * [new tag] v2.3.1 -> v2.3.1 2025-09-07T07:46:41.5096058Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-09-07T07:46:41.5096215Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-09-07T07:46:41.5096360Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-09-07T07:46:41.5096502Z * [new tag] v2.4.0 -> v2.4.0 2025-09-07T07:46:41.5096659Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-09-07T07:46:41.5096805Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-09-07T07:46:41.5096966Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-09-07T07:46:41.5097117Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-09-07T07:46:41.5097263Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-09-07T07:46:41.5097530Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-09-07T07:46:41.5097681Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-09-07T07:46:41.5097838Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-09-07T07:46:41.5097986Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-09-07T07:46:41.5098138Z * [new tag] v2.4.1 -> v2.4.1 2025-09-07T07:46:41.5098287Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-09-07T07:46:41.5098435Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-09-07T07:46:41.5098593Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-09-07T07:46:41.5098740Z * [new tag] v2.5.0 -> v2.5.0 2025-09-07T07:46:41.5098898Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-09-07T07:46:41.5099055Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-09-07T07:46:41.5099205Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-09-07T07:46:41.5099362Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-09-07T07:46:41.5099510Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-09-07T07:46:41.5099670Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-09-07T07:46:41.5099819Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-09-07T07:46:41.5099966Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-09-07T07:46:41.5100125Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-09-07T07:46:41.5100272Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-09-07T07:46:41.5100519Z * [new tag] v2.5.1 -> v2.5.1 2025-09-07T07:46:41.5100669Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-09-07T07:46:41.5100821Z * [new tag] v2.6.0 -> v2.6.0 2025-09-07T07:46:41.5100969Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-09-07T07:46:41.5101113Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-09-07T07:46:41.5101270Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-09-07T07:46:41.5101417Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-09-07T07:46:41.5101572Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-09-07T07:46:41.5101738Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-09-07T07:46:41.5101884Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-09-07T07:46:41.5102032Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-09-07T07:46:41.5102190Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-09-07T07:46:41.5102332Z * [new tag] v2.7.0 -> v2.7.0 2025-09-07T07:46:41.5102489Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-09-07T07:46:41.5102640Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-09-07T07:46:41.5102801Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-09-07T07:46:41.5102947Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-09-07T07:46:41.5103092Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-09-07T07:46:41.5103250Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-09-07T07:46:41.5103396Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-09-07T07:46:41.5103558Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-09-07T07:46:41.5103705Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-09-07T07:46:41.5103936Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-09-07T07:46:41.5104093Z * [new tag] v2.7.1 -> v2.7.1 2025-09-07T07:46:41.5104239Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-09-07T07:46:41.5104396Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-09-07T07:46:41.5104543Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-09-07T07:46:41.5104690Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-09-07T07:46:41.5104933Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-09-07T07:46:41.5105079Z * [new tag] v2.8.0 -> v2.8.0 2025-09-07T07:46:41.5105236Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-09-07T07:46:41.5105389Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-09-07T07:46:41.5105540Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-09-07T07:46:41.5105703Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-09-07T07:46:41.5105848Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-09-07T07:46:41.5106010Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-09-07T07:46:41.5106157Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-09-07T07:46:41.5106315Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-09-07T07:46:41.5106475Z * [new tag] whc_flight_1 -> whc_flight_1 2025-09-07T07:46:41.5106627Z * [new tag] whc_flight_2 -> whc_flight_2 2025-09-07T07:46:41.5106797Z * [new tag] whc_flight_4 -> whc_flight_4 2025-09-07T07:46:42.0246564Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:46:42.0271961Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:42.0275713Z ##[endgroup] 2025-09-07T07:46:42.0276125Z ##[group]Determining the checkout info 2025-09-07T07:46:42.0276942Z ##[endgroup] 2025-09-07T07:46:42.0280746Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:46:42.0328844Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:46:42.0354293Z ##[group]Checking out the ref 2025-09-07T07:46:42.0357771Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:43.0678120Z Updating files: 80% (15648/19405) 2025-09-07T07:46:43.0925320Z Updating files: 81% (15719/19405) 2025-09-07T07:46:43.1150141Z Updating files: 82% (15913/19405) 2025-09-07T07:46:43.1269125Z Updating files: 83% (16107/19405) 2025-09-07T07:46:43.1400623Z Updating files: 84% (16301/19405) 2025-09-07T07:46:43.1553324Z Updating files: 85% (16495/19405) 2025-09-07T07:46:43.1684527Z Updating files: 86% (16689/19405) 2025-09-07T07:46:43.1814602Z Updating files: 87% (16883/19405) 2025-09-07T07:46:43.1912432Z Updating files: 88% (17077/19405) 2025-09-07T07:46:43.2047056Z Updating files: 89% (17271/19405) 2025-09-07T07:46:43.2964312Z Updating files: 90% (17465/19405) 2025-09-07T07:46:43.3068392Z Updating files: 91% (17659/19405) 2025-09-07T07:46:43.3205075Z Updating files: 92% (17853/19405) 2025-09-07T07:46:43.3388104Z Updating files: 93% (18047/19405) 2025-09-07T07:46:43.3589646Z Updating files: 94% (18241/19405) 2025-09-07T07:46:43.3745529Z Updating files: 95% (18435/19405) 2025-09-07T07:46:43.3904296Z Updating files: 96% (18629/19405) 2025-09-07T07:46:43.4089210Z Updating files: 97% (18823/19405) 2025-09-07T07:46:43.4364696Z Updating files: 98% (19017/19405) 2025-09-07T07:46:43.4517262Z Updating files: 99% (19211/19405) 2025-09-07T07:46:43.4517897Z Updating files: 100% (19405/19405) 2025-09-07T07:46:43.4518460Z Updating files: 100% (19405/19405), done. 2025-09-07T07:46:43.4789042Z Note: switching to '93fb23d6fae7c4e82c4239a1033e522088742634'. 2025-09-07T07:46:43.4790108Z 2025-09-07T07:46:43.4790643Z You are in 'detached HEAD' state. You can look around, make experimental 2025-09-07T07:46:43.4791669Z changes and commit them, and you can discard any commits you make in this 2025-09-07T07:46:43.4792684Z state without impacting any branches by switching back to a branch. 2025-09-07T07:46:43.4793283Z 2025-09-07T07:46:43.4793688Z If you want to create a new branch to retain commits you create, you may 2025-09-07T07:46:43.4794605Z do so (now or later) by using -c with the switch command. Example: 2025-09-07T07:46:43.4795138Z 2025-09-07T07:46:43.4795337Z git switch -c 2025-09-07T07:46:43.4795700Z 2025-09-07T07:46:43.4795893Z Or undo this operation with: 2025-09-07T07:46:43.4796248Z 2025-09-07T07:46:43.4796413Z git switch - 2025-09-07T07:46:43.4796671Z 2025-09-07T07:46:43.4797119Z Turn off this advice by setting config variable advice.detachedHead to false 2025-09-07T07:46:43.4797718Z 2025-09-07T07:46:43.4798058Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:46:43.4902279Z ##[endgroup] 2025-09-07T07:46:43.4903058Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:46:43.4908299Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:46:43.4945615Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:46:43.4974551Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:46:43.4999585Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:46:43.5023944Z ##[endgroup] 2025-09-07T07:46:43.5024652Z ##[group]Fetching submodules 2025-09-07T07:46:43.5026983Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:46:44.1089800Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:46:44.1340120Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-09-07T07:46:44.1349198Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-09-07T07:46:44.1359142Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-09-07T07:46:44.1369140Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-09-07T07:46:44.1379246Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-09-07T07:46:44.1390114Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-09-07T07:46:44.1400231Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-09-07T07:46:44.1410559Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-09-07T07:46:44.1421202Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-09-07T07:46:44.1431820Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-09-07T07:46:44.1442284Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-09-07T07:46:44.1452571Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-09-07T07:46:44.1463498Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-09-07T07:46:44.1474446Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-09-07T07:46:44.1484652Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-09-07T07:46:44.1496167Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-09-07T07:46:44.1507513Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-09-07T07:46:44.1518198Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-09-07T07:46:44.1529252Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:46:44.1540652Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-09-07T07:46:44.1552095Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-09-07T07:46:44.1563153Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-09-07T07:46:44.1574794Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-09-07T07:46:44.1586725Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-09-07T07:46:44.1598706Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-09-07T07:46:44.1610302Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-09-07T07:46:44.1621734Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-09-07T07:46:44.1633226Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-09-07T07:46:44.1645100Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-09-07T07:46:44.1656785Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-09-07T07:46:44.1668560Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-09-07T07:46:44.1680389Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-09-07T07:46:44.1692247Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-09-07T07:46:44.1704555Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-09-07T07:46:44.1716888Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-09-07T07:46:44.1729259Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-09-07T07:46:44.1741932Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-09-07T07:46:44.1771315Z Cloning into '/home/david/_work/pytorch/pytorch/android/libs/fbjni'... 2025-09-07T07:46:45.7021740Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/FP16'... 2025-09-07T07:46:47.2341120Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/FXdiv'... 2025-09-07T07:46:48.1168897Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/NNPACK'... 2025-09-07T07:46:49.1814498Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/NVTX'... 2025-09-07T07:46:50.3069009Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-09-07T07:46:52.2151512Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-09-07T07:47:04.7526148Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/aiter'... 2025-09-07T07:47:13.9440025Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/benchmark'... 2025-09-07T07:47:15.5640848Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-09-07T07:47:22.1426163Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-09-07T07:47:23.1951231Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-09-07T07:47:24.3299166Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-09-07T07:47:27.6616518Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/cutlass'... 2025-09-07T07:47:31.7777553Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm'... 2025-09-07T07:47:33.8443940Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/flash-attention'... 2025-09-07T07:47:34.5781052Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-09-07T07:47:35.9833382Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fmt'... 2025-09-07T07:47:37.1713579Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-09-07T07:47:37.6775941Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/gloo'... 2025-09-07T07:47:38.1674825Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/googletest'... 2025-09-07T07:47:39.2407266Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/ideep'... 2025-09-07T07:47:39.7618372Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/ittapi'... 2025-09-07T07:47:40.3386748Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto'... 2025-09-07T07:47:41.6808592Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kleidiai'... 2025-09-07T07:47:42.2893285Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/mimalloc'... 2025-09-07T07:47:43.2631242Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/nlohmann'... 2025-09-07T07:47:52.8549744Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/onnx'... 2025-09-07T07:47:58.5069336Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-09-07T07:48:09.4603640Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/pocketfft'... 2025-09-07T07:48:10.2551298Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/protobuf'... 2025-09-07T07:48:20.1827992Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/psimd'... 2025-09-07T07:48:20.4802128Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-09-07T07:48:20.8387717Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/pybind11'... 2025-09-07T07:48:23.0171137Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-09-07T07:48:24.9838786Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/sleef'... 2025-09-07T07:48:27.0218498Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-09-07T07:48:27.5757641Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:48:27.5880781Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:48:27.5977975Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:48:27.6282269Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:48:27.7413590Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:48:27.8085889Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:48:28.5801005Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:48:28.7482747Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:48:28.7531594Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:48:28.7558291Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-09-07T07:48:32.4268321Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:48:32.4499841Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:48:32.7651617Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:48:32.8143003Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:48:32.9197093Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:48:32.9823289Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:48:33.6867408Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:48:33.8637736Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:48:33.8679373Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-09-07T07:48:33.8690124Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:48:33.8700845Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:48:33.8711543Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-09-07T07:48:33.8722534Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-09-07T07:48:33.8734061Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:48:33.8744848Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-09-07T07:48:33.8779777Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-09-07T07:48:35.2416717Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-09-07T07:48:36.3638400Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-09-07T07:48:37.0908960Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-09-07T07:48:40.3209992Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-09-07T07:48:43.1030954Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-09-07T07:48:44.5587599Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-09-07T07:48:55.7323278Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:48:56.0126015Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:48:56.1489213Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:48:57.2283833Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:48:57.3145616Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:57.3612038Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:48:57.6462303Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:48:57.8362087Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:48:57.9097065Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:48:57.9704610Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:48:57.9737016Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-09-07T07:49:04.2301233Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-09-07T07:49:10.2095472Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:49:11.1208934Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:49:11.2811044Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:49:11.3472688Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:49:11.4188016Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:49:11.4813359Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:49:11.7950664Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:49:12.0622184Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:49:12.1078094Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-09-07T07:49:12.1104417Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-09-07T07:49:30.5282312Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:49:30.5659001Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:49:30.6916997Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:49:30.7167868Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:49:30.7417690Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:49:30.7665133Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:49:30.7697675Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-09-07T07:49:32.0058150Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-09-07T07:49:34.4437216Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-09-07T07:49:37.3659923Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:49:37.3963973Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:49:37.4421347Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:49:37.4685748Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:49:37.6695935Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:49:37.7025804Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:49:37.8505708Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:49:37.9352574Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:49:37.9712119Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:49:37.9742674Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-09-07T07:49:41.5896266Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-09-07T07:49:42.7747691Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-09-07T07:49:45.3842896Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-09-07T07:49:46.8034329Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-09-07T07:49:48.6608518Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-09-07T07:49:51.7159641Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-09-07T07:50:06.6006805Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-09-07T07:50:07.9016063Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:50:07.9433431Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:50:08.0008874Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:50:08.0354530Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:50:08.0692572Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:08.0717875Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-09-07T07:50:09.3931967Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:50:09.4423046Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:50:09.5014834Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:50:09.8964631Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:50:09.9444371Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:50:10.0141260Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:50:10.0904281Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:50:10.1631354Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:50:10.2275733Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:50:10.3689359Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:50:11.2759747Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:50:11.3108815Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:11.3139229Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'... 2025-09-07T07:50:14.2735165Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:50:14.3821697Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:50:14.4300228Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:14.4792128Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:14.5345298Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:14.5941786Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:14.6466347Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:14.6971550Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:14.7521224Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:14.7971361Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:14.7997207Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-09-07T07:50:17.0751527Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-09-07T07:50:21.0875268Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-09-07T07:50:22.8158812Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-09-07T07:50:38.2221626Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-09-07T07:50:39.3645576Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-09-07T07:50:40.4071584Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-09-07T07:50:42.3724689Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-09-07T07:50:53.4215165Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:50:53.5852176Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:50:53.6395406Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:50:53.8119944Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:50:53.8480613Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:50:53.8953879Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:50:53.9382666Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:50:53.9576254Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:53.9815632Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:53.9854185Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'... 2025-09-07T07:50:57.4939525Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'... 2025-09-07T07:51:00.3559336Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T07:51:00.4125840Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T07:51:01.2241844Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T07:51:01.2530804Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T07:51:01.6299747Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T07:51:01.6530170Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:01.6732702Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:01.6760950Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/protobuf/third_party/benchmark'... 2025-09-07T07:51:03.0381871Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/protobuf/third_party/googletest'... 2025-09-07T07:51:05.3543269Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T07:51:05.4464028Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T07:51:05.4777554Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900' 2025-09-07T07:51:05.5053313Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8' 2025-09-07T07:51:05.5542221Z Submodule path 'third_party/pybind11': checked out 'f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8' 2025-09-07T07:51:05.5975719Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67' 2025-09-07T07:51:05.6653799Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68' 2025-09-07T07:51:05.7008257Z Submodule path 'third_party/tensorpipe': checked out 'af0118d13e52f5a08841464a768e01a0bf3e3075' 2025-09-07T07:51:05.7237416Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:05.7346149Z Submodule 'third_party/libnop' (https://github.com/google/libnop.git) registered for path 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:05.7547781Z Submodule 'third_party/libuv' (https://github.com/libuv/libuv.git) registered for path 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:05.7896610Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:05.7931354Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/tensorpipe/third_party/googletest'... 2025-09-07T07:51:07.6922852Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/tensorpipe/third_party/libnop'... 2025-09-07T07:51:09.0182664Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/tensorpipe/third_party/libuv'... 2025-09-07T07:51:11.6674050Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/tensorpipe/third_party/pybind11'... 2025-09-07T07:51:13.7061664Z Submodule path 'third_party/tensorpipe/third_party/googletest': checked out 'aee0f9d9b5b87796ee8a0ab26b7587ec30e8858e' 2025-09-07T07:51:13.7332073Z Submodule path 'third_party/tensorpipe/third_party/libnop': checked out '910b55815be16109f04f4180e9adee14fb4ce281' 2025-09-07T07:51:13.8221535Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '5152db2cbfeb5582e9c27c5ea1dba2cd9e10759b' 2025-09-07T07:51:13.8634323Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef' 2025-09-07T07:51:13.8828397Z Submodule 'tools/clang' (https://github.com/wjakob/clang-cindex-python3) registered for path 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:13.8853548Z Cloning into '/home/david/_work/pytorch/pytorch/third_party/tensorpipe/third_party/pybind11/tools/clang'... 2025-09-07T07:51:14.7734015Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5' 2025-09-07T07:51:14.7769239Z 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2025-09-07T07:51:20.4695169Z git version 2.51.0 2025-09-07T07:51:20.4718736Z ##[endgroup] 2025-09-07T07:51:20.4729873Z Temporarily overriding HOME='/home/david/_work/_temp/704ae26d-ac39-4362-93e5-16df5976d402' before making global git config changes 2025-09-07T07:51:20.4730769Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T07:51:20.4735342Z [command]/usr/bin/git config --global --add safe.directory /home/david/_work/pytorch/pytorch 2025-09-07T07:51:20.4810225Z [command]/usr/bin/git config --local --get remote.origin.url 2025-09-07T07:51:20.4830635Z https://github.com/pytorch/pytorch 2025-09-07T07:51:20.4843739Z ##[group]Removing previously created refs, to avoid conflicts 2025-09-07T07:51:20.4847229Z [command]/usr/bin/git rev-parse --symbolic-full-name --verify --quiet HEAD 2025-09-07T07:51:20.4867161Z HEAD 2025-09-07T07:51:20.4900209Z ##[endgroup] 2025-09-07T07:51:20.4903300Z [command]/usr/bin/git submodule status 2025-09-07T07:51:20.5171681Z 7e1e1fe3858c63c251c637ae41a20de425dde96f android/libs/fbjni (v0.1.0-12-g7e1e1fe) 2025-09-07T07:51:20.5251681Z 4dfe081cf6bcd15db339cf2680b9281b8451eeb3 third_party/FP16 (4dfe081) 2025-09-07T07:51:20.5331322Z b408327ac2a15ec3e43352421954f5b1967701d1 third_party/FXdiv (b408327) 2025-09-07T07:51:20.5425459Z c07e3a0400713d546e0dea2d5466dd22ea389c73 third_party/NNPACK (c07e3a0) 2025-09-07T07:51:20.5479799Z 2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07 third_party/NVTX (v3.1.0-263-g2942f16) 2025-09-07T07:51:20.5571661Z 1d8f600fd424278486eade7ed3e877c99f0846b1 third_party/VulkanMemoryAllocator (v2.1.0-982-g1d8f600) 2025-09-07T07:51:20.6098355Z 51a0103656eff6fc9bfd39a4597923c4b542c883 third_party/XNNPACK (remotes/origin/ds/ndk-1243-g51a0103656) 2025-09-07T07:51:20.6138673Z 01aae101b9e5e94d6c16a9514c9fb8df99c93150 third_party/aiter (v0.1.1-92-g01aae101) 2025-09-07T07:51:20.6164675Z 299e5928955cc62af9968370293b916f5130916f third_party/benchmark (v1.9.3) 2025-09-07T07:51:20.6248941Z 7fe50dc3da2069d6645d9deb8c017a876472a977 third_party/composable_kernel (rocm-6.4.3-459-g7fe50dc3d) 2025-09-07T07:51:20.6390258Z 89c932f313c6437c38f2982869beacc89c2f2246 third_party/cpp-httplib (v0.26.0) 2025-09-07T07:51:20.6514836Z 5e3d2445e6a84d9599bee2bf78edbb4d80865e1d third_party/cpuinfo (5e3d244) 2025-09-07T07:51:20.6554567Z f937055efc6d414d11f4c6577e3977fe74f35fb6 third_party/cudnn_frontend (v0.5-52-gf937055) 2025-09-07T07:51:20.6655816Z e51efbfe18fe4f4cbb66ab814c55bf4aa0185491 third_party/cutlass (v4.1.0) 2025-09-07T07:51:20.6717502Z 4b39c551efe15e6bbade20565b0ceb2d8ce3352d third_party/fbgemm (v1.3.0-rc1-342-g4b39c551) 2025-09-07T07:51:20.6809146Z 979702c87a8713a8e0a5e9fee122b90d2ef13be5 third_party/flash-attention (v2.7.4) 2025-09-07T07:51:20.6842724Z a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757 third_party/flatbuffers (v24.12.23) 2025-09-07T07:51:20.7268614Z 40626af88bd7df9a5fb80be7b25ac85b122d6c21 third_party/fmt (11.2.0) 2025-09-07T07:51:20.7379153Z 3fb5c176c17c765a3492cd2f0321b0dab712f350 third_party/gemmlowp/gemmlowp (remotes/origin/revert-87-master-135-g3fb5c17) 2025-09-07T07:51:20.7507249Z c7b7b022c124d9643957d9bd55f57ac59fce8fa2 third_party/gloo (remotes/origin/gh/c-p-i-o/1/base-33-gc7b7b02) 2025-09-07T07:51:20.7753802Z 52eb8108c5bdec04579160ae17225d66034bd723 third_party/googletest (release-1.8.0-3544-g52eb8108) 2025-09-07T07:51:20.7839324Z 719d8e6cd7f7a0e01b155657526d693acf97c2b3 third_party/ideep (pytorch-rls-v3.7.1) 2025-09-07T07:51:20.7903527Z dec1d23ca65ab069d225dfe40dea14f455170959 third_party/ittapi (v3.25.5) 2025-09-07T07:51:20.8182934Z 5e7501833f1021ce6f618572d3baf657b6319658 third_party/kineto (remotes/origin/sraikund/test-98-g5e75018) 2025-09-07T07:51:20.8210667Z cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7 third_party/kleidiai (v1.8.0) 2025-09-07T07:51:20.8236255Z fbd8b99c2b828428947d70fdc046bb55609be93e third_party/mimalloc (v2.2.4) 2025-09-07T07:51:20.8263363Z 55f93686c01528224f448c19128836e7df245f72 third_party/nlohmann (v3.12.0) 2025-09-07T07:51:20.8613807Z e709452ef2bbc1d113faf678c24e6d3467696e83 third_party/onnx (v1.18.0) 2025-09-07T07:51:20.8640289Z a799f4aed9c94b765dcdaabaeab7d5e7e2310878 third_party/opentelemetry-cpp (v1.14.2) 2025-09-07T07:51:20.8670188Z 0fa0ef591e38c2758e3184c6c23e497b9f732ffa third_party/pocketfft (release_for_eigen-40-g0fa0ef5) 2025-09-07T07:51:20.9047690Z d1eca4e4b421cd2997495c4b4e65cea6be4e9b8a third_party/protobuf (v3.7.0-rc.2-1279-gd1eca4e4b) 2025-09-07T07:51:20.9134143Z 072586a71b55b7f8c584153d223e95687148a900 third_party/psimd (heads/master) 2025-09-07T07:51:20.9194119Z 4fe0e1e183925bf8cfa6aae24237e724a96479b8 third_party/pthreadpool (0.1-144-g4fe0e1e) 2025-09-07T07:51:20.9220605Z f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8 third_party/pybind11 (v3.0.1) 2025-09-07T07:51:20.9303573Z f45429b087dd7d5bc78bb40dc7cf06425c252d67 third_party/python-peachpy (remotes/origin/pre-generated) 2025-09-07T07:51:20.9386278Z 5a1d179df9cf652951b59010a2d2075372d67f68 third_party/sleef (3.8) 2025-09-07T07:51:20.9459551Z af0118d13e52f5a08841464a768e01a0bf3e3075 third_party/tensorpipe (heads/main) 2025-09-07T07:51:20.9470623Z ##[group]Cleaning the repository 2025-09-07T07:51:20.9474735Z [command]/usr/bin/git clean -ffdx 2025-09-07T07:51:21.0993893Z [command]/usr/bin/git reset --hard HEAD 2025-09-07T07:51:21.7065476Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:51:21.7087914Z ##[endgroup] 2025-09-07T07:51:21.7090100Z ##[group]Disabling automatic garbage collection 2025-09-07T07:51:21.7095893Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:51:21.7264539Z ##[endgroup] 2025-09-07T07:51:21.7264977Z ##[group]Setting up auth 2025-09-07T07:51:21.7271138Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:51:21.7302626Z [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' || :" 2025-09-07T07:51:21.7539343Z Entering 'android/libs/fbjni' 2025-09-07T07:51:21.7582456Z Entering 'third_party/FP16' 2025-09-07T07:51:21.7625649Z Entering 'third_party/FXdiv' 2025-09-07T07:51:21.7669724Z Entering 'third_party/NNPACK' 2025-09-07T07:51:21.7712588Z Entering 'third_party/NVTX' 2025-09-07T07:51:21.7757452Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:21.7801898Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:21.7862379Z Entering 'third_party/aiter' 2025-09-07T07:51:21.7907689Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:21.7959249Z Entering 'third_party/benchmark' 2025-09-07T07:51:21.8003714Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:21.8055769Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:21.8099366Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:21.8143882Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:21.8187372Z Entering 'third_party/cutlass' 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Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:21.8883614Z Entering 'third_party/gloo' 2025-09-07T07:51:21.8926723Z Entering 'third_party/googletest' 2025-09-07T07:51:21.8970031Z Entering 'third_party/ideep' 2025-09-07T07:51:21.9012164Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:21.9063334Z Entering 'third_party/ittapi' 2025-09-07T07:51:21.9107161Z Entering 'third_party/kineto' 2025-09-07T07:51:21.9151158Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:21.9192963Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:21.9237356Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:21.9280939Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:21.9323982Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:21.9367263Z Entering 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Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:22.0400813Z Entering 'third_party/pocketfft' 2025-09-07T07:51:22.0443225Z Entering 'third_party/protobuf' 2025-09-07T07:51:22.0490891Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:22.0532393Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:22.0577816Z Entering 'third_party/psimd' 2025-09-07T07:51:22.0621791Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:22.0666022Z Entering 'third_party/pybind11' 2025-09-07T07:51:22.0707808Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:22.0750558Z Entering 'third_party/sleef' 2025-09-07T07:51:22.0793833Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:22.0837189Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:22.1818915Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:22.1861059Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:22.1903124Z Entering 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http.https://github.com/.extraheader 2025-09-07T07:51:22.3032647Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:22.3058512Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3127610Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:22.3152967Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3216009Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:22.3241228Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3298885Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:22.3324454Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3358644Z Entering 'third_party/cutlass' 2025-09-07T07:51:22.3383481Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3436834Z Entering 'third_party/fbgemm' 2025-09-07T07:51:22.3462454Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3517125Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:22.3540929Z http.https://github.com/.extraheader 2025-09-07T07:51:22.3604371Z Entering 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http.https://github.com/.extraheader 2025-09-07T07:51:22.5763470Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:22.5787085Z http.https://github.com/.extraheader 2025-09-07T07:51:22.5850469Z Entering 'third_party/ittapi' 2025-09-07T07:51:22.5875966Z http.https://github.com/.extraheader 2025-09-07T07:51:22.5955222Z Entering 'third_party/kineto' 2025-09-07T07:51:22.5979912Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6027526Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:22.6051246Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6101807Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:22.6126562Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6163174Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:22.6188371Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6324336Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:22.6350163Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6474868Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:22.6499532Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6547782Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:22.6571748Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6622228Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:22.6646515Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6698999Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:22.6723263Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6759617Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:22.6782713Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6881070Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:22.6904971Z http.https://github.com/.extraheader 2025-09-07T07:51:22.6954979Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:22.6978525Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7054252Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:22.7078172Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7140611Z Entering 'third_party/kleidiai' 2025-09-07T07:51:22.7166264Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7205847Z Entering 'third_party/mimalloc' 2025-09-07T07:51:22.7231887Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7289332Z Entering 'third_party/nlohmann' 2025-09-07T07:51:22.7314503Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7448326Z Entering 'third_party/onnx' 2025-09-07T07:51:22.7473960Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7542190Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:22.7566926Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7606394Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:22.7631562Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7663910Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:22.7687306Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7766170Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:22.7789960Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7888181Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:22.7912075Z http.https://github.com/.extraheader 2025-09-07T07:51:22.7953769Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:22.7978849Z http.https://github.com/.extraheader 2025-09-07T07:51:22.8019055Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:22.8042953Z http.https://github.com/.extraheader 2025-09-07T07:51:22.8099847Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:22.8122703Z http.https://github.com/.extraheader 2025-09-07T07:51:22.8174371Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:22.8197852Z http.https://github.com/.extraheader 2025-09-07T07:51:22.8243074Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:22.8267077Z http.https://github.com/.extraheader 2025-09-07T07:51:22.8326913Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:22.8350774Z http.https://github.com/.extraheader 2025-09-07T07:51:22.8465418Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:22.8488660Z http.https://github.com/.extraheader 2025-09-07T07:51:22.9645560Z Entering 'third_party/pocketfft' 2025-09-07T07:51:22.9671610Z http.https://github.com/.extraheader 2025-09-07T07:51:22.9758991Z Entering 'third_party/protobuf' 2025-09-07T07:51:22.9784255Z http.https://github.com/.extraheader 2025-09-07T07:51:22.9861543Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:22.9885216Z http.https://github.com/.extraheader 2025-09-07T07:51:23.0137807Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:23.0162181Z http.https://github.com/.extraheader 2025-09-07T07:51:23.0200777Z Entering 'third_party/psimd' 2025-09-07T07:51:23.0225551Z http.https://github.com/.extraheader 2025-09-07T07:51:23.0783088Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:23.0808299Z http.https://github.com/.extraheader 2025-09-07T07:51:23.1529964Z Entering 'third_party/pybind11' 2025-09-07T07:51:23.1554575Z http.https://github.com/.extraheader 2025-09-07T07:51:23.1638800Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:23.1663475Z http.https://github.com/.extraheader 2025-09-07T07:51:23.1867413Z Entering 'third_party/sleef' 2025-09-07T07:51:23.1892362Z http.https://github.com/.extraheader 2025-09-07T07:51:23.2044098Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:23.2068922Z http.https://github.com/.extraheader 2025-09-07T07:51:23.2168963Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:23.2192560Z http.https://github.com/.extraheader 2025-09-07T07:51:23.2337323Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:23.2361676Z http.https://github.com/.extraheader 2025-09-07T07:51:23.2534953Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:23.2557936Z http.https://github.com/.extraheader 2025-09-07T07:51:23.2688731Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:23.2714033Z http.https://github.com/.extraheader 2025-09-07T07:51:23.2861759Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:23.2885148Z http.https://github.com/.extraheader 2025-09-07T07:51:23.3153729Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:51:23.3567651Z ##[endgroup] 2025-09-07T07:51:23.3568078Z ##[group]Fetching the repository 2025-09-07T07:51:23.3575559Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:51:24.2162768Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:51:24.2186347Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:24.2190952Z ##[endgroup] 2025-09-07T07:51:24.2191370Z ##[group]Determining the checkout info 2025-09-07T07:51:24.2192204Z ##[endgroup] 2025-09-07T07:51:24.2195696Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:51:24.3756655Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:51:24.3816063Z ##[group]Checking out the ref 2025-09-07T07:51:24.3820674Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:24.4583169Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:51:24.4595501Z ##[endgroup] 2025-09-07T07:51:24.4596277Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:51:24.4600531Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:51:24.4824256Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:51:24.4851972Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:51:24.4939615Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:51:24.5038709Z ##[endgroup] 2025-09-07T07:51:24.5039197Z ##[group]Fetching submodules 2025-09-07T07:51:24.5042461Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:51:24.5381943Z Synchronizing submodule url for 'android/libs/fbjni' 2025-09-07T07:51:24.5520910Z Synchronizing submodule url for 'third_party/FP16' 2025-09-07T07:51:24.5745070Z Synchronizing submodule url for 'third_party/FXdiv' 2025-09-07T07:51:24.5885996Z Synchronizing submodule url for 'third_party/NNPACK' 2025-09-07T07:51:24.6046387Z Synchronizing submodule url for 'third_party/NVTX' 2025-09-07T07:51:24.6127472Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:24.6180547Z Synchronizing submodule url for 'third_party/XNNPACK' 2025-09-07T07:51:24.6321681Z Synchronizing submodule url for 'third_party/aiter' 2025-09-07T07:51:24.6574325Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:24.6677025Z Synchronizing submodule url for 'third_party/benchmark' 2025-09-07T07:51:24.6796657Z Synchronizing submodule url for 'third_party/composable_kernel' 2025-09-07T07:51:24.6948490Z Synchronizing submodule url for 'third_party/cpp-httplib' 2025-09-07T07:51:24.7051710Z Synchronizing submodule url for 'third_party/cpuinfo' 2025-09-07T07:51:24.7181852Z Synchronizing submodule url for 'third_party/cudnn_frontend' 2025-09-07T07:51:24.7385435Z Synchronizing submodule url for 'third_party/cutlass' 2025-09-07T07:51:24.7574187Z Synchronizing submodule url for 'third_party/fbgemm' 2025-09-07T07:51:24.7762550Z Synchronizing submodule url for 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:24.7873876Z Synchronizing submodule url for 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:24.8047018Z Synchronizing submodule url for 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:24.8239397Z Synchronizing submodule url for 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:24.8431484Z Synchronizing submodule url for 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:24.8583328Z Synchronizing submodule url for 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:24.8737707Z Synchronizing submodule url for 'third_party/fbgemm/external/json' 2025-09-07T07:51:24.8863444Z Synchronizing submodule url for 'third_party/flash-attention' 2025-09-07T07:51:24.9102812Z Synchronizing submodule url for 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:24.9252271Z Synchronizing submodule url for 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:24.9369472Z Synchronizing submodule url for 'third_party/flatbuffers' 2025-09-07T07:51:25.0951052Z Synchronizing submodule url for 'third_party/fmt' 2025-09-07T07:51:25.1004581Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:25.1106399Z Synchronizing submodule url for 'third_party/gloo' 2025-09-07T07:51:25.1198629Z Synchronizing submodule url for 'third_party/googletest' 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Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:25.2537073Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:25.2619947Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:25.2702407Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:25.2724811Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:25.2748048Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:25.2769805Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:25.2793715Z Synchronizing submodule url for 'third_party/kleidiai' 2025-09-07T07:51:25.2819141Z Synchronizing submodule url for 'third_party/mimalloc' 2025-09-07T07:51:25.2841781Z Synchronizing submodule url for 'third_party/nlohmann' 2025-09-07T07:51:25.2866482Z Synchronizing submodule url for 'third_party/onnx' 2025-09-07T07:51:25.2906649Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:25.2932421Z Synchronizing submodule url for 'third_party/opentelemetry-cpp' 2025-09-07T07:51:25.2955426Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:25.2975871Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:25.2996604Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:25.3017594Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:25.3039344Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:25.3059982Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:25.3080722Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:25.3101433Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:25.3123473Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:25.3147547Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:25.3192334Z Synchronizing submodule url for 'third_party/pocketfft' 2025-09-07T07:51:25.3215271Z Synchronizing submodule url for 'third_party/protobuf' 2025-09-07T07:51:25.3239774Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:25.3259572Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:25.3283639Z Synchronizing submodule url for 'third_party/psimd' 2025-09-07T07:51:25.3307094Z Synchronizing submodule url for 'third_party/pthreadpool' 2025-09-07T07:51:25.3329317Z Synchronizing submodule url for 'third_party/pybind11' 2025-09-07T07:51:25.3352712Z Synchronizing submodule url for 'third_party/python-peachpy' 2025-09-07T07:51:25.3375434Z Synchronizing submodule url for 'third_party/sleef' 2025-09-07T07:51:25.3398753Z Synchronizing submodule url for 'third_party/tensorpipe' 2025-09-07T07:51:25.3420362Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:25.3440410Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:25.3461059Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:25.3481525Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:25.3501980Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:25.3535614Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:51:25.3914983Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:51:25.4040132Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:51:25.4131853Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:51:25.4373189Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:51:25.5348771Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:51:25.5739699Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:51:26.5479499Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:51:26.7934066Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:51:27.1480558Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:51:27.1700503Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:51:27.6012182Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:51:27.6691278Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:51:27.8174022Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:51:27.8698957Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:51:28.8678935Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:51:29.0167535Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:51:29.0867387Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:51:29.3995451Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:51:29.5464662Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:51:29.8466071Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:51:29.8876900Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:51:29.9009892Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:51:30.0486401Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:51:30.1359899Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:51:30.3609355Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:51:30.4909113Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:51:30.8030938Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:51:30.8348970Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:51:30.8798198Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:51:30.9026687Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:51:30.9426634Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:51:30.9568637Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:51:31.6252603Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:51:31.6477116Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:51:31.7513657Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:51:31.9279219Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:51:32.1412424Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:51:32.1575329Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:51:32.1916863Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:51:32.2058363Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:51:32.2156712Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:51:32.2317949Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:51:32.2707042Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:51:32.3703493Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:51:32.4499217Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:51:32.4802875Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:51:32.5186756Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:51:32.5671246Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:51:32.6284937Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:51:32.7586829Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:51:32.8816027Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:51:32.9174891Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:51:32.9881568Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:51:33.0068052Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:51:33.0452232Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:51:33.0588029Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:51:33.1761967Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:51:33.1926931Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:51:33.2071617Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:51:33.2209967Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:51:33.4228317Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T07:51:33.4624459Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T07:51:33.5724855Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T07:51:33.5858622Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T07:51:33.9316262Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T07:51:33.9461111Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T07:51:33.9907235Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T07:51:34.0008503Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900' 2025-09-07T07:51:34.0161409Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8' 2025-09-07T07:51:34.0538600Z Submodule path 'third_party/pybind11': checked out 'f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8' 2025-09-07T07:51:34.1045133Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67' 2025-09-07T07:51:34.1600194Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68' 2025-09-07T07:51:34.1828223Z Submodule path 'third_party/tensorpipe': checked out 'af0118d13e52f5a08841464a768e01a0bf3e3075' 2025-09-07T07:51:34.2214333Z Submodule path 'third_party/tensorpipe/third_party/googletest': checked out 'aee0f9d9b5b87796ee8a0ab26b7587ec30e8858e' 2025-09-07T07:51:34.2367939Z Submodule path 'third_party/tensorpipe/third_party/libnop': checked out '910b55815be16109f04f4180e9adee14fb4ce281' 2025-09-07T07:51:34.2934116Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '5152db2cbfeb5582e9c27c5ea1dba2cd9e10759b' 2025-09-07T07:51:34.3189843Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef' 2025-09-07T07:51:34.3437254Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5' 2025-09-07T07:51:34.3476483Z [command]/usr/bin/git submodule foreach --recursive git config --local gc.auto 0 2025-09-07T07:51:34.3714445Z Entering 'android/libs/fbjni' 2025-09-07T07:51:34.3752783Z Entering 'third_party/FP16' 2025-09-07T07:51:34.3790458Z Entering 'third_party/FXdiv' 2025-09-07T07:51:34.3833039Z Entering 'third_party/NNPACK' 2025-09-07T07:51:34.3871648Z Entering 'third_party/NVTX' 2025-09-07T07:51:34.3912303Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:34.3949481Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:34.4005739Z Entering 'third_party/aiter' 2025-09-07T07:51:34.4046467Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:34.4093721Z Entering 'third_party/benchmark' 2025-09-07T07:51:34.4132166Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:34.4180945Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:34.4219702Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:34.4258451Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:34.4299959Z Entering 'third_party/cutlass' 2025-09-07T07:51:34.4351954Z Entering 'third_party/fbgemm' 2025-09-07T07:51:34.4392609Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:34.4428764Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:34.4473231Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:34.4512150Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:34.4559425Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:34.4597287Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:34.4634276Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:34.4674223Z Entering 'third_party/flash-attention' 2025-09-07T07:51:34.4713850Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:34.4757380Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:34.4804706Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:34.4846592Z Entering 'third_party/fmt' 2025-09-07T07:51:34.4885065Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:34.4923875Z Entering 'third_party/gloo' 2025-09-07T07:51:34.4962530Z Entering 'third_party/googletest' 2025-09-07T07:51:34.5000925Z Entering 'third_party/ideep' 2025-09-07T07:51:34.5037677Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:34.5082708Z Entering 'third_party/ittapi' 2025-09-07T07:51:34.5121076Z Entering 'third_party/kineto' 2025-09-07T07:51:34.5159382Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:34.5196268Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:34.5234576Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:34.5270943Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:34.5310078Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:34.5347149Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:34.5387649Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:34.5426177Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:34.5464137Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:34.5503190Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:34.5545214Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:34.5581202Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:34.5619089Z Entering 'third_party/kleidiai' 2025-09-07T07:51:34.5660247Z Entering 'third_party/mimalloc' 2025-09-07T07:51:34.5700158Z Entering 'third_party/nlohmann' 2025-09-07T07:51:34.5742252Z Entering 'third_party/onnx' 2025-09-07T07:51:34.5799792Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:34.5842773Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:34.5883458Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:34.5923220Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:34.5960508Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:34.5997740Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:34.6035567Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:34.6074692Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:34.6113478Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:34.6149906Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:34.6188517Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:34.6229115Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:34.6289022Z Entering 'third_party/pocketfft' 2025-09-07T07:51:34.6331244Z Entering 'third_party/protobuf' 2025-09-07T07:51:34.6374988Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:34.6411609Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:34.6452437Z Entering 'third_party/psimd' 2025-09-07T07:51:34.6491835Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:34.6530946Z Entering 'third_party/pybind11' 2025-09-07T07:51:34.6571655Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:34.6609446Z Entering 'third_party/sleef' 2025-09-07T07:51:34.6649502Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:34.6689856Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:34.6725676Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:34.6761138Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:34.6798342Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:34.6832985Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:34.6883143Z ##[endgroup] 2025-09-07T07:51:34.6883934Z ##[group]Persisting credentials for submodules 2025-09-07T07:51:34.6889845Z [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' || :" 2025-09-07T07:51:34.7123710Z Entering 'android/libs/fbjni' 2025-09-07T07:51:34.7147873Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7148516Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7179674Z Entering 'third_party/FP16' 2025-09-07T07:51:34.7205005Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7205656Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7236851Z Entering 'third_party/FXdiv' 2025-09-07T07:51:34.7261039Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7261681Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7292143Z Entering 'third_party/NNPACK' 2025-09-07T07:51:34.7317414Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7318052Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7349827Z Entering 'third_party/NVTX' 2025-09-07T07:51:34.7374849Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7375477Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7410150Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:34.7435344Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7435992Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7467691Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:34.7493306Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7493821Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7540920Z Entering 'third_party/aiter' 2025-09-07T07:51:34.7566161Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7566810Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7601107Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:34.7626199Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7626827Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7666295Z Entering 'third_party/benchmark' 2025-09-07T07:51:34.7691694Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7692344Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7723819Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:34.7749378Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7750028Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7789760Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:34.7815952Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7816581Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7848396Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:34.7874004Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7874638Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7907735Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:34.7931555Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7932549Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7964900Z Entering 'third_party/cutlass' 2025-09-07T07:51:34.7990347Z url.https://github.com/.insteadof 2025-09-07T07:51:34.7991018Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8034214Z Entering 'third_party/fbgemm' 2025-09-07T07:51:34.8059603Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8060255Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8096120Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:34.8120047Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8120673Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8151146Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:34.8176111Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8176741Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8219213Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:34.8244038Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8244717Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8275583Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:34.8300283Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8300927Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8343831Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:34.8368576Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8369195Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8401847Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:34.8426183Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8426798Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8458317Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:34.8482907Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8483540Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8521056Z Entering 'third_party/flash-attention' 2025-09-07T07:51:34.8547545Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8548191Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8582215Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:34.8605865Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8606499Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8646166Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:34.8670420Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8671050Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8714144Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:34.8740555Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8741197Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8776359Z Entering 'third_party/fmt' 2025-09-07T07:51:34.8801503Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8802147Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8835156Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:34.8860038Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8860678Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8894121Z Entering 'third_party/gloo' 2025-09-07T07:51:34.8919265Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8919906Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8950192Z Entering 'third_party/googletest' 2025-09-07T07:51:34.8975413Z url.https://github.com/.insteadof 2025-09-07T07:51:34.8976057Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9008925Z Entering 'third_party/ideep' 2025-09-07T07:51:34.9033918Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9034568Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9069692Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:34.9093558Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9094197Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9133837Z Entering 'third_party/ittapi' 2025-09-07T07:51:34.9158664Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9159307Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9189462Z Entering 'third_party/kineto' 2025-09-07T07:51:34.9215651Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9216682Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9248226Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:34.9272512Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9273170Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9303691Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:34.9327099Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9327713Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9360145Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:34.9385104Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9385739Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9417073Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:34.9441373Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9442016Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9474382Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:34.9499086Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9499730Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9529654Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:34.9554103Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9554743Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9590972Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:34.9615391Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9616026Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9647197Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:34.9671301Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9671979Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9702864Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:34.9727455Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9727973Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9760879Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:34.9785769Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9786426Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9818909Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:34.9842839Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9843484Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9877742Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:34.9902416Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9903035Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9935390Z Entering 'third_party/kleidiai' 2025-09-07T07:51:34.9961001Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9961604Z url.https://github.com/.insteadof 2025-09-07T07:51:34.9993336Z Entering 'third_party/mimalloc' 2025-09-07T07:51:35.0020047Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0020697Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0055218Z Entering 'third_party/nlohmann' 2025-09-07T07:51:35.0080578Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0081217Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0113828Z Entering 'third_party/onnx' 2025-09-07T07:51:35.0141068Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0141633Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0192809Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:35.0217885Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0218506Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0253433Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:35.0278240Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0278877Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0311878Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:35.0336165Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0337207Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0372316Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:35.0785022Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0785697Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0825640Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:35.0850700Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0851349Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0895177Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:35.0920815Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0921463Z url.https://github.com/.insteadof 2025-09-07T07:51:35.0975199Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:35.0999786Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1000446Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1044266Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:35.1069629Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1070256Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1101933Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:35.1126840Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1127480Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1165901Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:35.1189973Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1190612Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1226182Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:35.1250296Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1250677Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1283514Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:35.1308564Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1308949Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1396030Z Entering 'third_party/pocketfft' 2025-09-07T07:51:35.1422211Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1422853Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1473497Z Entering 'third_party/protobuf' 2025-09-07T07:51:35.1500995Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1501348Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1536960Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:35.1560913Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1561269Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1592469Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:35.1617244Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1617589Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1651440Z Entering 'third_party/psimd' 2025-09-07T07:51:35.1676407Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1676805Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1709041Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:35.1734045Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1734447Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1764460Z Entering 'third_party/pybind11' 2025-09-07T07:51:35.1789332Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1789683Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1822045Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:35.1846035Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1846415Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1876394Z Entering 'third_party/sleef' 2025-09-07T07:51:35.1902114Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1902490Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1934139Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:35.1958186Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1958556Z url.https://github.com/.insteadof 2025-09-07T07:51:35.1991311Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:35.2016423Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2016792Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2047082Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:35.2070933Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2071294Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2102313Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:35.2126413Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2126802Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2161196Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:35.2185678Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2186031Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2216737Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:35.2240437Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2240800Z url.https://github.com/.insteadof 2025-09-07T07:51:35.2291407Z [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" 2025-09-07T07:51:35.2528005Z Entering 'android/libs/fbjni' 2025-09-07T07:51:35.2566946Z file:/home/david/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:51:35.2584813Z Entering 'third_party/FP16' 2025-09-07T07:51:35.2622496Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:51:35.2641547Z Entering 'third_party/FXdiv' 2025-09-07T07:51:35.2679121Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:51:35.2698196Z Entering 'third_party/NNPACK' 2025-09-07T07:51:35.2738670Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:51:35.2757500Z Entering 'third_party/NVTX' 2025-09-07T07:51:35.2796070Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:51:35.2815623Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:35.2853055Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:51:35.2872688Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:35.2912010Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:51:35.2947228Z Entering 'third_party/aiter' 2025-09-07T07:51:35.2986305Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:51:35.3006149Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:35.3045375Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:51:35.3074647Z Entering 'third_party/benchmark' 2025-09-07T07:51:35.3112000Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:51:35.3131334Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:35.3169974Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T07:51:35.3196431Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:35.3238626Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T07:51:35.3256928Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:35.3294617Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T07:51:35.3313130Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:35.3353158Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T07:51:35.3371523Z Entering 'third_party/cutlass' 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2025-09-07T07:51:35.3960615Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:51:35.3980643Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:35.4017919Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:51:35.4042272Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:35.4078993Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:51:35.4108925Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:35.4151358Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:51:35.4174246Z Entering 'third_party/fmt' 2025-09-07T07:51:35.4212660Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 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Entering 'third_party/ittapi' 2025-09-07T07:51:35.4563834Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:51:35.4583016Z Entering 'third_party/kineto' 2025-09-07T07:51:35.4622601Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:51:35.4640942Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:35.4678705Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:51:35.4696537Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:35.4735282Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:51:35.4754291Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 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file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T07:51:35.4981249Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:35.5018943Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T07:51:35.5036735Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:35.5074498Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:51:35.5092219Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:35.5130585Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T07:51:35.5149023Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:35.5187667Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:51:35.5207331Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:35.5244552Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:51:35.5262195Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:35.5301501Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:51:35.5321279Z Entering 'third_party/kleidiai' 2025-09-07T07:51:35.5361948Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:51:35.5381556Z Entering 'third_party/mimalloc' 2025-09-07T07:51:35.5420326Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:51:35.5439598Z Entering 'third_party/nlohmann' 2025-09-07T07:51:35.5478630Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:51:35.5500667Z Entering 'third_party/onnx' 2025-09-07T07:51:35.5541831Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:51:35.5578842Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:35.5616892Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:51:35.5637645Z Entering 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file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:51:35.7091190Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:35.7129685Z file:/home/david/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/modules/tools/clang/config remote.origin.url 2025-09-07T07:51:35.7365259Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'git@github.com:' 2025-09-07T07:51:35.7606481Z Entering 'android/libs/fbjni' 2025-09-07T07:51:35.7643720Z Entering 'third_party/FP16' 2025-09-07T07:51:35.7681366Z Entering 'third_party/FXdiv' 2025-09-07T07:51:35.7718704Z Entering 'third_party/NNPACK' 2025-09-07T07:51:35.7755269Z Entering 'third_party/NVTX' 2025-09-07T07:51:35.7794081Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:35.7835861Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:35.7891115Z Entering 'third_party/aiter' 2025-09-07T07:51:35.7930053Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:35.7977988Z Entering 'third_party/benchmark' 2025-09-07T07:51:35.8017411Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:35.8065688Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:35.8103948Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:35.8143221Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:35.8181324Z Entering 'third_party/cutlass' 2025-09-07T07:51:35.8229737Z Entering 'third_party/fbgemm' 2025-09-07T07:51:35.8270703Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:35.8307565Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:35.8354627Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:35.8391990Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:35.8439552Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:35.8476571Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:35.8513186Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:35.8554615Z Entering 'third_party/flash-attention' 2025-09-07T07:51:35.8595101Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:35.8638911Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:35.8687129Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:35.8728528Z Entering 'third_party/fmt' 2025-09-07T07:51:35.8765766Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:35.8804719Z Entering 'third_party/gloo' 2025-09-07T07:51:35.8842694Z Entering 'third_party/googletest' 2025-09-07T07:51:35.8880870Z Entering 'third_party/ideep' 2025-09-07T07:51:35.8921427Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:35.8966190Z Entering 'third_party/ittapi' 2025-09-07T07:51:35.9003270Z Entering 'third_party/kineto' 2025-09-07T07:51:35.9041616Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:35.9077111Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:35.9114087Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:35.9150953Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:35.9187465Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:35.9223142Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:35.9261952Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:35.9299291Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:35.9335906Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:35.9373264Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:35.9410634Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:35.9445787Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:35.9483021Z Entering 'third_party/kleidiai' 2025-09-07T07:51:35.9521223Z Entering 'third_party/mimalloc' 2025-09-07T07:51:35.9558355Z Entering 'third_party/nlohmann' 2025-09-07T07:51:35.9597736Z Entering 'third_party/onnx' 2025-09-07T07:51:35.9654155Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:35.9693324Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:35.9732511Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:35.9767949Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:35.9803120Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:35.9837841Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:35.9874361Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:35.9909859Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:35.9946030Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:35.9981012Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:36.0018729Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:36.0056482Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:36.0113488Z Entering 'third_party/pocketfft' 2025-09-07T07:51:36.0152025Z Entering 'third_party/protobuf' 2025-09-07T07:51:36.0193592Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:36.0229910Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:36.0269541Z Entering 'third_party/psimd' 2025-09-07T07:51:36.0309326Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:36.0347867Z Entering 'third_party/pybind11' 2025-09-07T07:51:36.0388155Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:36.0426955Z Entering 'third_party/sleef' 2025-09-07T07:51:36.0463914Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:36.0500739Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:36.0536177Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:36.0571545Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:36.0607018Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:36.0640846Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:36.0697356Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-09-07T07:51:36.0929710Z Entering 'android/libs/fbjni' 2025-09-07T07:51:36.0968718Z Entering 'third_party/FP16' 2025-09-07T07:51:36.1007585Z Entering 'third_party/FXdiv' 2025-09-07T07:51:36.1046246Z Entering 'third_party/NNPACK' 2025-09-07T07:51:36.1084337Z Entering 'third_party/NVTX' 2025-09-07T07:51:36.1122664Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:51:36.1161044Z Entering 'third_party/XNNPACK' 2025-09-07T07:51:36.1215421Z Entering 'third_party/aiter' 2025-09-07T07:51:36.1254610Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:51:36.1300260Z Entering 'third_party/benchmark' 2025-09-07T07:51:36.1337581Z Entering 'third_party/composable_kernel' 2025-09-07T07:51:36.1384614Z Entering 'third_party/cpp-httplib' 2025-09-07T07:51:36.1422365Z Entering 'third_party/cpuinfo' 2025-09-07T07:51:36.1460149Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:51:36.1498608Z Entering 'third_party/cutlass' 2025-09-07T07:51:36.1546127Z Entering 'third_party/fbgemm' 2025-09-07T07:51:36.1585859Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:51:36.1621964Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:51:36.1664522Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:51:36.1700301Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:51:36.1747649Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:51:36.1783289Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:51:36.1819205Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:51:36.1858492Z Entering 'third_party/flash-attention' 2025-09-07T07:51:36.1900487Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:51:36.1943496Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:51:36.1989194Z Entering 'third_party/flatbuffers' 2025-09-07T07:51:36.2029329Z Entering 'third_party/fmt' 2025-09-07T07:51:36.2066157Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:51:36.2103555Z Entering 'third_party/gloo' 2025-09-07T07:51:36.2141151Z Entering 'third_party/googletest' 2025-09-07T07:51:36.2179445Z Entering 'third_party/ideep' 2025-09-07T07:51:36.2217671Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:51:36.2262040Z Entering 'third_party/ittapi' 2025-09-07T07:51:36.2300898Z Entering 'third_party/kineto' 2025-09-07T07:51:36.2339052Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:51:36.2374825Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:51:36.2414214Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:51:36.2450143Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:51:36.2487237Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:51:36.2523047Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:51:36.2562300Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:51:36.2605523Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:51:36.2642612Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:51:36.2681014Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:51:36.2720000Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:51:36.2757021Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:51:36.2795603Z Entering 'third_party/kleidiai' 2025-09-07T07:51:36.2834429Z Entering 'third_party/mimalloc' 2025-09-07T07:51:36.2873275Z Entering 'third_party/nlohmann' 2025-09-07T07:51:36.2913165Z Entering 'third_party/onnx' 2025-09-07T07:51:36.2969583Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:51:36.3009845Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:51:36.3453088Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:51:36.3488534Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:51:36.3525782Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:51:36.3561151Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:51:36.3598018Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:51:36.3634648Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:51:36.3672143Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:51:36.3708002Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:51:36.3747759Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:51:36.3787200Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:51:36.3847679Z Entering 'third_party/pocketfft' 2025-09-07T07:51:36.3886694Z Entering 'third_party/protobuf' 2025-09-07T07:51:36.3928985Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:51:36.3974299Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:51:36.4021842Z Entering 'third_party/psimd' 2025-09-07T07:51:36.4060647Z Entering 'third_party/pthreadpool' 2025-09-07T07:51:36.4100042Z Entering 'third_party/pybind11' 2025-09-07T07:51:36.4143119Z Entering 'third_party/python-peachpy' 2025-09-07T07:51:36.4183018Z Entering 'third_party/sleef' 2025-09-07T07:51:36.4222006Z Entering 'third_party/tensorpipe' 2025-09-07T07:51:36.4261789Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:51:36.4297780Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:51:36.4333785Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:51:36.4371306Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:51:36.4416282Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:51:36.4470696Z ##[endgroup] 2025-09-07T07:51:36.4506959Z [command]/usr/bin/git log -1 --format=%H 2025-09-07T07:51:36.4530142Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:36.4718312Z Prepare all required actions 2025-09-07T07:51:36.4718888Z Getting action download info 2025-09-07T07:51:36.7810400Z ##[group]Run ./.github/actions/setup-linux 2025-09-07T07:51:36.7810742Z env: 2025-09-07T07:51:36.7810982Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:36.7811235Z ##[endgroup] 2025-09-07T07:51:36.7849701Z ##[group]Run set -euo pipefail 2025-09-07T07:51:36.7850089Z set -euo pipefail 2025-09-07T07:51:36.7850377Z function get_ec2_metadata() { 2025-09-07T07:51:36.7850767Z  # Pulled from instance metadata endpoint for EC2 2025-09-07T07:51:36.7851420Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-09-07T07:51:36.7852007Z  category=$1 2025-09-07T07:51:36.7852378Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-09-07T07:51:36.7853007Z  runner_name_str=i-01a21955dc3821a00-1004 2025-09-07T07:51:36.7853433Z  if [[ -f /.inarc ]]; then 2025-09-07T07:51:36.7853792Z  echo "ARC Runner, no info on ec2 metadata" 2025-09-07T07:51:36.7854182Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-09-07T07:51:36.7854669Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-09-07T07:51:36.7855361Z  else 2025-09-07T07:51:36.7856259Z  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}" 2025-09-07T07:51:36.7857203Z  fi 2025-09-07T07:51:36.7857408Z } 2025-09-07T07:51:36.7857676Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-09-07T07:51:36.7858109Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-09-07T07:51:36.7858602Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-09-07T07:51:36.7859021Z echo "system info $(uname -a)" 2025-09-07T07:51:36.7872270Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:36.7872664Z env: 2025-09-07T07:51:36.7872892Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:36.7873159Z ##[endgroup] 2025-09-07T07:51:36.7909855Z ami-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:36.7915173Z instance-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:36.7920437Z instance-type: ARC Runner, no info on ec2 metadata 2025-09-07T07:51:36.7931077Z system info Linux c3fe6811bb8d 6.5.0-1024-aws #24~22.04.1-Ubuntu SMP Thu Jul 18 10:43:12 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux 2025-09-07T07:51:36.7949742Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:51:36.7950702Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:51:36.7962817Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:36.7963209Z env: 2025-09-07T07:51:36.7963420Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:36.7963690Z ##[endgroup] 2025-09-07T07:51:36.8035399Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T07:51:36.8035732Z with: 2025-09-07T07:51:36.8035935Z shell: bash 2025-09-07T07:51:36.8036164Z timeout_minutes: 5 2025-09-07T07:51:36.8036415Z max_attempts: 3 2025-09-07T07:51:36.8036662Z retry_wait_seconds: 30 2025-09-07T07:51:36.8039283Z command: AWS_ACCOUNT_ID=$(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 2025-09-07T07:51:36.8041679Z polling_interval_seconds: 1 2025-09-07T07:51:36.8041964Z warning_on_retry: true 2025-09-07T07:51:36.8042237Z continue_on_error: false 2025-09-07T07:51:36.8042511Z env: 2025-09-07T07:51:36.8042729Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:36.8042991Z AWS_RETRY_MODE: standard 2025-09-07T07:51:36.8043259Z AWS_MAX_ATTEMPTS: 5 2025-09-07T07:51:36.8043526Z AWS_DEFAULT_REGION: us-east-1 2025-09-07T07:51:36.8043810Z ##[endgroup] 2025-09-07T07:51:38.7751492Z 2025-09-07T07:51:38.7752564Z WARNING! Your credentials are stored unencrypted in '/home/david/.docker/config.json'. 2025-09-07T07:51:38.7753291Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:38.7753758Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:38.7754009Z 2025-09-07T07:51:38.7754105Z Login Succeeded 2025-09-07T07:51:38.8847029Z Command completed after 1 attempt(s). 2025-09-07T07:51:38.8906795Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:38.8907361Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:38.8907836Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:51:38.8920914Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:38.8921308Z env: 2025-09-07T07:51:38.8921523Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:38.8921792Z ##[endgroup] 2025-09-07T07:51:38.9002482Z ##[group]Run set +e 2025-09-07T07:51:38.9002782Z set +e 2025-09-07T07:51:38.9003024Z set -x 2025-09-07T07:51:38.9003253Z  2025-09-07T07:51:38.9003491Z PT_DOMAIN=download.pytorch.org 2025-09-07T07:51:38.9004093Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-09-07T07:51:38.9004877Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-09-07T07:51:38.9005445Z # one is returned at random 2025-09-07T07:51:38.9005853Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-09-07T07:51:38.9006231Z  2025-09-07T07:51:38.9006468Z if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:51:38.9006921Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-09-07T07:51:38.9007467Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-09-07T07:51:38.9007863Z  2025-09-07T07:51:38.9008100Z  if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:51:38.9008497Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-09-07T07:51:38.9008871Z  exit 1 2025-09-07T07:51:38.9009111Z  fi 2025-09-07T07:51:38.9009318Z fi 2025-09-07T07:51:38.9009531Z  2025-09-07T07:51:38.9009795Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-09-07T07:51:38.9010173Z  # Clean up any old records first 2025-09-07T07:51:38.9010537Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-09-07T07:51:38.9010870Z fi 2025-09-07T07:51:38.9011098Z  2025-09-07T07:51:38.9011416Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-09-07T07:51:38.9011833Z cat /etc/hosts 2025-09-07T07:51:38.9024122Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:38.9024510Z env: 2025-09-07T07:51:38.9024824Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:38.9025099Z ##[endgroup] 2025-09-07T07:51:38.9053160Z + PT_DOMAIN=download.pytorch.org 2025-09-07T07:51:38.9059133Z ++ dig -4 +short download.pytorch.org 2025-09-07T07:51:38.9060255Z ++ tail -n1 2025-09-07T07:51:38.9158432Z + RESOLVED_IP=3.170.131.53 2025-09-07T07:51:38.9158770Z + '[' -z 3.170.131.53 ']' 2025-09-07T07:51:38.9159071Z + grep -r download.pytorch.org /etc/hosts 2025-09-07T07:51:38.9172405Z + echo '3.170.131.53 download.pytorch.org' 2025-09-07T07:51:38.9173343Z + sudo tee -a /etc/hosts 2025-09-07T07:51:38.9228979Z 3.170.131.53 download.pytorch.org 2025-09-07T07:51:38.9235528Z + cat /etc/hosts 2025-09-07T07:51:38.9243198Z 127.0.0.1 localhost 2025-09-07T07:51:38.9248274Z ::1 localhost ip6-localhost ip6-loopback 2025-09-07T07:51:38.9248668Z fe00:: ip6-localnet 2025-09-07T07:51:38.9248919Z ff00:: ip6-mcastprefix 2025-09-07T07:51:38.9249164Z ff02::1 ip6-allnodes 2025-09-07T07:51:38.9249416Z ff02::2 ip6-allrouters 2025-09-07T07:51:38.9249666Z 172.17.0.2 c3fe6811bb8d 2025-09-07T07:51:38.9249934Z 3.170.131.53 download.pytorch.org 2025-09-07T07:51:38.9271196Z ##[group]Run set +x 2025-09-07T07:51:38.9271485Z set +x 2025-09-07T07:51:38.9271710Z  2025-09-07T07:51:38.9271935Z max_attempts=30 2025-09-07T07:51:38.9272189Z delay=10 2025-09-07T07:51:38.9272422Z attempt=1 2025-09-07T07:51:38.9272660Z  2025-09-07T07:51:38.9272912Z for attempt in $(seq 1 $max_attempts); do 2025-09-07T07:51:38.9273469Z  echo "Attempt $attempt of $max_attempts: Checking if Docker daemon is running..." 2025-09-07T07:51:38.9274003Z  if docker info > /dev/null 2>&1; then 2025-09-07T07:51:38.9274447Z  echo "Docker is running. Proceeding with the next steps" 2025-09-07T07:51:38.9275057Z  exit 0 2025-09-07T07:51:38.9275285Z  else 2025-09-07T07:51:38.9275553Z  echo "Docker is not running yet." 2025-09-07T07:51:38.9275928Z  echo "Retrying in $delay seconds..." 2025-09-07T07:51:38.9276278Z  sleep $delay 2025-09-07T07:51:38.9276528Z  fi 2025-09-07T07:51:38.9276750Z done 2025-09-07T07:51:38.9277108Z echo "Reached maximum attempts to connect to Docker. Exiting." 2025-09-07T07:51:38.9277545Z exit 1 2025-09-07T07:51:38.9290267Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:38.9290664Z env: 2025-09-07T07:51:38.9290890Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:38.9291163Z ##[endgroup] 2025-09-07T07:51:38.9330994Z Attempt 1 of 30: Checking if Docker daemon is running... 2025-09-07T07:51:38.9724084Z Docker is running. Proceeding with the next steps 2025-09-07T07:51:38.9889433Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-09-07T07:51:38.9889950Z with: 2025-09-07T07:51:38.9890907Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:38.9891979Z use-custom-docker-registry: true 2025-09-07T07:51:38.9892290Z docker-build-dir: .ci/docker 2025-09-07T07:51:38.9892600Z docker-build-script: ./build.sh 2025-09-07T07:51:38.9893298Z working-directory: . 2025-09-07T07:51:38.9893803Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:38.9894207Z force-push: false 2025-09-07T07:51:38.9894447Z env: 2025-09-07T07:51:38.9894668Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:38.9894929Z ##[endgroup] 2025-09-07T07:51:38.9913855Z ##[group]Run set -ex 2025-09-07T07:51:38.9914198Z set -ex 2025-09-07T07:51:38.9914421Z  2025-09-07T07:51:38.9914896Z # If the docker build directory or the build script doesn't exist, the action will 2025-09-07T07:51:38.9915603Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-09-07T07:51:38.9916184Z # job could then download the pre-built image as usual 2025-09-07T07:51:38.9916907Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-09-07T07:51:38.9917581Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9917922Z else 2025-09-07T07:51:38.9918190Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9918639Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9919061Z  2025-09-07T07:51:38.9919640Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-09-07T07:51:38.9920303Z  exit 0 2025-09-07T07:51:38.9920528Z fi 2025-09-07T07:51:38.9920740Z  2025-09-07T07:51:38.9921087Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-09-07T07:51:38.9921714Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-09-07T07:51:38.9922267Z  # use it as it is, but first let's extract the tag 2025-09-07T07:51:38.9922755Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-09-07T07:51:38.9923282Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9923789Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9924213Z else 2025-09-07T07:51:38.9924484Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-09-07T07:51:38.9924868Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-09-07T07:51:38.9925278Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-09-07T07:51:38.9925846Z  fi 2025-09-07T07:51:38.9926315Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-09-07T07:51:38.9926942Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9927612Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9928346Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:38.9928795Z fi 2025-09-07T07:51:38.9941651Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:38.9942043Z env: 2025-09-07T07:51:38.9942259Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:38.9942540Z REPO_NAME: pytorch 2025-09-07T07:51:38.9943757Z 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 2025-09-07T07:51:38.9944916Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:51:38.9945205Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-09-07T07:51:38.9945603Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:38.9946023Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-09-07T07:51:38.9946333Z CUSTOM_TAG_PREFIX: 2025-09-07T07:51:38.9946571Z ##[endgroup] 2025-09-07T07:51:38.9977413Z + [[ -d .ci/docker ]] 2025-09-07T07:51:38.9977706Z + [[ -f .ci/docker/./build.sh ]] 2025-09-07T07:51:38.9978003Z + [[ true == \t\r\u\e ]] 2025-09-07T07:51:38.9978266Z + echo skip=false 2025-09-07T07:51:38.9979493Z + [[ 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* ]] 2025-09-07T07:51:38.9985358Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:38.9986372Z ++ awk -F '[:,]' '{print $2}' 2025-09-07T07:51:38.9997524Z + DOCKER_TAG=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:38.9998715Z + echo docker-tag=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:39.0000337Z + 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 2025-09-07T07:51:39.0023794Z ##[group]Run set +e 2025-09-07T07:51:39.0024133Z set +e 2025-09-07T07:51:39.0024370Z set -x 2025-09-07T07:51:39.0024712Z  2025-09-07T07:51:39.0024918Z login() { 2025-09-07T07:51:39.0025417Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:51:39.0025962Z } 2025-09-07T07:51:39.0026178Z  2025-09-07T07:51:39.0026382Z retry () { 2025-09-07T07:51:39.0026658Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:51:39.0026985Z } 2025-09-07T07:51:39.0027199Z  2025-09-07T07:51:39.0027419Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:51:39.0027731Z  2025-09-07T07:51:39.0027955Z START_TIME=$(date +%s) 2025-09-07T07:51:39.0028259Z # Wait up to 120 minutes 2025-09-07T07:51:39.0028620Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-09-07T07:51:39.0029125Z  # Check if image already exists, if it does then skip building it 2025-09-07T07:51:39.0029634Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-09-07T07:51:39.0030015Z  exit 0 2025-09-07T07:51:39.0030252Z  fi 2025-09-07T07:51:39.0030462Z  2025-09-07T07:51:39.0030854Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-09-07T07:51:39.0031754Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-09-07T07:51:39.0032438Z  # latter, it will wait for the Docker images to become available before continuing 2025-09-07T07:51:39.0032961Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-09-07T07:51:39.0033374Z  # It's a Docker build job, let's build the image 2025-09-07T07:51:39.0033732Z  break 2025-09-07T07:51:39.0033972Z  else 2025-09-07T07:51:39.0034325Z  # It's a regular build job, wait for the image to become available 2025-09-07T07:51:39.0034739Z  sleep 300 2025-09-07T07:51:39.0034993Z  fi 2025-09-07T07:51:39.0035212Z done 2025-09-07T07:51:39.0035431Z  2025-09-07T07:51:39.0035927Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-09-07T07:51:39.0036524Z # be empty. The default action would be to continue rebuild the image 2025-09-07T07:51:39.0037059Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-09-07T07:51:39.0037528Z  # if we're on the base branch then use the parent commit 2025-09-07T07:51:39.0037930Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-09-07T07:51:39.0038259Z else 2025-09-07T07:51:39.0038597Z  # otherwise we're on a PR, so use the most recent base commit 2025-09-07T07:51:39.0039093Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-09-07T07:51:39.0039470Z fi 2025-09-07T07:51:39.0039675Z  2025-09-07T07:51:39.0039917Z if [[ -z "${MERGE_BASE}" ]]; then 2025-09-07T07:51:39.0040286Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:39.0040627Z  2025-09-07T07:51:39.0041097Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-09-07T07:51:39.0041674Z  exit 0 2025-09-07T07:51:39.0041902Z fi 2025-09-07T07:51:39.0042117Z  2025-09-07T07:51:39.0042418Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-09-07T07:51:39.0043127Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-09-07T07:51:39.0043735Z  exit 1 2025-09-07T07:51:39.0043965Z fi 2025-09-07T07:51:39.0044177Z  2025-09-07T07:51:39.0044540Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-09-07T07:51:39.0045224Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-09-07T07:51:39.0045834Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-09-07T07:51:39.0046543Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-09-07T07:51:39.0047341Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-09-07T07:51:39.0047801Z fi 2025-09-07T07:51:39.0048021Z  2025-09-07T07:51:39.0048293Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:51:39.0060669Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:39.0061062Z env: 2025-09-07T07:51:39.0061276Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:39.0061558Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:51:39.0061904Z BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:51:39.0062994Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:39.0064432Z DOCKER_TAG: pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:39.0065585Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:39.0065986Z DOCKER_PUSH: 2025-09-07T07:51:39.0066220Z ##[endgroup] 2025-09-07T07:51:39.0095643Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:39.0096104Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:39.0098421Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:51:39.0100222Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:39.8942849Z 2025-09-07T07:51:39.8943575Z WARNING! Your credentials are stored unencrypted in '/home/david/.docker/config.json'. 2025-09-07T07:51:39.8944222Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:39.8944756Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:39.8945009Z 2025-09-07T07:51:39.8945128Z Login Succeeded 2025-09-07T07:51:39.8963661Z ++ date +%s 2025-09-07T07:51:39.8972344Z + START_TIME=1757231499 2025-09-07T07:51:39.8976229Z ++ date +%s 2025-09-07T07:51:39.8983877Z + [[ 1757224299 -lt 1757231499 ]] 2025-09-07T07:51:39.8985059Z + 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 2025-09-07T07:51:40.2863962Z { 2025-09-07T07:51:40.2864258Z "schemaVersion": 2, 2025-09-07T07:51:40.2864734Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-09-07T07:51:40.2865200Z "config": { 2025-09-07T07:51:40.2865548Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-09-07T07:51:40.2865969Z "size": 31375, 2025-09-07T07:51:40.2866382Z "digest": "sha256:29d1d8a31b215537637bab7c99e18c255840b899cf7023e4e3cb5efa3270aef8" 2025-09-07T07:51:40.2866874Z }, 2025-09-07T07:51:40.2867079Z "layers": [ 2025-09-07T07:51:40.2867296Z { 2025-09-07T07:51:40.2867664Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2868102Z "size": 30448359, 2025-09-07T07:51:40.2868539Z "digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46" 2025-09-07T07:51:40.2869027Z }, 2025-09-07T07:51:40.2869209Z { 2025-09-07T07:51:40.2869539Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2869967Z "size": 1554, 2025-09-07T07:51:40.2870386Z "digest": "sha256:171dcef20c49de4bc9268f60e02f111b72c638b0f24c3c5636c5013029db6d30" 2025-09-07T07:51:40.2870858Z }, 2025-09-07T07:51:40.2871055Z { 2025-09-07T07:51:40.2871389Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2871818Z "size": 313297922, 2025-09-07T07:51:40.2872244Z "digest": "sha256:4c92b3f72f1df31fe9f487fc1c27fcf1ba475ffb43abd69056306d1247786e40" 2025-09-07T07:51:40.2872733Z }, 2025-09-07T07:51:40.2872927Z { 2025-09-07T07:51:40.2873264Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2873675Z "size": 792, 2025-09-07T07:51:40.2874094Z "digest": "sha256:744f9ba90a6582eb601b3c20409bb10d6dad635dd118c3975f79721f4c82747c" 2025-09-07T07:51:40.2874574Z }, 2025-09-07T07:51:40.2874767Z { 2025-09-07T07:51:40.2875085Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2875510Z "size": 106, 2025-09-07T07:51:40.2875919Z "digest": "sha256:d3c08322a3326e45849dd80264a047c4f42ba4a2419d35c919542e2890e23934" 2025-09-07T07:51:40.2876391Z }, 2025-09-07T07:51:40.2876681Z { 2025-09-07T07:51:40.2877002Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2877427Z "size": 704, 2025-09-07T07:51:40.2877846Z "digest": "sha256:ffd43b71f3ccf3ba563606231cb1d191eb9dd0052f422d54835e6af350525170" 2025-09-07T07:51:40.2878338Z }, 2025-09-07T07:51:40.2878519Z { 2025-09-07T07:51:40.2878851Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2879282Z "size": 1215, 2025-09-07T07:51:40.2879692Z "digest": "sha256:830692b57f6e2758398ec80c3b67a20441d12696b54ed14f2ecebf926198f7d6" 2025-09-07T07:51:40.2880521Z }, 2025-09-07T07:51:40.2880717Z { 2025-09-07T07:51:40.2881056Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2881482Z "size": 482, 2025-09-07T07:51:40.2881877Z "digest": "sha256:5bad36d184686719399be50830a98939d7dbda2313fb407df5915217483fc6a3" 2025-09-07T07:51:40.2882357Z }, 2025-09-07T07:51:40.2882555Z { 2025-09-07T07:51:40.2882884Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2883302Z "size": 110343614, 2025-09-07T07:51:40.2883743Z "digest": "sha256:0e34fdd9ac5c39eb0a9d2c2d258b26f42bb79d7dc0a22014bf201daa2e033eb4" 2025-09-07T07:51:40.2884232Z }, 2025-09-07T07:51:40.2884425Z { 2025-09-07T07:51:40.2884743Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2885164Z "size": 4786, 2025-09-07T07:51:40.2885783Z "digest": "sha256:3c868a62868ef54f82ac11be8dabe1b4365d000bacfe4c104e08022fc96dd767" 2025-09-07T07:51:40.2886276Z }, 2025-09-07T07:51:40.2886456Z { 2025-09-07T07:51:40.2886787Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2887212Z "size": 1710, 2025-09-07T07:51:40.2887630Z "digest": "sha256:62170a22dd571d55ffccac64c0be17f4006d2498cfbf7c6289325f0899cba005" 2025-09-07T07:51:40.2888102Z }, 2025-09-07T07:51:40.2888302Z { 2025-09-07T07:51:40.2888642Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2889068Z "size": 724, 2025-09-07T07:51:40.2889475Z "digest": "sha256:553c1d23b6c4dbd8ab136d0c3659460391ffa14cb9b43be9d7b2f47f90895697" 2025-09-07T07:51:40.2889959Z }, 2025-09-07T07:51:40.2890150Z { 2025-09-07T07:51:40.2890480Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2890893Z "size": 543, 2025-09-07T07:51:40.2891310Z "digest": "sha256:9408d557a804a7dce00897e03ce9f4f447281eb38ce4bc331098a1f1a5ff0d30" 2025-09-07T07:51:40.2891796Z }, 2025-09-07T07:51:40.2891988Z { 2025-09-07T07:51:40.2892307Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2892738Z "size": 3241148049, 2025-09-07T07:51:40.2893514Z "digest": "sha256:df607cfc7c07db6d442e0274e2be8cdc507df8716717363aa92f2fea069bdd9a" 2025-09-07T07:51:40.2894007Z }, 2025-09-07T07:51:40.2894189Z { 2025-09-07T07:51:40.2894520Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.2894943Z "size": 32, 2025-09-07T07:51:40.2895361Z "digest": 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"sha256:32340b97ae50ba7b2918ab40d6f4a8db875afee69318f484e4deb0a1e2ec4beb" 2025-09-07T07:51:40.2999634Z }, 2025-09-07T07:51:40.2999831Z { 2025-09-07T07:51:40.3000163Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3000587Z "size": 32, 2025-09-07T07:51:40.3000991Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:40.3001478Z }, 2025-09-07T07:51:40.3001674Z { 2025-09-07T07:51:40.3002002Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3002417Z "size": 109, 2025-09-07T07:51:40.3002851Z "digest": "sha256:5bbb04cd6b57ae13d7cf05ab9e9b4ed9752833ee2dba4eeaac47bde6022c4725" 2025-09-07T07:51:40.3003343Z }, 2025-09-07T07:51:40.3003532Z { 2025-09-07T07:51:40.3003848Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3004271Z "size": 1897, 2025-09-07T07:51:40.3004694Z "digest": "sha256:d8c4b845cfc7ca7cc0604f472bf6da8b1f1d4e98dff3c76e1985a7013a5b9e3f" 2025-09-07T07:51:40.3005183Z }, 2025-09-07T07:51:40.3005361Z { 2025-09-07T07:51:40.3005694Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3006121Z "size": 243440375, 2025-09-07T07:51:40.3006552Z "digest": "sha256:b35c180f4d8ddc2396eac4a6b893f438481a8163ceb0b88f203488bc5f2a8ba4" 2025-09-07T07:51:40.3007024Z }, 2025-09-07T07:51:40.3007217Z { 2025-09-07T07:51:40.3007548Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3007975Z "size": 106, 2025-09-07T07:51:40.3008371Z "digest": "sha256:5f967b3c303a99e609441551f7c8988cca4fd464c0c3127506bff8509583091b" 2025-09-07T07:51:40.3008844Z }, 2025-09-07T07:51:40.3009035Z { 2025-09-07T07:51:40.3009365Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3009782Z "size": 166, 2025-09-07T07:51:40.3010195Z "digest": "sha256:04770904f012e5584f1c19a0bc92d9863baaebf08bf75b4a9981f2b7795c8953" 2025-09-07T07:51:40.3010671Z }, 2025-09-07T07:51:40.3010872Z { 2025-09-07T07:51:40.3011191Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3011745Z "size": 7943, 2025-09-07T07:51:40.3012171Z "digest": "sha256:73373941fb321b4cb4a171b1423a68a4c7fedada3a1498868d7efe93cb03170e" 2025-09-07T07:51:40.3012662Z }, 2025-09-07T07:51:40.3013024Z { 2025-09-07T07:51:40.3013369Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3013800Z "size": 8072, 2025-09-07T07:51:40.3014226Z "digest": "sha256:9572e6cd907bfa4888456dbccc6e22146a0044374585f3fa0a8ced19b831ed62" 2025-09-07T07:51:40.3014696Z }, 2025-09-07T07:51:40.3014892Z { 2025-09-07T07:51:40.3015226Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3015652Z "size": 304, 2025-09-07T07:51:40.3016062Z "digest": "sha256:64a544aba233551e38898f138dd6ba3161ccdb9554e0ffb5b9d8f0f7fe4a7fa8" 2025-09-07T07:51:40.3016542Z }, 2025-09-07T07:51:40.3016736Z { 2025-09-07T07:51:40.3017241Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3017663Z "size": 13362696, 2025-09-07T07:51:40.3018081Z "digest": "sha256:7e35418a24997de5428763c93826679486760a1a9563209ae64de66ba45f99c1" 2025-09-07T07:51:40.3018555Z }, 2025-09-07T07:51:40.3018750Z { 2025-09-07T07:51:40.3019067Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3019497Z "size": 108, 2025-09-07T07:51:40.3019920Z "digest": "sha256:2ed8e82748d4a1131f41d9e41322f47a6ffef67a5a2b7bf5392237db5c035c61" 2025-09-07T07:51:40.3020403Z }, 2025-09-07T07:51:40.3020583Z { 2025-09-07T07:51:40.3020916Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3021344Z "size": 54145663, 2025-09-07T07:51:40.3021775Z "digest": "sha256:c988fbcccd708fb158a81c429d32e1060a7e40924fc3c987c629fa69d9484717" 2025-09-07T07:51:40.3022248Z }, 2025-09-07T07:51:40.3022439Z { 2025-09-07T07:51:40.3022774Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:51:40.3023197Z "size": 32, 2025-09-07T07:51:40.3023603Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:51:40.3024092Z } 2025-09-07T07:51:40.3024289Z ] 2025-09-07T07:51:40.3024479Z } 2025-09-07T07:51:40.3024754Z + exit 0 2025-09-07T07:51:40.3051090Z ##[group]Run set -eux 2025-09-07T07:51:40.3051380Z set -eux 2025-09-07T07:51:40.3051811Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-09-07T07:51:40.3053214Z 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 2025-09-07T07:51:40.3067198Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:40.3067575Z env: 2025-09-07T07:51:40.3067802Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:40.3068076Z ##[endgroup] 2025-09-07T07:51:40.3101567Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-09-07T07:51:40.3102534Z + jq --raw-output .SecretString 2025-09-07T07:51:40.3104021Z + jq -r .docker_hub_readonly_token 2025-09-07T07:51:40.3106003Z + docker login --username pytorchbot --password-stdin 2025-09-07T07:51:40.9432176Z 2025-09-07T07:51:40.9434311Z 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 2025-09-07T07:51:41.0474087Z Error: Cannot perform an interactive login from a non TTY device 2025-09-07T07:51:41.0485682Z + true 2025-09-07T07:51:41.0569900Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:51:41.0570297Z tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:51:41.0570696Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-09-07T07:51:41.0584112Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:41.0584514Z env: 2025-09-07T07:51:41.0584846Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.0585845Z 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 2025-09-07T07:51:41.0586860Z ##[endgroup] 2025-09-07T07:51:41.0620977Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:41.0668303Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-09-07T07:51:41.0668769Z with: 2025-09-07T07:51:41.0669711Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:41.0670821Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:41.0671240Z env: 2025-09-07T07:51:41.0671458Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.0671724Z ##[endgroup] 2025-09-07T07:51:41.0686612Z ##[group]Run set -x 2025-09-07T07:51:41.0686900Z set -x 2025-09-07T07:51:41.0687139Z set +e 2025-09-07T07:51:41.0687369Z  2025-09-07T07:51:41.0687573Z login() { 2025-09-07T07:51:41.0688067Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:51:41.0688606Z } 2025-09-07T07:51:41.0688822Z  2025-09-07T07:51:41.0689080Z retry () { 2025-09-07T07:51:41.0689363Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:51:41.0689679Z } 2025-09-07T07:51:41.0689893Z  2025-09-07T07:51:41.0690137Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:51:41.0690458Z  2025-09-07T07:51:41.0690952Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-09-07T07:51:41.0691659Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-09-07T07:51:41.0692048Z  2025-09-07T07:51:41.0692264Z set -e 2025-09-07T07:51:41.0692601Z # ignore output since only exit code is used for conditional 2025-09-07T07:51:41.0693294Z # only pull docker image if it's not available locally 2025-09-07T07:51:41.0693861Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-09-07T07:51:41.0694391Z  retry docker pull "${DOCKER_IMAGE}" 2025-09-07T07:51:41.0694724Z fi 2025-09-07T07:51:41.0707526Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:51:41.0707919Z env: 2025-09-07T07:51:41.0708149Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:51:41.0709138Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:41.0710266Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:41.0710654Z ##[endgroup] 2025-09-07T07:51:41.0744763Z + set +e 2025-09-07T07:51:41.0745310Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:41.0745780Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:41.0748513Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:51:41.0750306Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:51:41.9711406Z 2025-09-07T07:51:41.9712008Z WARNING! Your credentials are stored unencrypted in '/home/david/.docker/config.json'. 2025-09-07T07:51:41.9712650Z Configure a credential helper to remove this warning. See 2025-09-07T07:51:41.9713123Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:51:41.9713373Z 2025-09-07T07:51:41.9713469Z Login Succeeded 2025-09-07T07:51:41.9735669Z ++ 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 2025-09-07T07:51:41.9737155Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-09-07T07:51:42.3755710Z + IMAGE_SIZE=36183.606596946716 2025-09-07T07:51:42.3756136Z Compressed size of image in MB: 36183.606596946716 2025-09-07T07:51:42.3756584Z + echo 'Compressed size of image in MB: 36183.606596946716' 2025-09-07T07:51:42.3756966Z + set -e 2025-09-07T07:51:42.3758340Z + 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 2025-09-07T07:51:42.3875902Z + 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 2025-09-07T07:51:42.3877692Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:51:43.2135624Z pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image 2025-09-07T07:51:43.2136835Z e6fdc8487bfe: Pulling fs layer 2025-09-07T07:51:43.2137540Z 171dcef20c49: Pulling fs layer 2025-09-07T07:51:43.2137921Z 4c92b3f72f1d: Pulling fs layer 2025-09-07T07:51:43.2138217Z 744f9ba90a65: Pulling fs layer 2025-09-07T07:51:43.2138544Z d3c08322a332: Pulling fs layer 2025-09-07T07:51:43.2138840Z ffd43b71f3cc: Pulling fs layer 2025-09-07T07:51:43.2139125Z 830692b57f6e: Pulling fs layer 2025-09-07T07:51:43.2139413Z 5bad36d18468: Pulling fs layer 2025-09-07T07:51:43.2139681Z 744f9ba90a65: Waiting 2025-09-07T07:51:43.2139929Z d3c08322a332: Waiting 2025-09-07T07:51:43.2140180Z ffd43b71f3cc: Waiting 2025-09-07T07:51:43.2140435Z 0e34fdd9ac5c: Pulling fs layer 2025-09-07T07:51:43.2140716Z 830692b57f6e: Waiting 2025-09-07T07:51:43.2140964Z 3c868a62868e: Pulling fs layer 2025-09-07T07:51:43.2141237Z 5bad36d18468: Waiting 2025-09-07T07:51:43.2141485Z 62170a22dd57: Pulling fs layer 2025-09-07T07:51:43.2141757Z 553c1d23b6c4: Pulling fs layer 2025-09-07T07:51:43.2142028Z 3c868a62868e: Waiting 2025-09-07T07:51:43.2142277Z 9408d557a804: Pulling fs layer 2025-09-07T07:51:43.2142552Z 62170a22dd57: Waiting 2025-09-07T07:51:43.2142793Z df607cfc7c07: Pulling fs layer 2025-09-07T07:51:43.2143081Z 4f4fb700ef54: Pulling fs layer 2025-09-07T07:51:43.2143355Z 553c1d23b6c4: Waiting 2025-09-07T07:51:43.2143588Z 9408d557a804: Waiting 2025-09-07T07:51:43.2143828Z df607cfc7c07: Waiting 2025-09-07T07:51:43.2144073Z 4f4fb700ef54: Waiting 2025-09-07T07:51:43.2144329Z 40a8e39faeda: Pulling fs layer 2025-09-07T07:51:43.2144698Z d895771c9fac: Pulling fs layer 2025-09-07T07:51:43.2144994Z c4ee04f39d49: Pulling fs layer 2025-09-07T07:51:43.2145279Z 3690c9826e48: Pulling fs layer 2025-09-07T07:51:43.2145576Z 57cbc5013733: Pulling fs layer 2025-09-07T07:51:43.2145842Z 40a8e39faeda: Waiting 2025-09-07T07:51:43.2146140Z f5f4b06b58bb: Pulling fs layer 2025-09-07T07:51:43.2146422Z c4ee04f39d49: Waiting 2025-09-07T07:51:43.2146665Z 3690c9826e48: Waiting 2025-09-07T07:51:43.2146907Z d895771c9fac: Waiting 2025-09-07T07:51:43.2147142Z 57cbc5013733: Waiting 2025-09-07T07:51:43.2147403Z f59713ce4bf4: Pulling fs layer 2025-09-07T07:51:43.2147703Z fe0486521517: Pulling fs layer 2025-09-07T07:51:43.2147992Z 8c21cc3715a2: Pulling fs layer 2025-09-07T07:51:43.2148268Z d37c58456a6a: Pulling fs layer 2025-09-07T07:51:43.2148552Z f5f4b06b58bb: Waiting 2025-09-07T07:51:43.2148792Z fe0486521517: Waiting 2025-09-07T07:51:43.2149028Z f59713ce4bf4: Waiting 2025-09-07T07:51:43.2149266Z d042f63abc13: Pulling fs layer 2025-09-07T07:51:43.2149542Z 8c21cc3715a2: Waiting 2025-09-07T07:51:43.2149780Z d37c58456a6a: Waiting 2025-09-07T07:51:43.2150028Z 621284a9c05a: Pulling fs layer 2025-09-07T07:51:43.2150300Z 85f605d2dd3a: Pulling fs layer 2025-09-07T07:51:43.2150975Z 381b5539e598: Pulling fs layer 2025-09-07T07:51:43.2151266Z a487c0c80029: Pulling fs layer 2025-09-07T07:51:43.2151547Z d042f63abc13: Waiting 2025-09-07T07:51:43.2151778Z 85f605d2dd3a: Waiting 2025-09-07T07:51:43.2152022Z 381b5539e598: Waiting 2025-09-07T07:51:43.2152257Z 621284a9c05a: Waiting 2025-09-07T07:51:43.2152509Z 48bcb81e2566: Pulling fs layer 2025-09-07T07:51:43.2152784Z e261928c0043: Pulling fs layer 2025-09-07T07:51:43.2153069Z 0fea55428091: Pulling fs layer 2025-09-07T07:51:43.2153341Z a487c0c80029: Waiting 2025-09-07T07:51:43.2153583Z 48bcb81e2566: Waiting 2025-09-07T07:51:43.2153990Z e261928c0043: Waiting 2025-09-07T07:51:43.2154254Z b4291bccbb84: Pulling fs layer 2025-09-07T07:51:43.2154531Z 0fea55428091: Waiting 2025-09-07T07:51:43.2154791Z ddc91b09189a: Pulling fs layer 2025-09-07T07:51:43.2155058Z b4291bccbb84: Waiting 2025-09-07T07:51:43.2155308Z 7540c7428627: Pulling fs layer 2025-09-07T07:51:43.2155597Z 003c4e2598fb: Pulling fs layer 2025-09-07T07:51:43.2155884Z 5687149362ae: Pulling fs layer 2025-09-07T07:51:43.2156148Z ddc91b09189a: Waiting 2025-09-07T07:51:43.2156390Z 7540c7428627: Waiting 2025-09-07T07:51:43.2156645Z 003c4e2598fb: Waiting 2025-09-07T07:51:43.2156913Z cdd2cf54eb2a: Pulling fs layer 2025-09-07T07:51:43.2157206Z d3ad4df1ba3a: Pulling fs layer 2025-09-07T07:51:43.2157490Z cdd2cf54eb2a: Waiting 2025-09-07T07:51:43.2157736Z 5687149362ae: Waiting 2025-09-07T07:51:43.2157985Z 3c9055753b4c: Pulling fs layer 2025-09-07T07:51:43.2158274Z 31cf8d0bd21c: Pulling fs layer 2025-09-07T07:51:43.2158559Z d3ad4df1ba3a: Waiting 2025-09-07T07:51:43.2158805Z 3c9055753b4c: Waiting 2025-09-07T07:51:43.2159043Z 6623ea814971: Pulling fs layer 2025-09-07T07:51:43.2159322Z 31cf8d0bd21c: Waiting 2025-09-07T07:51:43.2159580Z 11696c3aa380: Pulling fs layer 2025-09-07T07:51:43.2159861Z 6623ea814971: Waiting 2025-09-07T07:51:43.2160103Z ef4d544e35ca: Pulling fs layer 2025-09-07T07:51:43.2160381Z 11696c3aa380: Waiting 2025-09-07T07:51:43.2160623Z ef4d544e35ca: Waiting 2025-09-07T07:51:43.2160887Z 5c5108865e5e: Pulling fs layer 2025-09-07T07:51:43.2161151Z 5c5108865e5e: Waiting 2025-09-07T07:51:43.2161410Z 9e97578e9edf: Pulling fs layer 2025-09-07T07:51:43.2161700Z da5a91b54cb5: Pulling fs layer 2025-09-07T07:51:43.2161989Z 9e97578e9edf: Waiting 2025-09-07T07:51:43.2162234Z 1e93be219e89: Pulling fs layer 2025-09-07T07:51:43.2162512Z da5a91b54cb5: Waiting 2025-09-07T07:51:43.2162751Z 1e93be219e89: Waiting 2025-09-07T07:51:43.2163003Z 136825afebb5: Pulling fs layer 2025-09-07T07:51:43.2163276Z 22b39805302d: Pulling fs layer 2025-09-07T07:51:43.2163571Z d12add675e35: Pulling fs layer 2025-09-07T07:51:43.2163864Z bc127046d33a: Pulling fs layer 2025-09-07T07:51:43.2164141Z 136825afebb5: Waiting 2025-09-07T07:51:43.2164369Z 22b39805302d: Waiting 2025-09-07T07:51:43.2164624Z d12add675e35: Waiting 2025-09-07T07:51:43.2164871Z bc127046d33a: Waiting 2025-09-07T07:51:43.2165130Z 951e8ce83841: Pulling fs layer 2025-09-07T07:51:43.2165406Z 32340b97ae50: Pulling fs layer 2025-09-07T07:51:43.2165694Z 951e8ce83841: Waiting 2025-09-07T07:51:43.2165933Z 32340b97ae50: Waiting 2025-09-07T07:51:43.2177839Z 5bbb04cd6b57: Pulling fs layer 2025-09-07T07:51:43.2178275Z d8c4b845cfc7: Pulling fs layer 2025-09-07T07:51:43.2178563Z b35c180f4d8d: Pulling fs layer 2025-09-07T07:51:43.2178865Z 5f967b3c303a: Pulling fs layer 2025-09-07T07:51:43.2179159Z 04770904f012: Pulling fs layer 2025-09-07T07:51:43.2179442Z 73373941fb32: Pulling fs layer 2025-09-07T07:51:43.2179709Z 5bbb04cd6b57: Waiting 2025-09-07T07:51:43.2179971Z 9572e6cd907b: Pulling fs layer 2025-09-07T07:51:43.2180281Z 64a544aba233: Pulling fs layer 2025-09-07T07:51:43.2180570Z 7e35418a2499: Pulling fs layer 2025-09-07T07:51:43.2180835Z d8c4b845cfc7: Waiting 2025-09-07T07:51:43.2181094Z 2ed8e82748d4: Pulling fs layer 2025-09-07T07:51:43.2181370Z 5f967b3c303a: Waiting 2025-09-07T07:51:43.2181631Z c988fbcccd70: Pulling fs layer 2025-09-07T07:51:43.2181901Z b35c180f4d8d: Waiting 2025-09-07T07:51:43.2182144Z 7e35418a2499: Waiting 2025-09-07T07:51:43.2182384Z 2ed8e82748d4: Waiting 2025-09-07T07:51:43.2182893Z 64a544aba233: Waiting 2025-09-07T07:51:43.2183125Z c988fbcccd70: Waiting 2025-09-07T07:51:43.2183366Z 04770904f012: Waiting 2025-09-07T07:51:43.2183607Z 9572e6cd907b: Waiting 2025-09-07T07:51:43.2183835Z 73373941fb32: Waiting 2025-09-07T07:51:43.3657235Z 171dcef20c49: Verifying Checksum 2025-09-07T07:51:43.3657600Z 171dcef20c49: Download complete 2025-09-07T07:51:43.5208109Z 744f9ba90a65: Download complete 2025-09-07T07:51:43.6383497Z e6fdc8487bfe: Verifying Checksum 2025-09-07T07:51:43.6383885Z e6fdc8487bfe: Download complete 2025-09-07T07:51:43.7986378Z d3c08322a332: Verifying Checksum 2025-09-07T07:51:43.7986778Z d3c08322a332: Download complete 2025-09-07T07:51:43.7987090Z ffd43b71f3cc: Verifying Checksum 2025-09-07T07:51:43.7987397Z ffd43b71f3cc: Download complete 2025-09-07T07:51:43.9379001Z 830692b57f6e: Verifying Checksum 2025-09-07T07:51:43.9379403Z 830692b57f6e: Download complete 2025-09-07T07:51:43.9602489Z 5bad36d18468: Verifying Checksum 2025-09-07T07:51:43.9602906Z 5bad36d18468: Download complete 2025-09-07T07:51:44.1027817Z 3c868a62868e: Verifying Checksum 2025-09-07T07:51:44.1028173Z 3c868a62868e: Download complete 2025-09-07T07:51:44.2765091Z 62170a22dd57: Download complete 2025-09-07T07:51:44.4236340Z 553c1d23b6c4: Verifying Checksum 2025-09-07T07:51:44.4236729Z 553c1d23b6c4: Download complete 2025-09-07T07:51:44.5797873Z 9408d557a804: Verifying Checksum 2025-09-07T07:51:44.5798261Z 9408d557a804: Download complete 2025-09-07T07:51:45.0999047Z e6fdc8487bfe: Pull complete 2025-09-07T07:51:45.5878494Z 0e34fdd9ac5c: Verifying Checksum 2025-09-07T07:51:45.5878922Z 0e34fdd9ac5c: Download complete 2025-09-07T07:51:45.6740932Z 4f4fb700ef54: Download complete 2025-09-07T07:51:45.8575038Z 40a8e39faeda: Verifying Checksum 2025-09-07T07:51:45.8575550Z 40a8e39faeda: Download complete 2025-09-07T07:51:46.1579564Z 171dcef20c49: Pull complete 2025-09-07T07:51:46.4923520Z 4c92b3f72f1d: Verifying Checksum 2025-09-07T07:51:46.4923923Z 4c92b3f72f1d: Download complete 2025-09-07T07:51:46.6419106Z d895771c9fac: Verifying Checksum 2025-09-07T07:51:46.6419481Z d895771c9fac: Download complete 2025-09-07T07:51:46.6497193Z c4ee04f39d49: Verifying Checksum 2025-09-07T07:51:46.6497525Z c4ee04f39d49: Download complete 2025-09-07T07:51:46.8444151Z 57cbc5013733: Verifying Checksum 2025-09-07T07:51:46.8444542Z 57cbc5013733: Download complete 2025-09-07T07:51:47.0053605Z f5f4b06b58bb: Verifying Checksum 2025-09-07T07:51:47.0054000Z f5f4b06b58bb: Download complete 2025-09-07T07:51:47.0214012Z f59713ce4bf4: Verifying Checksum 2025-09-07T07:51:47.0214377Z f59713ce4bf4: Download complete 2025-09-07T07:51:47.2248949Z fe0486521517: Verifying Checksum 2025-09-07T07:51:47.2249325Z fe0486521517: Download complete 2025-09-07T07:51:47.5491291Z d37c58456a6a: Verifying Checksum 2025-09-07T07:51:47.5491693Z d37c58456a6a: Download complete 2025-09-07T07:51:48.1137540Z d042f63abc13: Verifying Checksum 2025-09-07T07:51:48.1137940Z d042f63abc13: Download complete 2025-09-07T07:51:48.2881456Z 621284a9c05a: Verifying Checksum 2025-09-07T07:51:48.2881924Z 621284a9c05a: Download complete 2025-09-07T07:51:48.5462356Z 85f605d2dd3a: Verifying Checksum 2025-09-07T07:51:48.5462753Z 85f605d2dd3a: Download complete 2025-09-07T07:51:57.1054136Z 381b5539e598: Verifying Checksum 2025-09-07T07:51:57.1054687Z 381b5539e598: Download complete 2025-09-07T07:51:57.4026237Z a487c0c80029: Verifying Checksum 2025-09-07T07:51:57.4026689Z a487c0c80029: Download complete 2025-09-07T07:51:57.5616051Z 48bcb81e2566: Verifying Checksum 2025-09-07T07:51:57.5616644Z 48bcb81e2566: Download complete 2025-09-07T07:51:57.7572547Z e261928c0043: Verifying Checksum 2025-09-07T07:51:57.7573148Z e261928c0043: Download complete 2025-09-07T07:51:57.9106412Z 0fea55428091: Verifying Checksum 2025-09-07T07:51:57.9106854Z 0fea55428091: Download complete 2025-09-07T07:51:58.3170712Z b4291bccbb84: Verifying Checksum 2025-09-07T07:51:58.3171124Z b4291bccbb84: Download complete 2025-09-07T07:51:58.4858287Z ddc91b09189a: Verifying Checksum 2025-09-07T07:51:58.6108882Z ddc91b09189a: Download complete 2025-09-07T07:51:58.6873739Z 7540c7428627: Verifying Checksum 2025-09-07T07:51:58.6874118Z 7540c7428627: Download complete 2025-09-07T07:51:58.8500129Z 003c4e2598fb: Verifying Checksum 2025-09-07T07:51:58.8500583Z 003c4e2598fb: Download complete 2025-09-07T07:51:59.0373397Z 5687149362ae: Verifying Checksum 2025-09-07T07:51:59.0373775Z 5687149362ae: Download complete 2025-09-07T07:51:59.3306977Z cdd2cf54eb2a: Verifying Checksum 2025-09-07T07:51:59.3307420Z cdd2cf54eb2a: Download complete 2025-09-07T07:52:23.8799452Z 4c92b3f72f1d: Pull complete 2025-09-07T07:52:25.2601983Z 744f9ba90a65: Pull complete 2025-09-07T07:52:26.9918791Z d3c08322a332: Pull complete 2025-09-07T07:52:28.6560493Z ffd43b71f3cc: Pull complete 2025-09-07T07:52:30.3898706Z 830692b57f6e: Pull complete 2025-09-07T07:52:32.1521449Z 5bad36d18468: Pull complete 2025-09-07T07:52:43.7578637Z 0e34fdd9ac5c: Pull complete 2025-09-07T07:52:45.0036345Z 3c868a62868e: Pull complete 2025-09-07T07:52:46.3563402Z 62170a22dd57: Pull complete 2025-09-07T07:52:47.0187616Z df607cfc7c07: Verifying Checksum 2025-09-07T07:52:47.0188258Z df607cfc7c07: Download complete 2025-09-07T07:52:47.2581237Z 3c9055753b4c: Verifying Checksum 2025-09-07T07:52:47.2581647Z 3c9055753b4c: Download complete 2025-09-07T07:52:48.6031371Z 553c1d23b6c4: Pull complete 2025-09-07T07:52:49.9613489Z 9408d557a804: Pull complete 2025-09-07T07:52:53.1280327Z 31cf8d0bd21c: Verifying Checksum 2025-09-07T07:52:53.1280725Z 31cf8d0bd21c: Download complete 2025-09-07T07:55:35.7740609Z 8c21cc3715a2: Verifying Checksum 2025-09-07T07:55:35.7741035Z 8c21cc3715a2: Download complete 2025-09-07T07:55:36.0855119Z 11696c3aa380: Verifying Checksum 2025-09-07T07:55:36.0855525Z 11696c3aa380: Download complete 2025-09-07T07:55:36.2440153Z ef4d544e35ca: Verifying Checksum 2025-09-07T07:55:36.2440558Z ef4d544e35ca: Download complete 2025-09-07T07:55:36.4045301Z 5c5108865e5e: Verifying Checksum 2025-09-07T07:55:36.4045675Z 5c5108865e5e: Download complete 2025-09-07T07:55:36.5388599Z 9e97578e9edf: Verifying Checksum 2025-09-07T07:55:36.5388956Z 9e97578e9edf: Download complete 2025-09-07T07:55:36.7088138Z da5a91b54cb5: Download complete 2025-09-07T07:55:36.8650101Z 1e93be219e89: Verifying Checksum 2025-09-07T07:55:36.8650461Z 1e93be219e89: Download complete 2025-09-07T07:55:37.0264816Z 136825afebb5: Verifying Checksum 2025-09-07T07:55:37.0265174Z 136825afebb5: Download complete 2025-09-07T07:55:37.1882331Z 22b39805302d: Verifying Checksum 2025-09-07T07:55:37.1882684Z 22b39805302d: Download complete 2025-09-07T07:55:37.3399195Z d12add675e35: Verifying Checksum 2025-09-07T07:55:37.3399576Z d12add675e35: Download complete 2025-09-07T07:55:37.5321767Z bc127046d33a: Verifying Checksum 2025-09-07T07:55:37.5322129Z bc127046d33a: Download complete 2025-09-07T07:55:37.6889767Z 951e8ce83841: Verifying Checksum 2025-09-07T07:55:37.6890135Z 951e8ce83841: Download complete 2025-09-07T07:55:37.8430871Z 32340b97ae50: Download complete 2025-09-07T07:55:37.9932080Z 5bbb04cd6b57: Verifying Checksum 2025-09-07T07:55:37.9932495Z 5bbb04cd6b57: Download complete 2025-09-07T07:55:38.1469263Z d8c4b845cfc7: Verifying Checksum 2025-09-07T07:55:38.1469621Z d8c4b845cfc7: Download complete 2025-09-07T07:56:56.4502809Z b35c180f4d8d: Verifying Checksum 2025-09-07T07:56:56.4503194Z b35c180f4d8d: Download complete 2025-09-07T07:56:56.6131962Z 5f967b3c303a: Verifying Checksum 2025-09-07T07:56:56.6132343Z 5f967b3c303a: Download complete 2025-09-07T07:56:56.7732494Z 04770904f012: Verifying Checksum 2025-09-07T07:56:56.7733051Z 04770904f012: Download complete 2025-09-07T07:56:56.9297782Z 73373941fb32: Download complete 2025-09-07T07:56:57.0894272Z 9572e6cd907b: Download complete 2025-09-07T07:56:57.2438738Z 64a544aba233: Verifying Checksum 2025-09-07T07:56:57.2439133Z 64a544aba233: Download complete 2025-09-07T07:56:58.8159826Z 7e35418a2499: Verifying Checksum 2025-09-07T07:56:58.8160219Z 7e35418a2499: Download complete 2025-09-07T07:56:58.9791163Z 2ed8e82748d4: Download complete 2025-09-07T07:57:05.8906976Z c988fbcccd70: Verifying Checksum 2025-09-07T07:57:05.8907782Z c988fbcccd70: Download complete 2025-09-07T08:01:45.9552849Z 6623ea814971: Verifying Checksum 2025-09-07T08:01:45.9553244Z 6623ea814971: Download complete 2025-09-07T08:11:26.1674784Z d3ad4df1ba3a: Verifying Checksum 2025-09-07T08:11:26.1675227Z d3ad4df1ba3a: Download complete 2025-09-07T08:11:50.4989753Z df607cfc7c07: Pull complete 2025-09-07T08:11:53.2865077Z 4f4fb700ef54: Pull complete 2025-09-07T08:11:56.3458038Z 40a8e39faeda: Pull complete 2025-09-07T08:12:01.8609462Z d895771c9fac: Pull complete 2025-09-07T08:12:05.3056168Z c4ee04f39d49: Pull complete 2025-09-07T08:12:10.2145363Z 3690c9826e48: Pull complete 2025-09-07T08:12:15.0405107Z 57cbc5013733: Pull complete 2025-09-07T08:12:20.2119622Z f5f4b06b58bb: Pull complete 2025-09-07T08:12:23.2097009Z f59713ce4bf4: Pull complete 2025-09-07T08:12:26.5505173Z fe0486521517: Pull complete 2025-09-07T08:24:30.4588901Z 8c21cc3715a2: Pull complete 2025-09-07T08:24:33.0392207Z d37c58456a6a: Pull complete 2025-09-07T08:24:39.1859210Z d042f63abc13: Pull complete 2025-09-07T08:24:41.7049171Z 621284a9c05a: Pull complete 2025-09-07T08:24:44.8258044Z 85f605d2dd3a: Pull complete 2025-09-07T08:25:25.0728617Z 381b5539e598: Pull complete 2025-09-07T08:25:28.7456443Z a487c0c80029: Pull complete 2025-09-07T08:25:31.5075147Z 48bcb81e2566: Pull complete 2025-09-07T08:25:36.2975415Z e261928c0043: Pull complete 2025-09-07T08:25:38.6312231Z 0fea55428091: Pull complete 2025-09-07T08:25:41.4013832Z b4291bccbb84: Pull complete 2025-09-07T08:25:43.2589896Z ddc91b09189a: Pull complete 2025-09-07T08:25:45.1488388Z 7540c7428627: Pull complete 2025-09-07T08:25:49.8332641Z 003c4e2598fb: Pull complete 2025-09-07T08:25:52.2429466Z 5687149362ae: Pull complete 2025-09-07T08:25:54.0905641Z cdd2cf54eb2a: Pull complete 2025-09-07T08:47:08.4137971Z d3ad4df1ba3a: Pull complete 2025-09-07T08:47:11.8479943Z 3c9055753b4c: Pull complete 2025-09-07T08:47:17.5054490Z 31cf8d0bd21c: Pull complete 2025-09-07T08:51:32.0674662Z 6623ea814971: Pull complete 2025-09-07T08:51:34.0532695Z 11696c3aa380: Pull complete 2025-09-07T08:51:36.3274292Z ef4d544e35ca: Pull complete 2025-09-07T08:51:41.8175694Z 5c5108865e5e: Pull complete 2025-09-07T08:51:47.1707253Z 9e97578e9edf: Pull complete 2025-09-07T08:51:49.9816241Z da5a91b54cb5: Pull complete 2025-09-07T08:51:56.2768535Z 1e93be219e89: Pull complete 2025-09-07T08:52:03.4831900Z 136825afebb5: Pull complete 2025-09-07T08:52:06.9118289Z 22b39805302d: Pull complete 2025-09-07T08:52:14.1753482Z d12add675e35: Pull complete 2025-09-07T08:52:18.1448529Z bc127046d33a: Pull complete 2025-09-07T08:52:23.3254957Z 951e8ce83841: Pull complete 2025-09-07T08:52:26.8596862Z 32340b97ae50: Pull complete 2025-09-07T08:52:33.7104365Z 5bbb04cd6b57: Pull complete 2025-09-07T08:52:36.9177589Z d8c4b845cfc7: Pull complete 2025-09-07T08:53:19.2610978Z b35c180f4d8d: Pull complete 2025-09-07T08:53:22.6629431Z 5f967b3c303a: Pull complete 2025-09-07T08:53:25.0536701Z 04770904f012: Pull complete 2025-09-07T08:53:27.4337632Z 73373941fb32: Pull complete 2025-09-07T08:53:30.4924578Z 9572e6cd907b: Pull complete 2025-09-07T08:53:33.2816077Z 64a544aba233: Pull complete 2025-09-07T08:53:41.4678050Z 7e35418a2499: Pull complete 2025-09-07T08:53:43.9405290Z 2ed8e82748d4: Pull complete 2025-09-07T08:53:52.0026198Z c988fbcccd70: Pull complete 2025-09-07T08:53:55.8674834Z Digest: sha256:f30843ff9ea9e117a2c8e6d207e85c9e77dfe682f1dfcdfea5b94178d1bf00b3 2025-09-07T08:53:56.4830283Z 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 2025-09-07T08:53:56.6705768Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:53:56.6911129Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:53:56.6912128Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:53:56.6925559Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:53:56.6925957Z env: 2025-09-07T08:53:56.6926184Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:53:56.6926456Z ##[endgroup] 2025-09-07T08:53:56.7991678Z ##[group]Run echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:53:56.7992411Z echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:53:56.8005022Z shell: /usr/bin/bash -e {0} 2025-09-07T08:53:56.8005322Z env: 2025-09-07T08:53:56.8005546Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:53:56.8005813Z ##[endgroup] 2025-09-07T08:53:56.9038338Z ##[group]Run echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:53:56.9039239Z echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:53:56.9051834Z shell: /usr/bin/bash -e {0} 2025-09-07T08:53:56.9052132Z env: 2025-09-07T08:53:56.9052357Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:53:56.9052699Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:53:56.9053365Z ##[endgroup] 2025-09-07T08:53:56.9634161Z Prepare all required actions 2025-09-07T08:53:57.0104986Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-09-07T08:53:57.0105369Z with: 2025-09-07T08:53:57.0105811Z github-token: *** 2025-09-07T08:53:57.0106035Z env: 2025-09-07T08:53:57.0106260Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:53:57.0106609Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:53:57.0107081Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:53:57.0107468Z ##[endgroup] 2025-09-07T08:53:57.0635999Z ##[group]Run set -eux 2025-09-07T08:53:57.0636310Z set -eux 2025-09-07T08:53:57.0636771Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T08:53:57.0649716Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:53:57.0650107Z env: 2025-09-07T08:53:57.0650337Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:53:57.0650688Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:53:57.0651222Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:53:57.0651830Z GITHUB_TOKEN: *** 2025-09-07T08:53:57.0652076Z ##[endgroup] 2025-09-07T08:53:57.1165415Z + python3 .github/scripts/get_workflow_job_id.py 17525309334 i-01a21955dc3821a00-1004 2025-09-07T08:53:58.0470816Z Setting output job-id=49775768449 2025-09-07T08:53:58.0471492Z Setting output job-name=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T08:53:58.1007032Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:53:58.1007829Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:53:58.1008997Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-09-07T08:53:58.1009958Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-09-07T08:53:58.1024082Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:53:58.1024562Z env: 2025-09-07T08:53:58.1024886Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:53:58.1025236Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:53:58.1025725Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:53:58.1026196Z JOB_ID: 49775768449 2025-09-07T08:53:58.1026701Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T08:53:58.1027335Z WORKFLOW_NAME: inductor-A100-perf-nightly 2025-09-07T08:53:58.1027670Z WORKFLOW_RUN_ID: 17525309334 2025-09-07T08:53:58.1027961Z MONITOR_LOG_INTERVAL: 15 2025-09-07T08:53:58.1028504Z MONITOR_DATA_COLLECT_INTERVAL: 4 2025-09-07T08:53:58.1028872Z ##[endgroup] 2025-09-07T08:53:58.4799051Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:53:59.2203397Z Collecting psutil==5.9.8 2025-09-07T08:53:59.4505744Z 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) 2025-09-07T08:53:59.8141361Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 KB 774.5 kB/s eta 0:00:00 2025-09-07T08:54:00.2315677Z Collecting dataclasses_json==0.6.7 2025-09-07T08:54:00.2431942Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-09-07T08:54:00.8018304Z Collecting nvidia-ml-py==11.525.84 2025-09-07T08:54:00.8636936Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-09-07T08:54:01.4979357Z Collecting typing-inspect<1,>=0.4.0 2025-09-07T08:54:01.8485360Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-09-07T08:54:02.6123753Z Collecting marshmallow<4.0.0,>=3.18.0 2025-09-07T08:54:02.8376002Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-09-07T08:54:03.0955630Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 50.9/50.9 KB 159.1 kB/s eta 0:00:00 2025-09-07T08:54:03.8796934Z Collecting packaging>=17.0 2025-09-07T08:54:04.0974507Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-09-07T08:54:04.4079147Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 66.5/66.5 KB 197.2 kB/s eta 0:00:00 2025-09-07T08:54:04.6465220Z Collecting typing-extensions>=3.7.4 2025-09-07T08:54:04.6585748Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-09-07T08:54:04.9747305Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.6/44.6 KB 109.6 kB/s eta 0:00:00 2025-09-07T08:54:05.3778231Z Collecting mypy-extensions>=0.3.0 2025-09-07T08:54:05.3899737Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-09-07T08:54:06.1241575Z Installing collected packages: nvidia-ml-py, typing-extensions, psutil, packaging, mypy-extensions, typing-inspect, marshmallow, dataclasses_json 2025-09-07T08:54:12.4572051Z 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 2025-09-07T08:54:12.5368290Z Prepare all required actions 2025-09-07T08:54:12.5368696Z Getting action download info 2025-09-07T08:54:12.7424498Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-09-07T08:54:16.6371899Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-09-07T08:54:25.0260392Z ##[group]Run ./.github/actions/download-build-artifacts 2025-09-07T08:54:25.0260774Z with: 2025-09-07T08:54:25.0261035Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:54:25.0261378Z s3-bucket: gha-artifacts 2025-09-07T08:54:25.0261650Z env: 2025-09-07T08:54:25.0261875Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:25.0262239Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:25.0262692Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:25.0263090Z ##[endgroup] 2025-09-07T08:54:25.0716124Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:54:25.0716478Z with: 2025-09-07T08:54:25.0716719Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:54:25.0717071Z s3-bucket: gha-artifacts 2025-09-07T08:54:25.0717346Z region: us-east-1 2025-09-07T08:54:25.0717564Z env: 2025-09-07T08:54:25.0717781Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:25.0718121Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:25.0718588Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:25.0718982Z ##[endgroup] 2025-09-07T08:54:25.5400610Z (node:9631) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:54:25.5401124Z 2025-09-07T08:54:25.5401682Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:54:25.5402234Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:54:25.5402822Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:54:25.6558711Z Found 1 objects with prefix pytorch/pytorch/17525309334/linux-jammy-cuda12.8-py3.10-gcc9-sm80/ 2025-09-07T08:54:25.6559442Z Starting download (1/1): /home/david/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:54:34.1793959Z Finished download (1/1): /home/david/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:54:34.1801840Z Artifact download has finished successfully 2025-09-07T08:54:34.2328252Z ##[group]Run unzip -o artifacts.zip 2025-09-07T08:54:34.2328692Z unzip -o artifacts.zip 2025-09-07T08:54:34.2343535Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:34.2344050Z env: 2025-09-07T08:54:34.2344351Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:34.2344799Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:34.2345516Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:34.2346026Z ##[endgroup] 2025-09-07T08:54:34.2894192Z Archive: artifacts.zip 2025-09-07T08:54:34.2895609Z creating: dist/ 2025-09-07T08:54:36.2790968Z inflating: dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T08:54:36.2791492Z creating: dist/vision/ 2025-09-07T08:54:36.2917656Z inflating: dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:54:36.2918183Z creating: dist/audio/ 2025-09-07T08:54:36.2975373Z inflating: dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:54:36.2975891Z creating: dist/torchrec/ 2025-09-07T08:54:36.3001788Z inflating: dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:54:36.3002223Z creating: dist/fbgemm_gpu/ 2025-09-07T08:54:37.4735195Z inflating: dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:54:37.4735792Z creating: dist/ao/ 2025-09-07T08:54:37.4777309Z inflating: dist/ao/torchao-0.7.0+git51c87b6e-py3-none-any.whl 2025-09-07T08:54:37.4908671Z inflating: dist/.ninja_log 2025-09-07T08:54:37.4909047Z creating: build/custom_test_artifacts/ 2025-09-07T08:54:37.4909848Z creating: build/custom_test_artifacts/custom-op-build/ 2025-09-07T08:54:37.4910364Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/ 2025-09-07T08:54:37.4910965Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/pkgRedirects/ 2025-09-07T08:54:37.4917259Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/CMakeConfigureLog.yaml 2025-09-07T08:54:37.4917984Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/ 2025-09-07T08:54:37.4918667Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CMakeSystem.cmake 2025-09-07T08:54:37.4919395Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdC/ 2025-09-07T08:54:37.4920109Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdC/tmp/ 2025-09-07T08:54:37.4920925Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdC/CMakeCCompilerId.c 2025-09-07T08:54:37.4921944Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdC/a.out 2025-09-07T08:54:37.4922728Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CMakeCCompiler.cmake 2025-09-07T08:54:37.4923486Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdCXX/ 2025-09-07T08:54:37.4924207Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdCXX/tmp/ 2025-09-07T08:54:37.4925201Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdCXX/CMakeCXXCompilerId.cpp 2025-09-07T08:54:37.4926367Z inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/CompilerIdCXX/a.out 2025-09-07T08:54:37.4927418Z inflating: 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2025-09-07T08:54:45.8971937Z inflating: build/bin/BackoffTest 2025-09-07T08:54:45.9032208Z inflating: build/bin/TCPStoreTest 2025-09-07T08:54:45.9089714Z inflating: build/bin/FileStoreTest 2025-09-07T08:54:45.9146846Z inflating: build/bin/HashStoreTest 2025-09-07T08:54:45.9161572Z inflating: build/bin/ProcessGroupMPITest 2025-09-07T08:54:45.9164347Z inflating: build/bin/example_allreduce 2025-09-07T08:54:45.9225346Z inflating: build/bin/Dimname_test 2025-09-07T08:54:45.9289794Z inflating: build/bin/NamedTensor_test 2025-09-07T08:54:45.9357934Z inflating: build/bin/MaybeOwned_test 2025-09-07T08:54:45.9439338Z inflating: build/bin/Dict_test 2025-09-07T08:54:45.9502787Z inflating: build/bin/atest 2025-09-07T08:54:45.9565635Z inflating: build/bin/apply_utils_test 2025-09-07T08:54:45.9636919Z inflating: build/bin/basic 2025-09-07T08:54:45.9700029Z inflating: build/bin/cpu_generator_test 2025-09-07T08:54:45.9761403Z inflating: build/bin/broadcast_test 2025-09-07T08:54:45.9816022Z inflating: build/bin/cpu_allocator_test 2025-09-07T08:54:45.9872818Z inflating: build/bin/cpu_profiling_allocator_test 2025-09-07T08:54:45.9977877Z inflating: build/bin/cpu_rng_test 2025-09-07T08:54:46.0040566Z inflating: build/bin/extension_backend_test 2025-09-07T08:54:46.0095582Z inflating: build/bin/dlconvertor_test 2025-09-07T08:54:46.0162342Z inflating: build/bin/half_test 2025-09-07T08:54:46.0271199Z inflating: build/bin/ivalue_test 2025-09-07T08:54:46.0324370Z inflating: build/bin/lazy_tensor_test 2025-09-07T08:54:46.0383822Z inflating: build/bin/math_kernel_test 2025-09-07T08:54:46.0443693Z inflating: build/bin/memory_format_test 2025-09-07T08:54:46.0500520Z inflating: build/bin/memory_overlapping_test 2025-09-07T08:54:46.0559533Z inflating: build/bin/mobile_memory_cleanup 2025-09-07T08:54:46.0625100Z inflating: build/bin/native_test 2025-09-07T08:54:46.0679765Z inflating: build/bin/operators_test 2025-09-07T08:54:46.0734044Z inflating: build/bin/operator_name_test 2025-09-07T08:54:46.0792036Z inflating: build/bin/packedtensoraccessor_test 2025-09-07T08:54:46.0869416Z inflating: build/bin/pow_test 2025-09-07T08:54:46.0922882Z inflating: build/bin/reduce_ops_test 2025-09-07T08:54:46.0978809Z inflating: build/bin/reportMemoryUsage_test 2025-09-07T08:54:46.1043298Z inflating: build/bin/quantized_test 2025-09-07T08:54:46.1107961Z inflating: build/bin/scalar_tensor_test 2025-09-07T08:54:46.1170681Z inflating: build/bin/scalar_test 2025-09-07T08:54:46.1225848Z inflating: build/bin/StorageUtils_test 2025-09-07T08:54:46.1285553Z inflating: build/bin/stride_properties_test 2025-09-07T08:54:46.1369161Z inflating: build/bin/tensor_iterator_test 2025-09-07T08:54:46.1425074Z inflating: build/bin/thread_init_test 2025-09-07T08:54:46.1483017Z inflating: build/bin/test_parallel 2025-09-07T08:54:46.1542109Z inflating: build/bin/type_ptr_test 2025-09-07T08:54:46.1606309Z inflating: build/bin/type_test 2025-09-07T08:54:46.1662694Z inflating: build/bin/undefined_tensor_test 2025-09-07T08:54:46.1717317Z inflating: build/bin/verify_api_visibility 2025-09-07T08:54:46.1791330Z inflating: build/bin/legacy_vmap_test 2025-09-07T08:54:46.1846257Z inflating: build/bin/weakref_test 2025-09-07T08:54:46.1901603Z inflating: build/bin/wrapdim_test 2025-09-07T08:54:46.1957198Z inflating: build/bin/xla_tensor_test 2025-09-07T08:54:46.2021668Z inflating: build/bin/IListRef_test 2025-09-07T08:54:46.2135900Z inflating: build/bin/List_test 2025-09-07T08:54:46.2209935Z inflating: build/bin/KernelFunction_test 2025-09-07T08:54:46.2336669Z inflating: build/bin/kernel_function_legacy_test 2025-09-07T08:54:46.2440896Z inflating: build/bin/kernel_function_test 2025-09-07T08:54:46.2573720Z inflating: build/bin/kernel_lambda_legacy_test 2025-09-07T08:54:46.2685199Z inflating: build/bin/kernel_lambda_test 2025-09-07T08:54:46.2750156Z inflating: build/bin/kernel_stackbased_test 2025-09-07T08:54:46.2853479Z inflating: build/bin/make_boxed_from_unboxed_functor_test 2025-09-07T08:54:46.2909572Z inflating: build/bin/CppSignature_test 2025-09-07T08:54:46.2969119Z inflating: build/bin/backend_fallback_test 2025-09-07T08:54:46.3021340Z inflating: build/bin/op_allowlist_test 2025-09-07T08:54:46.3331990Z inflating: build/bin/op_registration_test 2025-09-07T08:54:46.3401721Z inflating: build/bin/inline_container_test 2025-09-07T08:54:46.3458056Z inflating: build/bin/cuda_apply_test 2025-09-07T08:54:46.3521589Z inflating: build/bin/cuda_atomic_ops_test 2025-09-07T08:54:46.3577377Z inflating: build/bin/cuda_allocator_test 2025-09-07T08:54:46.3638148Z inflating: build/bin/cuda_caching_host_allocator_test 2025-09-07T08:54:46.3711834Z inflating: build/bin/cuda_complex_math_test 2025-09-07T08:54:46.3774772Z inflating: build/bin/cuda_complex_test 2025-09-07T08:54:46.3840849Z inflating: build/bin/cuda_cub_test 2025-09-07T08:54:46.3894319Z inflating: build/bin/cuda_device_test 2025-09-07T08:54:46.3963277Z inflating: build/bin/cuda_distributions_test 2025-09-07T08:54:46.4018724Z inflating: build/bin/cuda_dlconvertor_test 2025-09-07T08:54:46.4072143Z inflating: build/bin/cuda_exchange_device_test 2025-09-07T08:54:46.4132756Z inflating: build/bin/cuda_generator_test 2025-09-07T08:54:46.4186133Z inflating: build/bin/cuda_half_test 2025-09-07T08:54:46.4241197Z inflating: build/bin/cuda_integer_divider_test 2025-09-07T08:54:46.4294792Z inflating: build/bin/cuda_optional_test 2025-09-07T08:54:46.4350739Z inflating: build/bin/cuda_reportMemoryUsage_test 2025-09-07T08:54:46.4405849Z inflating: build/bin/cuda_packedtensoraccessor_test 2025-09-07T08:54:46.4459166Z inflating: build/bin/cuda_allocatorTraceTracker_test 2025-09-07T08:54:46.4523560Z inflating: build/bin/cuda_stream_test 2025-09-07T08:54:46.4580238Z inflating: build/bin/cuda_vectorized_test 2025-09-07T08:54:46.4633265Z inflating: build/bin/cuda_cudnn_test 2025-09-07T08:54:46.5020522Z inflating: build/bin/test_nativert 2025-09-07T08:54:46.5079151Z inflating: build/bin/test_dist_autograd 2025-09-07T08:54:46.5151962Z inflating: build/bin/test_cpp_rpc 2025-09-07T08:54:46.6354777Z inflating: build/bin/test_api 2025-09-07T08:54:46.6356787Z inflating: build/bin/parallel_benchmark 2025-09-07T08:54:46.6424445Z inflating: build/bin/ProcessGroupNCCLTest 2025-09-07T08:54:46.6490331Z inflating: build/bin/ProcessGroupNCCLErrorsTest 2025-09-07T08:54:47.1115372Z inflating: build/bin/test_jit 2025-09-07T08:54:47.1184534Z inflating: build/bin/ProcessGroupGlooTest 2025-09-07T08:54:47.1253214Z inflating: build/bin/ProcessGroupGlooAsyncTest 2025-09-07T08:54:47.1616623Z inflating: build/bin/test_lazy 2025-09-07T08:54:47.1620443Z inflating: build/bin/torch_shm_manager 2025-09-07T08:54:47.1620841Z creating: .additional_ci_files/ 2025-09-07T08:54:47.1717731Z inflating: .additional_ci_files/test-times.json 2025-09-07T08:54:47.2065560Z inflating: .additional_ci_files/test-class-times.json 2025-09-07T08:54:47.2167059Z ##[group]Run rm artifacts.zip 2025-09-07T08:54:47.2167381Z rm artifacts.zip 2025-09-07T08:54:47.2180127Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:47.2180532Z env: 2025-09-07T08:54:47.2180765Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:47.2181108Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:47.2181581Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:47.2181993Z ##[endgroup] 2025-09-07T08:54:47.3981377Z ##[group]Run df -H 2025-09-07T08:54:47.3981645Z df -H 2025-09-07T08:54:47.3994124Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:47.3994530Z env: 2025-09-07T08:54:47.3994760Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:47.3995090Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:47.3995564Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:47.3995964Z ##[endgroup] 2025-09-07T08:54:47.4316146Z Filesystem Size Used Avail Use% Mounted on 2025-09-07T08:54:47.4316723Z overlay 5.3T 603G 4.7T 12% / 2025-09-07T08:54:47.4317339Z tmpfs 68M 0 68M 0% /dev 2025-09-07T08:54:47.4317673Z shm 68M 0 68M 0% /dev/shm 2025-09-07T08:54:47.4318202Z /dev/root 5.3T 603G 4.7T 12% /home/david/_work 2025-09-07T08:54:47.4318803Z tmpfs 121G 111k 121G 1% /run/docker.sock 2025-09-07T08:54:47.4319239Z tmpfs 603G 13k 603G 1% /proc/driver/nvidia 2025-09-07T08:54:47.4319734Z tmpfs 241G 1.7M 241G 1% /run/.ro2501796620/nvidia-persistenced/socket 2025-09-07T08:54:47.4320186Z tmpfs 603G 0 603G 0% /proc/acpi 2025-09-07T08:54:47.4320595Z tmpfs 603G 0 603G 0% /proc/scsi 2025-09-07T08:54:47.4320983Z tmpfs 603G 0 603G 0% /sys/firmware 2025-09-07T08:54:47.4359029Z Prepare all required actions 2025-09-07T08:54:47.4359839Z Getting action download info 2025-09-07T08:54:47.6443988Z ##[group]Run ./.github/actions/download-td-artifacts 2025-09-07T08:54:47.6444370Z with: 2025-09-07T08:54:47.6444579Z env: 2025-09-07T08:54:47.6444823Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:47.6445162Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:47.6445632Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:47.6446037Z ##[endgroup] 2025-09-07T08:54:47.7013415Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:54:47.7013766Z with: 2025-09-07T08:54:47.7013984Z name: td_results 2025-09-07T08:54:47.7014234Z s3-bucket: gha-artifacts 2025-09-07T08:54:47.7014508Z region: us-east-1 2025-09-07T08:54:47.7014726Z env: 2025-09-07T08:54:47.7014941Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:47.7015277Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:47.7015850Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:47.7016254Z ##[endgroup] 2025-09-07T08:54:48.1796454Z (node:9652) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:54:48.1796967Z 2025-09-07T08:54:48.1797207Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:54:48.1797758Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:54:48.1798321Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:54:48.3027291Z Found 0 objects with prefix pytorch/pytorch/17525309334/td_results/ 2025-09-07T08:54:48.3033142Z Artifact download has finished successfully 2025-09-07T08:54:48.3412691Z ##[group]Run mkdir -p .additional_ci_files 2025-09-07T08:54:48.3413294Z mkdir -p .additional_ci_files 2025-09-07T08:54:48.3413747Z mv td_results.json .additional_ci_files/td_results.json || true 2025-09-07T08:54:48.3426864Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:48.3427250Z env: 2025-09-07T08:54:48.3427478Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:48.3427821Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:48.3428288Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:48.3428687Z ##[endgroup] 2025-09-07T08:54:48.3959101Z mv: cannot stat 'td_results.json': No such file or directory 2025-09-07T08:54:48.4633336Z ##[group]Run .github/scripts/parse_ref.py 2025-09-07T08:54:48.4633722Z .github/scripts/parse_ref.py 2025-09-07T08:54:48.4645644Z shell: /usr/bin/bash -e {0} 2025-09-07T08:54:48.4645939Z env: 2025-09-07T08:54:48.4646168Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:48.4646510Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:48.4646972Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:48.4647373Z ##[endgroup] 2025-09-07T08:54:48.4999296Z Setting output branch=main 2025-09-07T08:54:48.5127849Z Prepare all required actions 2025-09-07T08:54:48.5128250Z Getting action download info 2025-09-07T08:54:48.6756102Z ##[group]Run ./.github/actions/filter-test-configs 2025-09-07T08:54:48.6756512Z with: 2025-09-07T08:54:48.6756934Z github-token: *** 2025-09-07T08:54:48.6762973Z 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"}]} 2025-09-07T08:54:48.6769130Z job-name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T08:54:48.6769636Z env: 2025-09-07T08:54:48.6769857Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:48.6770209Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:48.6770667Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:48.6771065Z ##[endgroup] 2025-09-07T08:54:48.7260623Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T08:54:48.7261173Z with: 2025-09-07T08:54:48.7261521Z shell: bash 2025-09-07T08:54:48.7261866Z timeout_minutes: 10 2025-09-07T08:54:48.7262121Z max_attempts: 5 2025-09-07T08:54:48.7262456Z retry_wait_seconds: 30 2025-09-07T08:54:48.7263567Z 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 2025-09-07T08:54:48.7264599Z polling_interval_seconds: 1 2025-09-07T08:54:48.7265017Z warning_on_retry: true 2025-09-07T08:54:48.7265297Z continue_on_error: false 2025-09-07T08:54:48.7265598Z env: 2025-09-07T08:54:48.7265966Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:48.7266308Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:48.7266792Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:48.7267524Z GITHUB_TOKEN: *** 2025-09-07T08:54:48.7267790Z ##[endgroup] 2025-09-07T08:54:48.8039351Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:54:49.1145238Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:54:49.5512739Z Collecting requests==2.27.1 2025-09-07T08:54:49.6490030Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-09-07T08:54:49.9690174Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 166.8 kB/s eta 0:00:00 2025-09-07T08:54:50.3106869Z Collecting pyyaml==6.0.2 2025-09-07T08:54:50.3237881Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-09-07T08:54:50.7671409Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 1.7 MB/s eta 0:00:00 2025-09-07T08:54:51.3220503Z Collecting charset-normalizer~=2.0.0 2025-09-07T08:54:51.3353564Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-09-07T08:54:51.5884570Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.27.1) (1.26.5) 2025-09-07T08:54:51.5892430Z Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.27.1) (2020.6.20) 2025-09-07T08:54:51.5909664Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.27.1) (3.3) 2025-09-07T08:54:51.6711367Z Installing collected packages: pyyaml, charset-normalizer, requests 2025-09-07T08:54:52.5250810Z WARNING: The script normalizer is installed in '/home/david/.local/bin' which is not on PATH. 2025-09-07T08:54:52.5251815Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T08:54:53.8153743Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-09-07T08:54:54.8089505Z Command completed after 1 attempt(s). 2025-09-07T08:54:54.8590663Z ##[group]Run set -x 2025-09-07T08:54:54.8590943Z set -x 2025-09-07T08:54:54.8591177Z  2025-09-07T08:54:54.8591566Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:54:54.8592071Z # in runner workspace 2025-09-07T08:54:54.8592474Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-09-07T08:54:54.8605167Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:54.8605569Z env: 2025-09-07T08:54:54.8605783Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:54.8606142Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:54.8606610Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:54.8607006Z ##[endgroup] 2025-09-07T08:54:54.9129354Z + python3 /home/david/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-09-07T08:54:54.9282065Z Setting output branch=main 2025-09-07T08:54:54.9683891Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:54:54.9684349Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:54:54.9684701Z echo "Job name: ${JOB_NAME}" 2025-09-07T08:54:54.9684995Z  2025-09-07T08:54:54.9685392Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:54:54.9685891Z # in runner workspace 2025-09-07T08:54:54.9686333Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-09-07T08:54:54.9686823Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-09-07T08:54:54.9687168Z  --job-name "${JOB_NAME}" \ 2025-09-07T08:54:54.9693398Z  --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"}]}" \ 2025-09-07T08:54:54.9700226Z  --selected-test-configs "" \ 2025-09-07T08:54:54.9700580Z  --pr-number "${PR_NUMBER}" \ 2025-09-07T08:54:54.9700917Z  --tag "${TAG}" \ 2025-09-07T08:54:54.9701226Z  --event-name "${EVENT_NAME}" \ 2025-09-07T08:54:54.9701585Z  --schedule "${SCHEDULE}" \ 2025-09-07T08:54:54.9701911Z  --branch "${HEAD_BRANCH}" 2025-09-07T08:54:54.9714336Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:54.9714753Z env: 2025-09-07T08:54:54.9714983Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:54.9715325Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:54.9715781Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:54.9716396Z GITHUB_TOKEN: *** 2025-09-07T08:54:54.9716844Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T08:54:54.9717366Z PR_NUMBER: 2025-09-07T08:54:54.9717590Z TAG: 2025-09-07T08:54:54.9717794Z EVENT_NAME: schedule 2025-09-07T08:54:54.9718054Z SCHEDULE: 0 7 * * 0 2025-09-07T08:54:54.9718303Z HEAD_BRANCH: main 2025-09-07T08:54:54.9718545Z ##[endgroup] 2025-09-07T08:54:55.0213950Z Workflow: inductor-A100-perf-nightly 2025-09-07T08:54:55.0214483Z Job name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T08:54:55.2827521Z Setting output keep-going=True 2025-09-07T08:54:55.2827924Z Setting output ci-verbose-test-logs=False 2025-09-07T08:54:55.2828328Z Setting output ci-test-showlocals=False 2025-09-07T08:54:55.2828665Z Setting output ci-no-test-timeout=False 2025-09-07T08:54:55.2829004Z Setting output ci-no-td=False 2025-09-07T08:54:55.2829321Z Setting output ci-td-distributed=False 2025-09-07T08:54:55.2829654Z Setting output is-unstable=False 2025-09-07T08:54:55.2829953Z Setting output reenabled-issues= 2025-09-07T08:54:55.2836168Z 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"}]} 2025-09-07T08:54:55.2842468Z Setting output is-test-matrix-empty=False 2025-09-07T08:54:55.3050608Z ##[group]Run echo "Filtered matrix:" 2025-09-07T08:54:55.3050977Z echo "Filtered matrix:" 2025-09-07T08:54:55.3056967Z 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"}]}" 2025-09-07T08:54:55.3062935Z  2025-09-07T08:54:55.3063145Z echo 2025-09-07T08:54:55.3063428Z echo "Is the current job unstable? False" 2025-09-07T08:54:55.3063772Z  2025-09-07T08:54:55.3063966Z echo 2025-09-07T08:54:55.3064223Z echo "Is keep-going label set? True" 2025-09-07T08:54:55.3064551Z  2025-09-07T08:54:55.3064756Z echo 2025-09-07T08:54:55.3065047Z echo "Reenabled issues? " 2025-09-07T08:54:55.3077635Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:55.3078035Z env: 2025-09-07T08:54:55.3078267Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:55.3078612Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:55.3079069Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:55.3079481Z ##[endgroup] 2025-09-07T08:54:55.3262090Z Filtered matrix: 2025-09-07T08:54:55.3269035Z {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}]} 2025-09-07T08:54:55.3274970Z 2025-09-07T08:54:55.3275096Z Is the current job unstable? False 2025-09-07T08:54:55.3275302Z 2025-09-07T08:54:55.3275414Z Is keep-going label set? True 2025-09-07T08:54:55.3275612Z 2025-09-07T08:54:55.3275704Z Reenabled issues? 2025-09-07T08:54:55.3532138Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:54:55.3532706Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:54:55.3545002Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:55.3545410Z env: 2025-09-07T08:54:55.3545636Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:55.3545976Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:55.3546455Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:55.3546868Z JOB_TIMEOUT: 1440 2025-09-07T08:54:55.3547117Z ##[endgroup] 2025-09-07T08:54:55.4245696Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:54:55.4246244Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:54:55.4246704Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:54:55.4258654Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:54:55.4259050Z env: 2025-09-07T08:54:55.4259288Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:55.4259628Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:55.4260087Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:55.4260484Z ##[endgroup] 2025-09-07T08:54:55.4907653Z ##[group]Run set -x 2025-09-07T08:54:55.4908064Z set -x 2025-09-07T08:54:55.4908296Z  2025-09-07T08:54:55.4908546Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-09-07T08:54:55.4908956Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-09-07T08:54:55.4909373Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-09-07T08:54:55.4909756Z  TEST_COMMAND=.ci/onnx/test.sh 2025-09-07T08:54:55.4910070Z else 2025-09-07T08:54:55.4910323Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:54:55.4910646Z fi 2025-09-07T08:54:55.4910855Z  2025-09-07T08:54:55.4911130Z # Leaving 1GB for the runner and other things 2025-09-07T08:54:55.4911733Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-09-07T08:54:55.4912648Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-09-07T08:54:55.4913385Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-09-07T08:54:55.4913929Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-09-07T08:54:55.4914364Z  2025-09-07T08:54:55.4914637Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:54:55.4914998Z  SHM_OPTS= 2025-09-07T08:54:55.4915242Z  JENKINS_USER= 2025-09-07T08:54:55.4915606Z  # ensure that docker container cleanly exits in 12 hours 2025-09-07T08:54:55.4916101Z  # if for some reason cleanup action doesn't stop container 2025-09-07T08:54:55.4916515Z  # when job is cancelled 2025-09-07T08:54:55.4916840Z  DOCKER_SHELL_CMD="sleep 12h" 2025-09-07T08:54:55.4917325Z else 2025-09-07T08:54:55.4917590Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-09-07T08:54:55.4917946Z  JENKINS_USER="--user jenkins" 2025-09-07T08:54:55.4918282Z  DOCKER_SHELL_CMD= 2025-09-07T08:54:55.4918543Z fi 2025-09-07T08:54:55.4918763Z  2025-09-07T08:54:55.4919111Z # detached container should get cleaned up by teardown_ec2_linux 2025-09-07T08:54:55.4919665Z # TODO: Stop building test binaries as part of the build phase 2025-09-07T08:54:55.4920286Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-09-07T08:54:55.4920844Z # shellcheck disable=SC2086,SC2090 2025-09-07T08:54:55.4921190Z container_name=$(docker run \ 2025-09-07T08:54:55.4921511Z  ${GPU_FLAG:-} \ 2025-09-07T08:54:55.4921826Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-09-07T08:54:55.4922168Z  -e BUILD_ENVIRONMENT \ 2025-09-07T08:54:55.4922481Z  -e PR_NUMBER \ 2025-09-07T08:54:55.4922759Z  -e GITHUB_ACTIONS \ 2025-09-07T08:54:55.4923061Z  -e GITHUB_REPOSITORY \ 2025-09-07T08:54:55.4923364Z  -e GITHUB_WORKFLOW \ 2025-09-07T08:54:55.4923658Z  -e GITHUB_JOB \ 2025-09-07T08:54:55.4923938Z  -e GITHUB_RUN_ID \ 2025-09-07T08:54:55.4924225Z  -e GITHUB_RUN_NUMBER \ 2025-09-07T08:54:55.4924520Z  -e GITHUB_RUN_ATTEMPT \ 2025-09-07T08:54:55.4924818Z  -e JOB_ID \ 2025-09-07T08:54:55.4925075Z  -e JOB_NAME \ 2025-09-07T08:54:55.4925339Z  -e BASE_SHA \ 2025-09-07T08:54:55.4925592Z  -e BRANCH \ 2025-09-07T08:54:55.4925846Z  -e SHA1 \ 2025-09-07T08:54:55.4926105Z  -e AWS_DEFAULT_REGION \ 2025-09-07T08:54:55.4926409Z  -e IN_WHEEL_TEST \ 2025-09-07T08:54:55.4926679Z  -e SHARD_NUMBER \ 2025-09-07T08:54:55.4926962Z  -e TEST_CONFIG \ 2025-09-07T08:54:55.4927251Z  -e NUM_TEST_SHARDS \ 2025-09-07T08:54:55.4927552Z  -e REENABLED_ISSUES \ 2025-09-07T08:54:55.4927852Z  -e CONTINUE_THROUGH_ERROR \ 2025-09-07T08:54:55.4928325Z  -e VERBOSE_TEST_LOGS \ 2025-09-07T08:54:55.4928642Z  -e TEST_SHOWLOCALS \ 2025-09-07T08:54:55.4928943Z  -e NO_TEST_TIMEOUT \ 2025-09-07T08:54:55.4929219Z  -e NO_TD \ 2025-09-07T08:54:55.4929485Z  -e TD_DISTRIBUTED \ 2025-09-07T08:54:55.4929778Z  -e PR_LABELS \ 2025-09-07T08:54:55.4930086Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-09-07T08:54:55.4930418Z  -e SCCACHE_BUCKET \ 2025-09-07T08:54:55.4930713Z  -e SCCACHE_REGION \ 2025-09-07T08:54:55.4931001Z  -e XLA_CUDA \ 2025-09-07T08:54:55.4931299Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-09-07T08:54:55.4931674Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-09-07T08:54:55.4932057Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-09-07T08:54:55.4932440Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-09-07T08:54:55.4932956Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-09-07T08:54:55.4933310Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-09-07T08:54:55.4933685Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-09-07T08:54:55.4934182Z  -e DASHBOARD_TAG \ 2025-09-07T08:54:55.4934488Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-09-07T08:54:55.4934869Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-09-07T08:54:55.4935373Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-09-07T08:54:55.4935834Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-09-07T08:54:55.4936268Z  --security-opt seccomp=unconfined \ 2025-09-07T08:54:55.4936715Z  --cap-add=SYS_PTRACE \ 2025-09-07T08:54:55.4937052Z  --ipc=host \ 2025-09-07T08:54:55.4937310Z  ${SHM_OPTS} \ 2025-09-07T08:54:55.4937828Z  --tty \ 2025-09-07T08:54:55.4938078Z  --detach \ 2025-09-07T08:54:55.4938384Z  --name="${container_name}" \ 2025-09-07T08:54:55.4938712Z  ${JENKINS_USER} \ 2025-09-07T08:54:55.4939149Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-09-07T08:54:55.4939563Z  -w /var/lib/jenkins/workspace \ 2025-09-07T08:54:55.4939926Z  "${DOCKER_IMAGE}" \ 2025-09-07T08:54:55.4940206Z  ${DOCKER_SHELL_CMD} 2025-09-07T08:54:55.4940482Z ) 2025-09-07T08:54:55.4940779Z # Propagate download.pytorch.org IP to container 2025-09-07T08:54:55.4941469Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-09-07T08:54:55.4942213Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-09-07T08:54:55.4942626Z  2025-09-07T08:54:55.4942900Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:54:55.4943501Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-09-07T08:54:55.4944039Z fi 2025-09-07T08:54:55.4944239Z  2025-09-07T08:54:55.4944753Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-09-07T08:54:55.4956713Z shell: /usr/bin/bash -e {0} 2025-09-07T08:54:55.4957004Z env: 2025-09-07T08:54:55.4957225Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:54:55.4957553Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:54:55.4958020Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T08:54:55.4958512Z BUILD_ENVIRONMENT: linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T08:54:55.4958900Z PR_NUMBER: 2025-09-07T08:54:55.4959138Z GITHUB_REPOSITORY: pytorch/pytorch 2025-09-07T08:54:55.4959491Z GITHUB_WORKFLOW: inductor-A100-perf-nightly 2025-09-07T08:54:55.4959875Z GITHUB_JOB: test 2025-09-07T08:54:55.4960133Z GITHUB_RUN_ID: 17525309334 2025-09-07T08:54:55.4960401Z GITHUB_RUN_NUMBER: 5418 2025-09-07T08:54:55.4960670Z GITHUB_RUN_ATTEMPT: 1 2025-09-07T08:54:55.4960923Z JOB_ID: 49775768449 2025-09-07T08:54:55.4961531Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T08:54:55.4962046Z BRANCH: main 2025-09-07T08:54:55.4962305Z SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:54:55.4962690Z BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:54:55.4963063Z TEST_CONFIG: inductor_torchbench_perf 2025-09-07T08:54:55.4963388Z SHARD_NUMBER: 1 2025-09-07T08:54:55.4963614Z NUM_TEST_SHARDS: 6 2025-09-07T08:54:55.4963862Z REENABLED_ISSUES: 2025-09-07T08:54:55.4964120Z CONTINUE_THROUGH_ERROR: True 2025-09-07T08:54:55.4964409Z VERBOSE_TEST_LOGS: False 2025-09-07T08:54:55.4964667Z TEST_SHOWLOCALS: False 2025-09-07T08:54:55.4964932Z NO_TEST_TIMEOUT: False 2025-09-07T08:54:55.4965184Z NO_TD: False 2025-09-07T08:54:55.4965457Z TD_DISTRIBUTED: False 2025-09-07T08:54:55.4965762Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-09-07T08:54:55.4966132Z SCCACHE_REGION: us-east-1 2025-09-07T08:54:55.4966406Z SHM_SIZE: 2g 2025-09-07T08:54:55.4967347Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:54:55.4968340Z XLA_CUDA: 2025-09-07T08:54:55.4968705Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:54:55.4969176Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-09-07T08:54:55.4969505Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-09-07T08:54:55.4970836Z 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 2025-09-07T08:54:55.4972382Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-09-07T08:54:55.4973125Z HUGGING_FACE_HUB_TOKEN: *** 2025-09-07T08:54:55.4973565Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-09-07T08:54:55.4974054Z ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T08:54:55.4974545Z ##[endgroup] 2025-09-07T08:54:55.5155581Z + [[ inductor_torchbench_perf == \m\u\l\t\i\g\p\u ]] 2025-09-07T08:54:55.5156016Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *onnx* ]] 2025-09-07T08:54:55.5156402Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:54:55.5158893Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-09-07T08:54:55.5167392Z + TOTAL_AVAILABLE_MEMORY_IN_GB='1120.797 ' 2025-09-07T08:54:55.5167747Z + TOTAL_MEMORY_WITH_SWAP=1123 2025-09-07T08:54:55.5168121Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *\s\3\9\0\x* ]] 2025-09-07T08:54:55.5168519Z + SHM_OPTS=--shm-size=2g 2025-09-07T08:54:55.5168795Z + JENKINS_USER='--user jenkins' 2025-09-07T08:54:55.5169062Z + DOCKER_SHELL_CMD= 2025-09-07T08:54:55.5176191Z +++ nproc --ignore=2 2025-09-07T08:54:55.5190122Z ++ docker run --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all -e SCCACHE_SERVER_PORT=5230 -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/david/_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 2025-09-07T09:13:38.5430393Z + container_name=7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T09:13:38.5432684Z + grep download.pytorch.org /etc/hosts 2025-09-07T09:13:38.5434588Z + docker exec -i 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 sudo bash -c '/bin/cat >> /etc/hosts' 2025-09-07T09:13:38.6151233Z + echo DOCKER_CONTAINER_ID=7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T09:13:38.6159972Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *\s\3\9\0\x* ]] 2025-09-07T09:13:38.6163818Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T09:13:38.6166268Z + docker exec -t 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-09-07T09:13:39.0221579Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d) 2025-09-07T09:13:39.8453915Z 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) 2025-09-07T09:13:39.8458256Z 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) 2025-09-07T09:13:39.8462897Z 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) 2025-09-07T09:13:39.8467722Z 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) 2025-09-07T09:13:39.8471545Z 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) 2025-09-07T09:13:39.8476644Z 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) 2025-09-07T09:13:39.8491851Z 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) 2025-09-07T09:13:39.8860139Z 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) 2025-09-07T09:13:39.8879841Z 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) 2025-09-07T09:13:39.8918559Z 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) 2025-09-07T09:13:40.8005441Z Installing collected packages: torch 2025-09-07T09:13:53.8045460Z 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. 2025-09-07T09:13:53.8046943Z dall-e 0.1 requires torchvision, which is not installed. 2025-09-07T09:13:53.8047620Z effdet 0.4.1 requires torchvision, which is not installed. 2025-09-07T09:13:53.8048355Z python-doctr 1.0.0 requires torchvision>=0.15.0, which is not installed. 2025-09-07T09:13:53.8049435Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed. 2025-09-07T09:13:53.8050754Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed. 2025-09-07T09:13:53.8052054Z timm 1.0.14 requires torchvision, which is not installed. 2025-09-07T09:13:53.8053956Z Successfully installed torch-2.9.0a0+git93fb23d 2025-09-07T09:13:54.1905880Z + export TERM=vt100 2025-09-07T09:13:54.1906362Z + TERM=vt100 2025-09-07T09:13:54.1909386Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:13:54.1918747Z + source .ci/pytorch/common.sh 2025-09-07T09:13:54.1923629Z +++ dirname .ci/pytorch/common.sh 2025-09-07T09:13:54.1930471Z ++ source .ci/pytorch/common_utils.sh 2025-09-07T09:13:54.1931518Z +++ declare -f -t trap_add 2025-09-07T09:13:54.1936722Z ++ set -ex -o pipefail 2025-09-07T09:13:54.1937271Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:13:54.1937891Z ++ BUILD_TEST_LIBTORCH=0 2025-09-07T09:13:54.1942374Z ++ dirname .ci/pytorch/test.sh 2025-09-07T09:13:54.1950279Z + source .ci/pytorch/common-build.sh 2025-09-07T09:13:54.1951747Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *win-* ]] 2025-09-07T09:13:54.1958827Z ++++ dirname .ci/pytorch/common-build.sh 2025-09-07T09:13:54.1966517Z +++ cd .ci/pytorch 2025-09-07T09:13:54.1966936Z +++ pwd -P 2025-09-07T09:13:54.1969118Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-09-07T09:13:54.1969831Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-pch* ]] 2025-09-07T09:13:54.1970472Z ++ which sccache 2025-09-07T09:13:54.1982729Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-09-07T09:13:54.1983308Z ++ sccache --stop-server 2025-09-07T09:13:54.2009674Z ++ true 2025-09-07T09:13:54.2010076Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-09-07T09:13:54.2020142Z ++ trap_add sccache_epilogue EXIT 2025-09-07T09:13:54.2020632Z ++ trap_add_cmd=sccache_epilogue 2025-09-07T09:13:54.2021048Z ++ shift 2025-09-07T09:13:54.2021428Z ++ for trap_add_name in "$@" 2025-09-07T09:13:54.2028061Z ++++ trap -p EXIT 2025-09-07T09:13:54.2029999Z +++ eval 'extract_trap_cmd ' 2025-09-07T09:13:54.2036820Z ++++ extract_trap_cmd 2025-09-07T09:13:54.2037085Z ++++ printf '%s\n' '' 2025-09-07T09:13:54.2037361Z +++ printf '%s\n' sccache_epilogue 2025-09-07T09:13:54.2037672Z ++ trap -- ' 2025-09-07T09:13:54.2037916Z sccache_epilogue' EXIT 2025-09-07T09:13:54.2038171Z ++ [[ -n 1 ]] 2025-09-07T09:13:54.2038575Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-09-07T09:13:54.2039200Z Skipping sccache server initialization, setting environment variables 2025-09-07T09:13:54.2039667Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:13:54.2039958Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:13:54.2040321Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:13:54.2040790Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:13:54.2041222Z ++ export RUST_LOG=sccache::server=error 2025-09-07T09:13:54.2041552Z ++ RUST_LOG=sccache::server=error 2025-09-07T09:13:54.2041865Z ++ sccache --zero-stats 2025-09-07T09:13:54.4894006Z Statistics zeroed. 2025-09-07T09:13:54.4897573Z ++ which ccache 2025-09-07T09:13:54.4911259Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *rocm* ]] 2025-09-07T09:13:54.4911754Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *s390x* ]] 2025-09-07T09:13:54.4912174Z + [[ -d /var/lib/jenkins/workspace ]] 2025-09-07T09:13:54.4914863Z ++ stat -c %u /var/lib/jenkins/workspace 2025-09-07T09:13:54.4925863Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-09-07T09:13:54.4926263Z + trap_add cleanup_workspace EXIT 2025-09-07T09:13:54.4926588Z + trap_add_cmd=cleanup_workspace 2025-09-07T09:13:54.4926879Z + shift 2025-09-07T09:13:54.4927105Z + for trap_add_name in "$@" 2025-09-07T09:13:54.4932536Z +++ trap -p EXIT 2025-09-07T09:13:54.4935124Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-09-07T09:13:54.4935464Z sccache_epilogue'\'' EXIT' 2025-09-07T09:13:54.4935802Z +++ extract_trap_cmd trap -- ' 2025-09-07T09:13:54.4936082Z sccache_epilogue' EXIT 2025-09-07T09:13:54.4936338Z +++ printf '%s\n' ' 2025-09-07T09:13:54.4936581Z sccache_epilogue' 2025-09-07T09:13:54.4936860Z ++ printf '%s\n' cleanup_workspace 2025-09-07T09:13:54.4937485Z + trap -- ' 2025-09-07T09:13:54.4937708Z sccache_epilogue 2025-09-07T09:13:54.4937956Z cleanup_workspace' EXIT 2025-09-07T09:13:54.4938579Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-09-07T09:14:17.8820750Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-09-07T09:14:17.8838864Z + echo 'Environment variables:' 2025-09-07T09:14:17.8839204Z Environment variables: 2025-09-07T09:14:17.8839454Z + env 2025-09-07T09:14:17.8848036Z GITHUB_WORKSPACE=/home/david/_work/pytorch/pytorch 2025-09-07T09:14:17.8848447Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:14:17.8848815Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T09:14:17.8851168Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:14:17.8851483Z HOSTNAME=7a3992371752 2025-09-07T09:14:17.8852004Z GITHUB_PATH=/home/david/_work/_temp/_runner_file_commands/add_path_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:17.8852592Z GITHUB_ACTION=__run_2 2025-09-07T09:14:17.8853147Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:14:17.8853456Z GITHUB_RUN_NUMBER=5418 2025-09-07T09:14:17.8853736Z TEST_CONFIG=inductor_torchbench_perf 2025-09-07T09:14:17.8854067Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:14:17.8854401Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:14:17.8854725Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:14:17.8855138Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:14:17.8855436Z GITHUB_TRIGGERING_ACTOR=desertfire 2025-09-07T09:14:17.8855745Z GITHUB_REF_TYPE=branch 2025-09-07T09:14:17.8856044Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:17.8856383Z XLA_CUDA= 2025-09-07T09:14:17.8856602Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:14:17.8857070Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:14:17.8857493Z *** 2025-09-07T09:14:17.8857720Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:14:17.8858015Z GITHUB_ACTIONS=true 2025-09-07T09:14:17.8858283Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:14:17.8858957Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:14:17.8859365Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:17.8859753Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:17.8860418Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly.yml@refs/heads/main 2025-09-07T09:14:17.8861001Z UCC_HOME=/usr 2025-09-07T09:14:17.8861236Z VERBOSE_TEST_LOGS=False 2025-09-07T09:14:17.8861509Z GITHUB_REF=refs/heads/main 2025-09-07T09:14:17.8861778Z SHARD_NUMBER=1 2025-09-07T09:14:17.8862004Z GITHUB_REF_PROTECTED=true 2025-09-07T09:14:17.8862270Z HOME=/var/lib/jenkins 2025-09-07T09:14:17.8862528Z SCCACHE_SERVER_PORT=5230 2025-09-07T09:14:17.8862837Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:14:17.8863165Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:14:17.8863523Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:14:17.8863876Z USE_SYSTEM_NCCL=1 2025-09-07T09:14:17.8864115Z NUM_TEST_SHARDS=6 2025-09-07T09:14:17.8864336Z UCX_HOME=/usr 2025-09-07T09:14:17.8864937Z GITHUB_STATE=/home/david/_work/_temp/_runner_file_commands/save_state_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:17.8865723Z JOB_NAME=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T09:14:17.8866469Z GITHUB_ENV=/home/david/_work/_temp/_runner_file_commands/set_env_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:17.8867142Z GITHUB_EVENT_PATH=/home/david/_work/_temp/_github_workflow/event.json 2025-09-07T09:14:17.8867571Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:14:17.8868886Z 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 2025-09-07T09:14:17.8870242Z GITHUB_RUN_ID=17525309334 2025-09-07T09:14:17.8870516Z INSTALLED_OPENBLAS= 2025-09-07T09:14:17.8871057Z GITHUB_STEP_SUMMARY=/home/david/_work/_temp/_runner_file_commands/step_summary_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:17.8871675Z GITHUB_ACTOR=desertfire 2025-09-07T09:14:17.8871928Z PR_NUMBER= 2025-09-07T09:14:17.8872153Z DESIRED_CUDA=12.8.1 2025-09-07T09:14:17.8872386Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:14:17.8872847Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:14:17.8873207Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:14:17.8873570Z TERM=vt100 2025-09-07T09:14:17.8873780Z INSTALLED_VISION=yes 2025-09-07T09:14:17.8874027Z BRANCH=main 2025-09-07T09:14:17.8874257Z SCCACHE_REGION=us-east-1 2025-09-07T09:14:17.8874533Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:14:17.8874812Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:14:17.8875261Z GITHUB_ACTION_PATH=/home/david/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:14:17.8875774Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:14:17.8876149Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:14:17.8876517Z REENABLED_ISSUES= 2025-09-07T09:14:17.8876752Z DOCS= 2025-09-07T09:14:17.8876960Z SHLVL=1 2025-09-07T09:14:17.8877166Z MAX_JOBS=10 2025-09-07T09:14:17.8877376Z GITHUB_ACTOR_ID=3659962 2025-09-07T09:14:17.8877730Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:17.8878134Z GITHUB_REF_NAME=main 2025-09-07T09:14:17.8878539Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:14:17.8878974Z GITHUB_JOB=test 2025-09-07T09:14:17.8879210Z NO_TEST_TIMEOUT=False 2025-09-07T09:14:17.8879464Z TD_DISTRIBUTED=False 2025-09-07T09:14:17.8879739Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:14:17.8880043Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:14:17.8880309Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:14:17.8880583Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:14:17.8881403Z 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 2025-09-07T09:14:17.8882236Z GITHUB_BASE_REF= 2025-09-07T09:14:17.8882472Z INSTALLED_ACL= 2025-09-07T09:14:17.8883034Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T09:14:17.8883525Z CI=true 2025-09-07T09:14:17.8883745Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:14:17.8884101Z RUST_LOG=sccache::server=error 2025-09-07T09:14:17.8884384Z JOB_ID=49775768449 2025-09-07T09:14:17.8884621Z GITHUB_HEAD_REF= 2025-09-07T09:14:17.8884845Z GITHUB_ACTION_REF= 2025-09-07T09:14:17.8885143Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:14:17.8885512Z TEST_SHOWLOCALS=False 2025-09-07T09:14:17.8885803Z GITHUB_WORKFLOW=inductor-A100-perf-nightly 2025-09-07T09:14:17.8886141Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:14:17.8886694Z GITHUB_OUTPUT=/home/david/_work/_temp/_runner_file_commands/set_output_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:17.8887268Z NO_TD=False 2025-09-07T09:14:17.8887502Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:14:17.8887805Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:14:17.8888124Z _=/usr/bin/env 2025-09-07T09:14:17.8888455Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-09-07T09:14:17.9143671Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-09-07T09:14:17.9144319Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-09-07T09:14:17.9144988Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-09-07T09:14:17.9145601Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-09-07T09:14:17.9146063Z + BUILD_DIR=build 2025-09-07T09:14:17.9146316Z + BUILD_RENAMED_DIR=build_renamed 2025-09-07T09:14:17.9146604Z + BUILD_BIN_DIR=build/bin 2025-09-07T09:14:17.9146864Z + SHARD_NUMBER=1 2025-09-07T09:14:17.9147096Z + NUM_TEST_SHARDS=6 2025-09-07T09:14:17.9147357Z + export TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:14:17.9147668Z + TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:14:17.9147953Z + export VALGRIND=ON 2025-09-07T09:14:17.9148196Z + VALGRIND=ON 2025-09-07T09:14:17.9148520Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *clang9* ]] 2025-09-07T09:14:17.9148944Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *xpu* ]] 2025-09-07T09:14:17.9149308Z + detect_cuda_arch 2025-09-07T09:14:17.9149840Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:14:17.9150223Z + command -v nvidia-smi 2025-09-07T09:14:17.9150473Z /usr/bin/nvidia-smi 2025-09-07T09:14:17.9152464Z ++ nvidia-smi --query-gpu=compute_cap --format=csv 2025-09-07T09:14:17.9153619Z ++ tail -n 1 2025-09-07T09:14:17.9383775Z + TORCH_CUDA_ARCH_LIST=8.0 2025-09-07T09:14:17.9384071Z + export TORCH_CUDA_ARCH_LIST 2025-09-07T09:14:17.9384433Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *s390x* ]] 2025-09-07T09:14:17.9384837Z + [[ 0 == \1 ]] 2025-09-07T09:14:17.9385060Z + [[ True == \1 ]] 2025-09-07T09:14:17.9385350Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *bazel* ]] 2025-09-07T09:14:17.9389007Z ++ realpath build/custom_test_artifacts 2025-09-07T09:14:17.9398158Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-09-07T09:14:17.9398685Z + [[ -n '' ]] 2025-09-07T09:14:17.9398928Z + echo 'Environment variables' 2025-09-07T09:14:17.9399207Z Environment variables 2025-09-07T09:14:17.9399450Z + env 2025-09-07T09:14:17.9405430Z GITHUB_WORKSPACE=/home/david/_work/pytorch/pytorch 2025-09-07T09:14:17.9405815Z CONTINUE_THROUGH_ERROR=True 2025-09-07T09:14:17.9406174Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm80 2025-09-07T09:14:17.9406804Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T09:14:17.9407098Z HOSTNAME=7a3992371752 2025-09-07T09:14:17.9407601Z GITHUB_PATH=/home/david/_work/_temp/_runner_file_commands/add_path_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:17.9408166Z GITHUB_ACTION=__run_2 2025-09-07T09:14:17.9408425Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T09:14:17.9408738Z GITHUB_RUN_NUMBER=5418 2025-09-07T09:14:17.9409015Z TEST_CONFIG=inductor_torchbench_perf 2025-09-07T09:14:17.9409342Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T09:14:18.5333146Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T09:14:18.5333488Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T09:14:18.5334010Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T09:14:18.5345157Z GITHUB_TRIGGERING_ACTOR=desertfire 2025-09-07T09:14:18.5345519Z GITHUB_REF_TYPE=branch 2025-09-07T09:14:18.5345785Z TORCH_CUDA_ARCH_LIST=8.0 2025-09-07T09:14:18.5346109Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:18.5346465Z XLA_CUDA= 2025-09-07T09:14:18.5346709Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T09:14:18.5347230Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T09:14:18.5347624Z *** 2025-09-07T09:14:18.5347851Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T09:14:18.5348143Z GITHUB_ACTIONS=true 2025-09-07T09:14:18.5348398Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T09:14:18.5348744Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T09:14:18.5349156Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:18.5349551Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:18.5350254Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly.yml@refs/heads/main 2025-09-07T09:14:18.5350857Z UCC_HOME=/usr 2025-09-07T09:14:18.5351107Z TORCH_SERIALIZATION_DEBUG=1 2025-09-07T09:14:18.5351393Z VERBOSE_TEST_LOGS=False 2025-09-07T09:14:18.5351669Z GITHUB_REF=refs/heads/main 2025-09-07T09:14:18.5351942Z SHARD_NUMBER=1 2025-09-07T09:14:18.5352189Z GITHUB_REF_PROTECTED=true 2025-09-07T09:14:18.5352447Z HOME=/var/lib/jenkins 2025-09-07T09:14:18.5352712Z SCCACHE_SERVER_PORT=5230 2025-09-07T09:14:18.5353024Z GITHUB_API_URL=https://api.github.com 2025-09-07T09:14:18.5353373Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T09:14:18.5353722Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T09:14:18.5354079Z USE_SYSTEM_NCCL=1 2025-09-07T09:14:18.5354320Z NUM_TEST_SHARDS=6 2025-09-07T09:14:18.5354555Z UCX_HOME=/usr 2025-09-07T09:14:18.5355041Z GITHUB_STATE=/home/david/_work/_temp/_runner_file_commands/save_state_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:18.5355819Z JOB_NAME=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T09:14:18.5356564Z GITHUB_ENV=/home/david/_work/_temp/_runner_file_commands/set_env_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:18.5357529Z GITHUB_EVENT_PATH=/home/david/_work/_temp/_github_workflow/event.json 2025-09-07T09:14:18.5357962Z GITHUB_EVENT_NAME=schedule 2025-09-07T09:14:18.5359273Z 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 2025-09-07T09:14:18.5360612Z GITHUB_RUN_ID=17525309334 2025-09-07T09:14:18.5360885Z INSTALLED_OPENBLAS= 2025-09-07T09:14:18.5361444Z GITHUB_STEP_SUMMARY=/home/david/_work/_temp/_runner_file_commands/step_summary_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:18.5362052Z GITHUB_ACTOR=desertfire 2025-09-07T09:14:18.5362313Z PR_NUMBER= 2025-09-07T09:14:18.5362539Z DESIRED_CUDA=12.8.1 2025-09-07T09:14:18.5362796Z GITHUB_RUN_ATTEMPT=1 2025-09-07T09:14:18.5363033Z VALGRIND=ON 2025-09-07T09:14:18.5363274Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T09:14:18.5363628Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T09:14:18.5363995Z TERM=vt100 2025-09-07T09:14:18.5364206Z INSTALLED_VISION=yes 2025-09-07T09:14:18.5364458Z BRANCH=main 2025-09-07T09:14:18.5364693Z SCCACHE_REGION=us-east-1 2025-09-07T09:14:18.5364966Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T09:14:18.5365262Z CUDA_PATH=/usr/local/cuda 2025-09-07T09:14:18.5365720Z GITHUB_ACTION_PATH=/home/david/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T09:14:18.5366241Z GITHUB_SERVER_URL=https://github.com 2025-09-07T09:14:18.5366616Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T09:14:18.5366960Z REENABLED_ISSUES= 2025-09-07T09:14:18.5367202Z DOCS= 2025-09-07T09:14:18.5367411Z SHLVL=1 2025-09-07T09:14:18.5367608Z MAX_JOBS=10 2025-09-07T09:14:18.5367836Z GITHUB_ACTOR_ID=3659962 2025-09-07T09:14:18.5368406Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T09:14:18.5368811Z GITHUB_REF_NAME=main 2025-09-07T09:14:18.5369194Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T09:14:18.5369650Z GITHUB_JOB=test 2025-09-07T09:14:18.5369898Z NO_TEST_TIMEOUT=False 2025-09-07T09:14:18.5370161Z TD_DISTRIBUTED=False 2025-09-07T09:14:18.5370425Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T09:14:18.5370741Z GITHUB_RETENTION_DAYS=90 2025-09-07T09:14:18.5371022Z OPENSSL_DIR=/opt/openssl 2025-09-07T09:14:18.5371303Z GITHUB_ACTION_REPOSITORY= 2025-09-07T09:14:18.5372105Z 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 2025-09-07T09:14:18.5373128Z GITHUB_BASE_REF= 2025-09-07T09:14:18.5373378Z INSTALLED_ACL= 2025-09-07T09:14:18.5373813Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T09:14:18.5374308Z CI=true 2025-09-07T09:14:18.5374528Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T09:14:18.5374869Z RUST_LOG=sccache::server=error 2025-09-07T09:14:18.5375154Z JOB_ID=49775768449 2025-09-07T09:14:18.5375392Z GITHUB_HEAD_REF= 2025-09-07T09:14:18.5375623Z GITHUB_ACTION_REF= 2025-09-07T09:14:18.5375931Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T09:14:18.5376299Z TEST_SHOWLOCALS=False 2025-09-07T09:14:18.5376582Z GITHUB_WORKFLOW=inductor-A100-perf-nightly 2025-09-07T09:14:18.5376933Z DEBIAN_FRONTEND=noninteractive 2025-09-07T09:14:18.5377494Z GITHUB_OUTPUT=/home/david/_work/_temp/_runner_file_commands/set_output_44378947-e14c-4abf-8942-de4f3f193167 2025-09-07T09:14:18.5378068Z NO_TD=False 2025-09-07T09:14:18.5378314Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T09:14:18.5378627Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T09:14:18.5378954Z _=/usr/bin/env 2025-09-07T09:14:18.5379194Z + echo 'Testing pytorch' 2025-09-07T09:14:18.5379463Z Testing pytorch 2025-09-07T09:14:18.5379705Z + export LANG=C.UTF-8 2025-09-07T09:14:18.5379961Z + LANG=C.UTF-8 2025-09-07T09:14:18.5380191Z + PR_NUMBER= 2025-09-07T09:14:18.5380454Z + [[ inductor_torchbench_perf == \d\e\f\a\u\l\t ]] 2025-09-07T09:14:18.5381084Z + [[ inductor_torchbench_perf == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-09-07T09:14:18.5381498Z + [[ inductor_torchbench_perf == \s\l\o\w ]] 2025-09-07T09:14:18.5381946Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *slow-gradcheck* ]] 2025-09-07T09:14:18.5382436Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:14:18.5382835Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:14:18.5383207Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T09:14:18.5383567Z + [[ inductor_torchbench_perf == *crossref* ]] 2025-09-07T09:14:18.5383973Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:14:18.5384387Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *xpu* ]] 2025-09-07T09:14:18.5384915Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *-bazel-* ]] 2025-09-07T09:14:18.5385326Z + pip_install ninja==1.10.2 2025-09-07T09:14:18.5385716Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:14:18.5386191Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-09-07T09:14:18.9916837Z Collecting ninja==1.10.2 2025-09-07T09:14:19.0333690Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-09-07T09:14:19.6118265Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-09-07T09:14:20.5304150Z Installing collected packages: ninja 2025-09-07T09:14:20.5304943Z Attempting uninstall: ninja 2025-09-07T09:14:20.5314414Z Found existing installation: ninja 1.11.1.3 2025-09-07T09:14:20.5335227Z Uninstalling ninja-1.11.1.3: 2025-09-07T09:14:20.7349837Z Successfully uninstalled ninja-1.11.1.3 2025-09-07T09:14:20.9224942Z Successfully installed ninja-1.10.2 2025-09-07T09:14:21.0111063Z + 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 2025-09-07T09:14:21.0113216Z + 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 2025-09-07T09:14:21.0114260Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *aarch64* ]] 2025-09-07T09:14:21.0114720Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *asan* ]] 2025-09-07T09:14:21.0115201Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-debug* ]] 2025-09-07T09:14:21.0115646Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 != *-bazel-* ]] 2025-09-07T09:14:21.0116256Z + echo 'We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm80. Expect the assertion to pass' 2025-09-07T09:14:21.0117018Z We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm80. Expect the assertion to pass 2025-09-07T09:14:21.0117536Z + cd test 2025-09-07T09:14:21.0117892Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-09-07T09:14:21.6524669Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:21.6526092Z import pynvml # type: ignore[import] 2025-09-07T09:14:22.9108245Z + [[ inductor_torchbench_perf == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-09-07T09:14:22.9108760Z + [[ inductor_torchbench_perf == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-09-07T09:14:22.9109275Z + [[ inductor_torchbench_perf == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-09-07T09:14:22.9111817Z + DYNAMO_BENCHMARK_FLAGS=() 2025-09-07T09:14:22.9112818Z + [[ inductor_torchbench_perf == *pr_time_benchmarks* ]] 2025-09-07T09:14:22.9113223Z + [[ inductor_torchbench_perf == *dynamo_eager* ]] 2025-09-07T09:14:22.9113625Z + [[ inductor_torchbench_perf == *aot_eager* ]] 2025-09-07T09:14:22.9114044Z + [[ inductor_torchbench_perf == *aot_inductor* ]] 2025-09-07T09:14:22.9114463Z + [[ inductor_torchbench_perf == *max_autotune_inductor* ]] 2025-09-07T09:14:22.9122717Z + [[ inductor_torchbench_perf == *inductor* ]] 2025-09-07T09:14:22.9123317Z + [[ inductor_torchbench_perf != *perf* ]] 2025-09-07T09:14:22.9123678Z + [[ inductor_torchbench_perf == *dynamic* ]] 2025-09-07T09:14:22.9124037Z + [[ inductor_torchbench_perf == *cpu* ]] 2025-09-07T09:14:22.9124396Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-09-07T09:14:22.9135599Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *libtorch* ]] 2025-09-07T09:14:22.9136076Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *-bazel-* ]] 2025-09-07T09:14:22.9139631Z + cd test 2025-09-07T09:14:22.9140000Z + python -c 'import torch; print(torch.__config__.show())' 2025-09-07T09:14:23.4993866Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:23.4995291Z import pynvml # type: ignore[import] 2025-09-07T09:14:26.1229755Z PyTorch built with: 2025-09-07T09:14:26.1230055Z - GCC 9.5 2025-09-07T09:14:26.1230288Z - C++ Version: 201703 2025-09-07T09:14:26.1230880Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:14:26.1231632Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:14:26.1232095Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:14:26.1232433Z - LAPACK is enabled (usually provided by MKL) 2025-09-07T09:14:26.1232780Z - NNPACK is enabled 2025-09-07T09:14:26.1233052Z - CPU capability usage: AVX512 2025-09-07T09:14:26.1233346Z - CUDA Runtime 12.8 2025-09-07T09:14:26.1233688Z - NVCC architecture flags: -gencode;arch=compute_80,code=sm_80 2025-09-07T09:14:26.1234458Z - CuDNN 90.8 2025-09-07T09:14:26.1239275Z - 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, 2025-09-07T09:14:26.1244247Z 2025-09-07T09:14:27.0712696Z + cd test 2025-09-07T09:14:27.0713573Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-09-07T09:14:27.6740413Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:27.6743489Z import pynvml # type: ignore[import] 2025-09-07T09:14:28.4949629Z ATen/Parallel: 2025-09-07T09:14:28.4949998Z at::get_num_threads() : 12 2025-09-07T09:14:28.4950304Z at::get_num_interop_threads() : 48 2025-09-07T09:14:28.4950624Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T09:14:28.4950969Z omp_get_max_threads() : 12 2025-09-07T09:14:28.4951553Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T09:14:28.4952159Z mkl_get_max_threads() : 12 2025-09-07T09:14:28.4952978Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T09:14:28.4953455Z std::thread::hardware_concurrency() : 96 2025-09-07T09:14:28.4953794Z Environment variables: 2025-09-07T09:14:28.4954052Z OMP_NUM_THREADS : [not set] 2025-09-07T09:14:28.4954342Z MKL_NUM_THREADS : [not set] 2025-09-07T09:14:28.4954636Z ATen parallel backend: OpenMP 2025-09-07T09:14:28.4954826Z 2025-09-07T09:14:28.8405965Z + [[ inductor_torchbench_perf == *numpy_2* ]] 2025-09-07T09:14:28.8406439Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *aarch64* ]] 2025-09-07T09:14:28.8406862Z + [[ inductor_torchbench_perf == *backward* ]] 2025-09-07T09:14:28.8407220Z + [[ inductor_torchbench_perf == *xla* ]] 2025-09-07T09:14:28.8407567Z + [[ inductor_torchbench_perf == *vllm* ]] 2025-09-07T09:14:28.8407949Z + [[ inductor_torchbench_perf == *executorch* ]] 2025-09-07T09:14:28.8408351Z + [[ inductor_torchbench_perf == \j\i\t\_\l\e\g\a\c\y ]] 2025-09-07T09:14:28.8408799Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *libtorch* ]] 2025-09-07T09:14:28.8409220Z + [[ inductor_torchbench_perf == distributed ]] 2025-09-07T09:14:28.8409611Z + [[ inductor_torchbench_perf == *operator_benchmark* ]] 2025-09-07T09:14:28.8410053Z + [[ inductor_torchbench_perf == *inductor_distributed* ]] 2025-09-07T09:14:28.8410487Z + [[ inductor_torchbench_perf == *inductor-halide* ]] 2025-09-07T09:14:28.8410918Z + [[ inductor_torchbench_perf == *inductor-triton-cpu* ]] 2025-09-07T09:14:28.8411386Z + [[ inductor_torchbench_perf == *inductor-micro-benchmark* ]] 2025-09-07T09:14:28.8411820Z + [[ inductor_torchbench_perf == *huggingface* ]] 2025-09-07T09:14:28.8412192Z + [[ inductor_torchbench_perf == *timm* ]] 2025-09-07T09:14:28.8412546Z + [[ inductor_torchbench_perf == cachebench ]] 2025-09-07T09:14:28.9273441Z + [[ inductor_torchbench_perf == verify_cachebench ]] 2025-09-07T09:14:28.9273826Z + [[ inductor_torchbench_perf == *torchbench* ]] 2025-09-07T09:14:28.9274171Z + install_torchaudio 2025-09-07T09:14:28.9274450Z + local commit 2025-09-07T09:14:28.9274689Z ++ get_pinned_commit audio 2025-09-07T09:14:28.9274964Z ++ cat .github/ci_commit_pins/audio.txt 2025-09-07T09:14:28.9276261Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:14:28.9276970Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio 2025-09-07T09:14:28.9277859Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T09:14:28.9278439Z + local wheel_dir=dist/audio 2025-09-07T09:14:28.9278706Z + local found_whl=0 2025-09-07T09:14:28.9278957Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:28.9279411Z + [[ -f dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:14:28.9279875Z + found_whl=1 2025-09-07T09:14:28.9280079Z + break 2025-09-07T09:14:28.9280281Z + '[' 1 == 0 ']' 2025-09-07T09:14:28.9280531Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:28.9281026Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:28.9281667Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:14:28.9282120Z + local args 2025-09-07T09:14:28.9282512Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:14:28.9283002Z + for path in "${args[@]}" 2025-09-07T09:14:28.9283455Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:14:28.9284136Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:28.9284913Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.2849700Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.2931463Z Installing collected packages: torchaudio 2025-09-07T09:14:29.6127963Z Successfully installed torchaudio-2.8.0a0+2e30055 2025-09-07T09:14:29.6537341Z + install_torchvision 2025-09-07T09:14:29.6537655Z + local orig_preload 2025-09-07T09:14:29.6537904Z + local commit 2025-09-07T09:14:29.6541074Z ++ get_pinned_commit vision 2025-09-07T09:14:29.6541430Z ++ cat .github/ci_commit_pins/vision.txt 2025-09-07T09:14:29.6552815Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:14:29.6553182Z + orig_preload= 2025-09-07T09:14:29.6553422Z + '[' -n '' ']' 2025-09-07T09:14:29.6553732Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *cuda* ]] 2025-09-07T09:14:29.6554096Z + export FORCE_CUDA=1 2025-09-07T09:14:29.6554349Z + FORCE_CUDA=1 2025-09-07T09:14:29.6554576Z + export WITH_CUDA=1 2025-09-07T09:14:29.6554819Z + WITH_CUDA=1 2025-09-07T09:14:29.6555400Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-09-07T09:14:29.6556356Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T09:14:29.6556954Z + local wheel_dir=dist/vision 2025-09-07T09:14:29.6557246Z + local found_whl=0 2025-09-07T09:14:29.6557503Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:29.6557964Z + [[ -f dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:14:29.6558437Z + found_whl=1 2025-09-07T09:14:29.6558661Z + break 2025-09-07T09:14:29.6558869Z + '[' 1 == 0 ']' 2025-09-07T09:14:29.6559099Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:29.6559607Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.6560296Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:14:29.6560767Z + local args 2025-09-07T09:14:29.6561161Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:14:29.6562043Z + for path in "${args[@]}" 2025-09-07T09:14:29.6562539Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:14:29.6563269Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:29.6564072Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:30.0162109Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:30.0285038Z Installing collected packages: torchvision 2025-09-07T09:14:31.0279732Z Successfully installed torchvision-0.22.0a0+966da7e 2025-09-07T09:14:31.0980003Z + '[' -n '' ']' 2025-09-07T09:14:31.0980295Z + id=0 2025-09-07T09:14:31.0980532Z + pip_install opencv-python==4.8.0.74 2025-09-07T09:14:31.0980955Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:14:31.0981470Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74 2025-09-07T09:14:31.9833081Z Collecting opencv-python==4.8.0.74 2025-09-07T09:14:32.0254423Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB) 2025-09-07T09:14:32.4643807Z 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) 2025-09-07T09:14:32.4789059Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB) 2025-09-07T09:14:38.3981699Z Installing collected packages: opencv-python 2025-09-07T09:14:38.3982254Z Attempting uninstall: opencv-python 2025-09-07T09:14:38.3997801Z Found existing installation: opencv-python 4.11.0.86 2025-09-07T09:14:38.4089438Z Uninstalling opencv-python-4.11.0.86: 2025-09-07T09:14:38.5749557Z Successfully uninstalled opencv-python-4.11.0.86 2025-09-07T09:14:39.8533566Z Successfully installed opencv-python-4.8.0.74 2025-09-07T09:14:39.9571468Z + [[ inductor_torchbench_perf == *inductor_torchbench_smoketest_perf* ]] 2025-09-07T09:14:39.9572092Z + [[ inductor_torchbench_perf == *inductor_torchbench_cpu_smoketest_perf* ]] 2025-09-07T09:14:39.9573329Z + [[ inductor_torchbench_perf == *torchbench_gcp_smoketest* ]] 2025-09-07T09:14:39.9573765Z + [[ inductor_torchbench_perf != *cpu* ]] 2025-09-07T09:14:39.9574101Z + install_torchrec_and_fbgemm 2025-09-07T09:14:39.9574379Z + local torchrec_commit 2025-09-07T09:14:39.9575501Z ++ get_pinned_commit torchrec 2025-09-07T09:14:39.9575821Z ++ cat .github/ci_commit_pins/torchrec.txt 2025-09-07T09:14:39.9587671Z + torchrec_commit=6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:14:39.9591846Z + local fbgemm_commit 2025-09-07T09:14:39.9592149Z ++ get_pinned_commit fbgemm 2025-09-07T09:14:39.9592461Z ++ cat .github/ci_commit_pins/fbgemm.txt 2025-09-07T09:14:39.9603177Z + fbgemm_commit=de731af65b4f04696e85c729e3282450b51b95fd 2025-09-07T09:14:39.9603638Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:14:39.9604037Z + pip_uninstall torchrec-nightly 2025-09-07T09:14:39.9604369Z + pip3 uninstall -y torchrec-nightly 2025-09-07T09:14:40.3236849Z WARNING: Skipping torchrec-nightly as it is not installed. 2025-09-07T09:14:40.3622111Z + pip_uninstall fbgemm-gpu-nightly 2025-09-07T09:14:40.3622493Z + pip3 uninstall -y fbgemm-gpu-nightly 2025-09-07T09:14:40.7271435Z WARNING: Skipping fbgemm-gpu-nightly as it is not installed. 2025-09-07T09:14:40.7641136Z + pip_install setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:14:40.7641711Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T09:14:40.7642375Z + python3 -m pip install --progress-bar off setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T09:14:41.1229966Z Requirement already satisfied: setuptools-git-versioning in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (2.1.0) 2025-09-07T09:14:41.1232428Z Requirement already satisfied: scikit-build in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.18.1) 2025-09-07T09:14:41.1234973Z Requirement already satisfied: pyre-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.0.32) 2025-09-07T09:14:41.1247729Z Requirement already satisfied: packaging in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (25.0) 2025-09-07T09:14:41.1251351Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (80.9.0) 2025-09-07T09:14:41.1258892Z 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) 2025-09-07T09:14:41.1305739Z Requirement already satisfied: distro in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (1.9.0) 2025-09-07T09:14:41.1314850Z 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) 2025-09-07T09:14:41.1323111Z Requirement already satisfied: typing-inspect in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (0.9.0) 2025-09-07T09:14:41.1326719Z Requirement already satisfied: typing-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (4.15.0) 2025-09-07T09:14:41.1408938Z 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) 2025-09-07T09:14:42.2033805Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm80 == *rocm* ]] 2025-09-07T09:14:42.2034604Z + pip_build_and_install git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 dist/torchrec 2025-09-07T09:14:42.2035578Z + local build_target=git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T09:14:42.2036185Z + local wheel_dir=dist/torchrec 2025-09-07T09:14:42.2036480Z + local found_whl=0 2025-09-07T09:14:42.2036738Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:42.2037132Z + [[ -f dist/torchrec/torchrec-0.3.2-py3-none-any.whl ]] 2025-09-07T09:14:42.2037498Z + found_whl=1 2025-09-07T09:14:42.2037716Z + break 2025-09-07T09:14:42.2037919Z + '[' 1 == 0 ']' 2025-09-07T09:14:42.2038511Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:42.2038921Z + pip_install_whl dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:42.2039402Z + args=('dist/torchrec/torchrec-0.3.2-py3-none-any.whl') 2025-09-07T09:14:42.2039772Z + local args 2025-09-07T09:14:42.2040078Z + [[ dist/torchrec/torchrec-0.3.2-py3-none-any.whl == *\ * ]] 2025-09-07T09:14:42.2040484Z + for path in "${args[@]}" 2025-09-07T09:14:42.2040874Z + echo 'Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl' 2025-09-07T09:14:42.2041381Z Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:42.2041955Z + python3 -mpip install --no-index --no-deps dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:42.5652028Z Processing ./dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T09:14:42.5729217Z Installing collected packages: torchrec 2025-09-07T09:14:43.2565583Z Successfully installed torchrec-0.3.2 2025-09-07T09:14:43.2960767Z + pip_build_and_install git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu dist/fbgemm_gpu 2025-09-07T09:14:43.2961955Z + local build_target=git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu 2025-09-07T09:14:43.2962693Z + local wheel_dir=dist/fbgemm_gpu 2025-09-07T09:14:43.2962981Z + local found_whl=0 2025-09-07T09:14:43.2963242Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:43.2963699Z + [[ -f dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T09:14:43.2964164Z + found_whl=1 2025-09-07T09:14:43.2964376Z + break 2025-09-07T09:14:43.2964592Z + '[' 1 == 0 ']' 2025-09-07T09:14:43.2964842Z + for file in "${wheel_dir}"/*.whl 2025-09-07T09:14:43.2965334Z + pip_install_whl dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:43.2966323Z + args=('dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl') 2025-09-07T09:14:43.2966791Z + local args 2025-09-07T09:14:43.2967199Z + [[ dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T09:14:43.2967697Z + for path in "${args[@]}" 2025-09-07T09:14:43.2968172Z + echo 'Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl' 2025-09-07T09:14:43.2968852Z Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:43.2969641Z + python3 -mpip install --no-index --no-deps dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:43.6540008Z Processing ./dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T09:14:43.9369621Z Installing collected packages: fbgemm-gpu 2025-09-07T09:14:46.4678184Z Successfully installed fbgemm-gpu-0.4.1.post421 2025-09-07T09:14:46.5077527Z + PYTHONPATH=/torchbench 2025-09-07T09:14:46.5077831Z + test_dynamo_benchmark torchbench 0 2025-09-07T09:14:46.5081924Z ++ pwd 2025-09-07T09:14:46.5083852Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:46.5084303Z + local suite=torchbench 2025-09-07T09:14:46.5084566Z + shift 2025-09-07T09:14:46.5084761Z + local shard_id=0 2025-09-07T09:14:46.5084989Z + shift 2025-09-07T09:14:46.5085241Z + [[ inductor_torchbench_perf == *perf_compare* ]] 2025-09-07T09:14:46.5085616Z + [[ inductor_torchbench_perf == *perf* ]] 2025-09-07T09:14:46.5085946Z + [[ inductor_torchbench_perf == *b200* ]] 2025-09-07T09:14:46.5086327Z + test_single_dynamo_benchmark dashboard torchbench 0 2025-09-07T09:14:46.5088926Z ++ pwd 2025-09-07T09:14:46.5090782Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:46.5091245Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:46.5107422Z + local name=dashboard 2025-09-07T09:14:46.5107689Z + shift 2025-09-07T09:14:46.5107918Z + local suite=torchbench 2025-09-07T09:14:46.5108157Z + shift 2025-09-07T09:14:46.5108359Z + local shard_id=0 2025-09-07T09:14:46.5108585Z + shift 2025-09-07T09:14:46.5108799Z + partition_flags=() 2025-09-07T09:14:46.5109397Z + local partition_flags 2025-09-07T09:14:46.5109657Z + [[ -n 6 ]] 2025-09-07T09:14:46.5109874Z + [[ -n 0 ]] 2025-09-07T09:14:46.5110296Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id") 2025-09-07T09:14:46.5110838Z + [[ inductor_torchbench_perf == *perf_compare* ]] 2025-09-07T09:14:46.5111218Z + [[ inductor_torchbench_perf == *perf* ]] 2025-09-07T09:14:46.5111741Z + test_perf_for_dashboard torchbench --device cuda --total-partitions 6 --partition-id 0 2025-09-07T09:14:46.5112250Z ++ pwd 2025-09-07T09:14:46.5113911Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:46.5114376Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T09:14:46.5126243Z + local suite=torchbench 2025-09-07T09:14:46.5126531Z + shift 2025-09-07T09:14:46.5126749Z + local backend=inductor 2025-09-07T09:14:46.5126996Z + modes=() 2025-09-07T09:14:46.5127206Z + local modes 2025-09-07T09:14:46.5128509Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *training-true* ]] 2025-09-07T09:14:46.5129912Z + modes+=(training) 2025-09-07T09:14:46.5131226Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *inference-true* ]] 2025-09-07T09:14:46.5132602Z + modes+=(inference) 2025-09-07T09:14:46.5133105Z + targets=('accuracy' 'performance') 2025-09-07T09:14:46.5133415Z + local targets 2025-09-07T09:14:46.5133648Z + local device=cuda 2025-09-07T09:14:46.5133903Z + [[ inductor_torchbench_perf == *cpu* ]] 2025-09-07T09:14:46.5134500Z + [[ inductor_torchbench_perf == *cuda_a10g* ]] 2025-09-07T09:14:46.5134862Z + [[ inductor_torchbench_perf == *h100* ]] 2025-09-07T09:14:46.5135207Z + [[ inductor_torchbench_perf == *b200* ]] 2025-09-07T09:14:46.5135549Z + [[ inductor_torchbench_perf == *rocm* ]] 2025-09-07T09:14:46.5135865Z + for mode in "${modes[@]}" 2025-09-07T09:14:46.5136152Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:14:46.5136463Z + [[ training == \t\r\a\i\n\i\n\g ]] 2025-09-07T09:14:46.5136752Z + dtype=amp 2025-09-07T09:14:46.5136965Z + for target in "${targets[@]}" 2025-09-07T09:14:46.5137258Z + target_flag=('--accuracy') 2025-09-07T09:14:46.5137530Z + local target_flag 2025-09-07T09:14:46.5137773Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:14:46.5138092Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T09:14:46.5138429Z + target_flag+=(--no-translation-validation) 2025-09-07T09:14:46.5139847Z + [[ 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* ]] 2025-09-07T09:14:46.5142285Z + [[ 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* ]] 2025-09-07T09:14:46.5144923Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:14:47.1119801Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:47.1121350Z import pynvml # type: ignore[import] 2025-09-07T09:14:51.1449041Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:51.1450487Z import pynvml # type: ignore[import] 2025-09-07T09:14:53.8510611Z 2025-09-07T09:14:54.0553911Z loading model: 0it [00:00, ?it/s][rank0]:W0907 09:14:54.054000 204 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T09:14:55.0385879Z 2025-09-07T09:14:55.0386435Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:14:55.0387086Z cuda train torchrec_dlrm 2025-09-07T09:15:07.9641062Z [rank0]:W0907 09:15:07.963000 204 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:15:16.5204259Z pass 2025-09-07T09:15:19.1326601Z [rank0]:[W907 09:15:19.418827352 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T09:15:20.4372695Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:15:20.4375762Z import pynvml # type: ignore[import] 2025-09-07T09:15:23.2531869Z 2025-09-07T09:15:25.8516829Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:25.8517721Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:15:25.8518054Z cuda train BERT_pytorch 2025-09-07T09:16:03.4965437Z pass 2025-09-07T09:16:07.3562518Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:07.3565272Z import pynvml # type: ignore[import] 2025-09-07T09:16:10.2241852Z 2025-09-07T09:16:14.1164630Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:16:14.1165011Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:16:14.1165345Z cuda train Background_Matting 2025-09-07T09:16:14.1398833Z pass_due_to_skip 2025-09-07T09:16:15.9333680Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:15.9335147Z import pynvml # type: ignore[import] 2025-09-07T09:16:18.7039367Z 2025-09-07T09:16:22.3671362Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:16:22.3671757Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:16:22.3672088Z cuda train LearningToPaint 2025-09-07T09:16:36.4251234Z pass 2025-09-07T09:16:39.8631982Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:39.8634416Z import pynvml # type: ignore[import] 2025-09-07T09:16:42.6152942Z 2025-09-07T09:16:44.1947541Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/vgg16-397923af.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/vgg16-397923af.pth 2025-09-07T09:16:44.2124402Z 2025-09-07T09:16:44.2124524Z 2025-09-07T09:16:44.3129911Z 0% 0.00/528M [00:00 will be ignored 2025-09-07T09:17:53.1883256Z pass 2025-09-07T09:17:57.5380224Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:17:57.5381663Z import pynvml # type: ignore[import] 2025-09-07T09:18:00.4801421Z 2025-09-07T09:18:01.0699151Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/alexnet-owt-7be5be79.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/alexnet-owt-7be5be79.pth 2025-09-07T09:18:01.0907621Z 2025-09-07T09:18:01.0907653Z 2025-09-07T09:18:01.1914469Z 0% 0.00/233M [00:00 will be ignored 2025-09-07T09:18:40.7006668Z pass 2025-09-07T09:18:43.8438278Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:18:43.8440229Z import pynvml # type: ignore[import] 2025-09-07T09:18:46.6093872Z 2025-09-07T09:18:49.1278948Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:18:49.1279310Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:18:49.1279638Z cuda train basic_gnn_gcn 2025-09-07T09:18:56.6431910Z W0907 09:18:56.642000 7655 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T09:18:58.1466359Z pass 2025-09-07T09:19:01.1116966Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:19:01.1119595Z import pynvml # type: ignore[import] 2025-09-07T09:19:03.8710005Z 2025-09-07T09:19:06.2688735Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:19:06.2689341Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:19:06.2689941Z cuda train basic_gnn_gin 2025-09-07T09:19:13.2299991Z W0907 09:19:13.229000 8001 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:19:16.2505487Z pass 2025-09-07T09:19:19.4283235Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:19:19.4287722Z import pynvml # type: ignore[import] 2025-09-07T09:19:22.0826065Z 2025-09-07T09:19:24.7572349Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:19:24.7572741Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:19:24.7573343Z cuda train basic_gnn_sage 2025-09-07T09:19:30.8335722Z W0907 09:19:30.832000 8281 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:19:33.6065787Z pass 2025-09-07T09:19:36.6642456Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:19:36.6643880Z import pynvml # type: ignore[import] 2025-09-07T09:19:39.3919713Z 2025-09-07T09:19:40.0666891Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:19:40.0667517Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:19:40.0668036Z cuda train dcgan 2025-09-07T09:19:46.8763644Z pass 2025-09-07T09:19:49.9445659Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:19:49.9447090Z import pynvml # type: ignore[import] 2025-09-07T09:19:52.6273716Z 2025-09-07T09:19:56.0152756Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:19:56.0153392Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:19:56.0153949Z cuda train demucs 2025-09-07T09:20:24.5306834Z pass 2025-09-07T09:20:27.7720694Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:20:27.7722115Z import pynvml # type: ignore[import] 2025-09-07T09:20:30.5802411Z 2025-09-07T09:20:30.9683187Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/densenet121-a639ec97.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/densenet121-a639ec97.pth 2025-09-07T09:20:30.9944422Z 2025-09-07T09:20:30.9945284Z 2025-09-07T09:20:31.0951165Z 0% 0.00/30.8M [00:00 will be ignored 2025-09-07T09:22:29.2795543Z pass 2025-09-07T09:22:31.4377221Z [rank0]:[W907 09:22:31.724014260 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T09:22:32.6795606Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:22:32.6801457Z import pynvml # type: ignore[import] 2025-09-07T09:22:35.4824321Z 2025-09-07T09:22:38.0763526Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:22:38.0763937Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:22:38.0764268Z cuda train BERT_pytorch 2025-09-07T09:23:11.6683943Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:23:11.6685208Z pred = mod(*cloned_inputs) 2025-09-07T09:23:11.6685820Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward 2025-09-07T09:23:11.6686478Z x = self.bert(x, segment_label) 2025-09-07T09:23:11.6687057Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward 2025-09-07T09:23:11.6687707Z x = self.embedding(x, segment_info) 2025-09-07T09:23:11.6688336Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward 2025-09-07T09:23:11.6689145Z x = self.token(sequence) + self.position(sequence) + self.segment(segment_label) 2025-09-07T09:23:11.6689530Z 2025-09-07T09:23:11.6689535Z 2025-09-07T09:23:12.1170433Z pass 2025-09-07T09:23:15.9477512Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:23:15.9478931Z import pynvml # type: ignore[import] 2025-09-07T09:23:18.7350794Z 2025-09-07T09:23:22.8659371Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:23:22.8659745Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:23:22.8660080Z cuda train Background_Matting 2025-09-07T09:23:22.8891336Z pass_due_to_skip 2025-09-07T09:23:24.6380078Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:23:24.6381520Z import pynvml # type: ignore[import] 2025-09-07T09:23:27.5140253Z 2025-09-07T09:23:31.0137417Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:23:31.0137819Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:23:31.0138155Z cuda train LearningToPaint 2025-09-07T09:23:44.6677624Z pass 2025-09-07T09:23:48.2487592Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:23:48.2489040Z import pynvml # type: ignore[import] 2025-09-07T09:23:50.9308431Z 2025-09-07T09:23:53.6763870Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:23:53.6764275Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:23:53.6764647Z cuda train Super_SloMo 2025-09-07T09:24:40.7460313Z W0907 09:24:40.745000 14443 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:24:53.6738330Z pass 2025-09-07T09:24:57.9686542Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:24:57.9687965Z import pynvml # type: ignore[import] 2025-09-07T09:25:00.7272069Z 2025-09-07T09:25:02.6547255Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:25:02.6548229Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:25:02.6548556Z cuda train alexnet 2025-09-07T09:25:17.4397746Z pass 2025-09-07T09:25:20.6466578Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:25:20.6468005Z import pynvml # type: ignore[import] 2025-09-07T09:25:23.4906155Z 2025-09-07T09:25:26.0234009Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:25:26.0234401Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:25:26.0234732Z cuda train basic_gnn_edgecnn 2025-09-07T09:25:30.1388728Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in torch_dynamo_resume_in_scatter_at_93 2025-09-07T09:25:30.1390037Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T09:25:30.1390289Z 2025-09-07T09:25:30.1390294Z 2025-09-07T09:25:32.6202380Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpjhs9_hcl.py", line 190, in propagate 2025-09-07T09:25:32.6203341Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T09:25:32.6203802Z File "/tmp/jenkins_pyg/tmpjhs9_hcl.py", line 141, in _collect 2025-09-07T09:25:32.6204214Z x_i = self._lift(x_i, edge_def, i) 2025-09-07T09:25:32.6204600Z File "/tmp/jenkins_pyg/tmpjhs9_hcl.py", line 88, in _lift 2025-09-07T09:25:32.6205026Z return src.index_select(self.node_dim, index) 2025-09-07T09:25:32.6205277Z 2025-09-07T09:25:32.6205282Z 2025-09-07T09:25:32.6548465Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpjhs9_hcl.py", line 190, in propagate 2025-09-07T09:25:32.6549391Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T09:25:32.6549855Z File "/tmp/jenkins_pyg/tmpjhs9_hcl.py", line 141, in _collect 2025-09-07T09:25:32.6550652Z x_i = self._lift(x_i, edge_def, i) 2025-09-07T09:25:32.6551042Z File "/tmp/jenkins_pyg/tmpjhs9_hcl.py", line 88, in _lift 2025-09-07T09:25:32.6551453Z return src.index_select(self.node_dim, index) 2025-09-07T09:25:32.6551721Z 2025-09-07T09:25:32.6551726Z 2025-09-07T09:25:33.0152026Z W0907 09:25:33.014000 14718 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T09:25:34.8535169Z pass 2025-09-07T09:25:37.9705130Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:25:37.9706577Z import pynvml # type: ignore[import] 2025-09-07T09:25:40.9713052Z 2025-09-07T09:25:43.5018551Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:25:43.5018972Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:25:43.5019303Z cuda train basic_gnn_gcn 2025-09-07T09:25:46.9814881Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T09:25:46.9817441Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T09:25:46.9818770Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:25:46.9819999Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:25:46.9820497Z 2025-09-07T09:25:46.9820506Z 2025-09-07T09:25:47.3436980Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp_ob_pmbn.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:25:47.3438895Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:25:47.3439685Z File "/tmp/jenkins_pyg/tmp_ob_pmbn.py", line 188, in propagate 2025-09-07T09:25:47.3440664Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:25:47.3442098Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:25:47.3443373Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:25:47.3444566Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:25:47.3445710Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:25:47.3446978Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:25:47.3448045Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:25:47.3449190Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:25:47.3450315Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:25:47.3451367Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:25:47.3452445Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:25:47.3453305Z 2025-09-07T09:25:47.3453314Z 2025-09-07T09:25:47.6992273Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:25:47.6994233Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:25:47.6995088Z File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 188, in propagate 2025-09-07T09:25:47.6996661Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:25:47.6998256Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:25:47.6999694Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:25:47.7000982Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:25:47.7002281Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:25:47.7003551Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:25:47.7004876Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:25:47.7006226Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:25:47.7007484Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:25:47.7008725Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:25:47.7010021Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:25:47.7010550Z 2025-09-07T09:25:47.7010558Z 2025-09-07T09:25:47.9716212Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:25:47.9718150Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:25:47.9719026Z File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 188, in propagate 2025-09-07T09:25:47.9720047Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:25:47.9729124Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:25:47.9730580Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:25:47.9731902Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:25:47.9733648Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:25:47.9734984Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:25:47.9736345Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:25:47.9737679Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:25:47.9738909Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:25:47.9740166Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:25:47.9741479Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:25:47.9742013Z 2025-09-07T09:25:47.9742032Z 2025-09-07T09:25:49.0762456Z W0907 09:25:49.075000 14844 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T09:25:50.4013386Z pass 2025-09-07T09:25:53.4189314Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:25:53.4190740Z import pynvml # type: ignore[import] 2025-09-07T09:25:56.3349185Z 2025-09-07T09:25:58.7476278Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:25:58.7476906Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:25:58.7477535Z cuda train basic_gnn_gin 2025-09-07T09:26:02.7826015Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:26:02.7828411Z pred = mod(*cloned_inputs) 2025-09-07T09:26:02.7829559Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T09:26:02.7830761Z x = self.convs[i](x, edge_index) 2025-09-07T09:26:02.7831440Z File "/tmp/jenkins_pyg/tmp2mme5vo2.py", line 225, in forward 2025-09-07T09:26:02.7832193Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T09:26:02.7832997Z File "/tmp/jenkins_pyg/tmp2mme5vo2.py", line 182, in propagate 2025-09-07T09:26:02.7834021Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:26:02.7835651Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:26:02.7837148Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:26:02.7838485Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:26:02.7839832Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:26:02.7841114Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:26:02.7842418Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:26:02.7843690Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:26:02.7844884Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:26:02.7846100Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:26:02.7847784Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:26:02.7848304Z 2025-09-07T09:26:02.7848320Z 2025-09-07T09:26:03.5232793Z W0907 09:26:03.522000 14950 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:26:05.7644344Z pass 2025-09-07T09:26:08.8394436Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:26:08.8395860Z import pynvml # type: ignore[import] 2025-09-07T09:26:11.5480358Z 2025-09-07T09:26:13.9400384Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:26:13.9400784Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:26:13.9401166Z cuda train basic_gnn_sage 2025-09-07T09:26:17.8609662Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:26:17.8610937Z pred = mod(*cloned_inputs) 2025-09-07T09:26:17.8611584Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T09:26:17.8612254Z x = self.convs[i](x, edge_index) 2025-09-07T09:26:17.8612648Z File "/tmp/jenkins_pyg/tmpo1uwvbxh.py", line 228, in forward 2025-09-07T09:26:17.8613324Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T09:26:17.8613777Z File "/tmp/jenkins_pyg/tmpo1uwvbxh.py", line 182, in propagate 2025-09-07T09:26:17.8614360Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:26:17.8615260Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:26:17.8616471Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:26:17.8617200Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:26:17.8617922Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:26:17.8618636Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T09:26:17.8619360Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T09:26:17.8620076Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:26:17.8620720Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:26:17.8621372Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter 2025-09-07T09:26:17.8622077Z count.scatter_add_(0, index, src.new_ones(src.size(dim))) 2025-09-07T09:26:17.8622369Z 2025-09-07T09:26:17.8622374Z 2025-09-07T09:26:18.4289626Z W0907 09:26:18.428000 15036 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:26:20.3312399Z pass 2025-09-07T09:26:23.3007533Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:26:23.3009029Z import pynvml # type: ignore[import] 2025-09-07T09:26:26.0993477Z 2025-09-07T09:26:26.7659164Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:26:26.7659808Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:26:26.7660934Z cuda train dcgan 2025-09-07T09:26:33.2210663Z pass 2025-09-07T09:26:36.3182336Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:26:36.3183750Z import pynvml # type: ignore[import] 2025-09-07T09:26:39.0318244Z 2025-09-07T09:26:42.6092277Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:26:42.6092657Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:26:42.6093189Z cuda train demucs 2025-09-07T09:27:10.0853467Z pass 2025-09-07T09:27:13.4511829Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:27:13.4514497Z import pynvml # type: ignore[import] 2025-09-07T09:27:16.2119967Z 2025-09-07T09:27:18.7916677Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:27:18.7917091Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:27:18.7917424Z cuda train densenet121 2025-09-07T09:28:44.8577439Z pass 2025-09-07T09:28:49.6004460Z accuracy pass_rate=92.31% 2025-09-07T09:28:49.6012090Z calls_captured gmean=0.00x mean=225.615x 2025-09-07T09:28:49.6016980Z unique_graphs gmean=0.00x mean=3.538x 2025-09-07T09:28:49.6021299Z graph_breaks gmean=0.00x mean=7.692x 2025-09-07T09:28:49.6025816Z unique_graph_breaks gmean=0.00x mean=4.846x 2025-09-07T09:28:49.6030252Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:28:49.6034571Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:28:49.6038868Z cudagraph_skips gmean=0.00x mean=0.769x 2025-09-07T09:28:49.6040303Z compilation_latency mean=20.314 seconds 2025-09-07T09:28:50.5328260Z + [[ 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* ]] 2025-09-07T09:28:50.5330990Z + 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 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:28:51.1462375Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:28:51.1465161Z import pynvml # type: ignore[import] 2025-09-07T09:28:54.9601866Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:28:54.9605417Z import pynvml # type: ignore[import] 2025-09-07T09:28:57.6945353Z 2025-09-07T09:28:57.8907933Z loading model: 0it [00:00, ?it/s][rank0]:W0907 09:28:57.890000 15559 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T09:28:59.0916454Z 2025-09-07T09:28:59.0916827Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:28:59.0917453Z cuda train torchrec_dlrm 2025-09-07T09:29:13.8401554Z [rank0]:W0907 09:29:13.839000 15559 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:29:15.5237301Z pass 2025-09-07T09:29:17.5397603Z [rank0]:[W907 09:29:17.826054674 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T09:29:18.6935535Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:29:18.6936959Z import pynvml # type: ignore[import] 2025-09-07T09:29:21.4907087Z 2025-09-07T09:29:24.6307471Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:24.6307861Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:29:24.6308241Z cuda train BERT_pytorch 2025-09-07T09:29:36.6548373Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:29:36.6549637Z pred = mod(*cloned_inputs) 2025-09-07T09:29:36.6550261Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward 2025-09-07T09:29:36.6550916Z x = self.bert(x, segment_label) 2025-09-07T09:29:36.6551500Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward 2025-09-07T09:29:36.6552104Z x = self.embedding(x, segment_info) 2025-09-07T09:29:36.6552750Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward 2025-09-07T09:29:36.6553546Z x = self.token(sequence) + self.position(sequence) + self.segment(segment_label) 2025-09-07T09:29:36.6553932Z 2025-09-07T09:29:36.6553936Z 2025-09-07T09:29:37.8277091Z pass 2025-09-07T09:29:40.8097721Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:29:40.8099182Z import pynvml # type: ignore[import] 2025-09-07T09:29:43.6866716Z 2025-09-07T09:29:47.6924569Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:47.6924950Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:29:47.6925292Z cuda train Background_Matting 2025-09-07T09:29:47.7159699Z pass_due_to_skip 2025-09-07T09:29:49.6130327Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:29:49.6131862Z import pynvml # type: ignore[import] 2025-09-07T09:29:52.5260057Z 2025-09-07T09:29:56.2139671Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:56.2140112Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:29:56.2140455Z cuda train LearningToPaint 2025-09-07T09:30:06.6568682Z pass 2025-09-07T09:30:09.9793108Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:30:09.9794542Z import pynvml # type: ignore[import] 2025-09-07T09:30:12.6984800Z 2025-09-07T09:30:15.4420911Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:30:15.4421295Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:30:15.4421631Z cuda train Super_SloMo 2025-09-07T09:30:28.9313514Z W0907 09:30:28.930000 16222 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:30:31.5497156Z pass 2025-09-07T09:30:34.8679947Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:30:34.8681383Z import pynvml # type: ignore[import] 2025-09-07T09:30:37.6672942Z 2025-09-07T09:30:39.4970575Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:30:39.4970966Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:30:39.4971295Z cuda train alexnet 2025-09-07T09:30:48.0849317Z pass 2025-09-07T09:30:51.5841795Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:30:51.5843244Z import pynvml # type: ignore[import] 2025-09-07T09:30:54.2451115Z 2025-09-07T09:30:56.6813586Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:30:56.6814216Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:30:56.6814789Z cuda train basic_gnn_edgecnn 2025-09-07T09:31:00.6483323Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in torch_dynamo_resume_in_scatter_at_93 2025-09-07T09:31:00.6485681Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T09:31:00.6486109Z 2025-09-07T09:31:00.6486118Z 2025-09-07T09:31:02.8196035Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpu6zhaoid.py", line 190, in propagate 2025-09-07T09:31:02.8197790Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T09:31:02.8199044Z File "/tmp/jenkins_pyg/tmpu6zhaoid.py", line 141, in _collect 2025-09-07T09:31:02.8199799Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T09:31:02.8200478Z File "/tmp/jenkins_pyg/tmpu6zhaoid.py", line 88, in _lift 2025-09-07T09:31:02.8201243Z return src.index_select(self.node_dim, index) 2025-09-07T09:31:02.8201697Z 2025-09-07T09:31:02.8201706Z 2025-09-07T09:31:02.8651924Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpu6zhaoid.py", line 190, in propagate 2025-09-07T09:31:02.8653999Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T09:31:02.8654830Z File "/tmp/jenkins_pyg/tmpu6zhaoid.py", line 141, in _collect 2025-09-07T09:31:02.8655558Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T09:31:02.8656207Z File "/tmp/jenkins_pyg/tmpu6zhaoid.py", line 88, in _lift 2025-09-07T09:31:02.8656928Z return src.index_select(self.node_dim, index) 2025-09-07T09:31:02.8657381Z 2025-09-07T09:31:02.8657402Z 2025-09-07T09:31:02.8998838Z W0907 09:31:02.899000 16562 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T09:31:03.4564699Z pass 2025-09-07T09:31:06.3140041Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:06.3141459Z import pynvml # type: ignore[import] 2025-09-07T09:31:08.9851687Z 2025-09-07T09:31:11.5486214Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:11.5486838Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:31:11.5487370Z cuda train basic_gnn_gcn 2025-09-07T09:31:14.6357074Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T09:31:14.6359758Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T09:31:14.6361169Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:31:14.6362471Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:31:14.6363035Z 2025-09-07T09:31:14.6363044Z 2025-09-07T09:31:14.7482167Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp_ob_pmbn.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:31:14.7484199Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:31:14.7485147Z File "/tmp/jenkins_pyg/tmp_ob_pmbn.py", line 188, in propagate 2025-09-07T09:31:14.7486226Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:31:14.7487877Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:31:14.7489401Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:31:14.7490794Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:31:14.7492154Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:31:14.7493869Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:31:14.7495218Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:31:14.7496512Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:31:14.7497757Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:31:14.7499532Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:31:14.7500849Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:31:14.7501398Z 2025-09-07T09:31:14.7501406Z 2025-09-07T09:31:14.9183040Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:31:14.9185162Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:31:14.9186061Z File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 188, in propagate 2025-09-07T09:31:14.9187137Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:31:14.9188811Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:31:14.9190313Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:31:14.9191538Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:31:14.9192743Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:31:14.9193925Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:31:14.9195141Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:31:14.9196473Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:31:14.9197705Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:31:14.9198936Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:31:14.9200797Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:31:14.9201326Z 2025-09-07T09:31:14.9201334Z 2025-09-07T09:31:15.0858000Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:31:15.0860030Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:31:15.0860957Z File "/tmp/jenkins_pyg/tmp0zx0m1bm.py", line 188, in propagate 2025-09-07T09:31:15.0861992Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:31:15.0863516Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:31:15.0865069Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:31:15.0866452Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:31:15.0867767Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:31:15.0869071Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:31:15.0870395Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:31:15.0871612Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:31:15.0872841Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:31:15.0874111Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:31:15.0875454Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:31:15.0875998Z 2025-09-07T09:31:15.0876007Z 2025-09-07T09:31:15.2896940Z W0907 09:31:15.288000 16682 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T09:31:15.7182947Z pass 2025-09-07T09:31:19.1974304Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:19.1975755Z import pynvml # type: ignore[import] 2025-09-07T09:31:21.9454885Z 2025-09-07T09:31:24.3651010Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:24.3651390Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:31:24.3651715Z cuda train basic_gnn_gin 2025-09-07T09:31:27.3711460Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:31:27.3712779Z pred = mod(*cloned_inputs) 2025-09-07T09:31:27.3713441Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T09:31:27.3714112Z x = self.convs[i](x, edge_index) 2025-09-07T09:31:27.3714490Z File "/tmp/jenkins_pyg/tmp2mme5vo2.py", line 225, in forward 2025-09-07T09:31:27.3714933Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T09:31:27.3715381Z File "/tmp/jenkins_pyg/tmp2mme5vo2.py", line 182, in propagate 2025-09-07T09:31:27.3715972Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:31:27.3716847Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:31:27.3717634Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:31:27.3718801Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:31:27.3719522Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:31:27.3720253Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:31:27.3720973Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:31:27.3721670Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:31:27.3722328Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:31:27.3722987Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:31:27.3723683Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:31:27.3723969Z 2025-09-07T09:31:27.3723973Z 2025-09-07T09:31:27.7623472Z W0907 09:31:27.761000 16759 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:31:28.3044351Z pass 2025-09-07T09:31:32.5317962Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:32.5319401Z import pynvml # type: ignore[import] 2025-09-07T09:31:35.3529629Z 2025-09-07T09:31:37.8206003Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:37.8206400Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:31:37.8206715Z cuda train basic_gnn_sage 2025-09-07T09:31:40.7520418Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:31:40.7521752Z pred = mod(*cloned_inputs) 2025-09-07T09:31:40.7522847Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T09:31:40.7523531Z x = self.convs[i](x, edge_index) 2025-09-07T09:31:40.7523932Z File "/tmp/jenkins_pyg/tmpo1uwvbxh.py", line 228, in forward 2025-09-07T09:31:40.7524367Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T09:31:40.7524819Z File "/tmp/jenkins_pyg/tmpo1uwvbxh.py", line 182, in propagate 2025-09-07T09:31:40.7525407Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T09:31:40.7526286Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:31:40.7527070Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:31:40.7527815Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:31:40.7528528Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:31:40.7529242Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T09:31:40.7529958Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T09:31:40.7530658Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:31:40.7531346Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:31:40.7531994Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter 2025-09-07T09:31:40.7532696Z count.scatter_add_(0, index, src.new_ones(src.size(dim))) 2025-09-07T09:31:40.7533309Z 2025-09-07T09:31:40.7533314Z 2025-09-07T09:31:41.1137308Z W0907 09:31:41.113000 16836 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:31:41.6108065Z pass 2025-09-07T09:31:46.1148442Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:46.1149854Z import pynvml # type: ignore[import] 2025-09-07T09:31:49.0410692Z 2025-09-07T09:31:49.7803649Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:49.7804070Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:49.7804973Z cuda train dcgan 2025-09-07T09:31:58.2188558Z pass 2025-09-07T09:32:01.5741256Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:32:01.5743803Z import pynvml # type: ignore[import] 2025-09-07T09:32:04.3631620Z 2025-09-07T09:32:07.6939726Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:07.6940368Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:32:07.6940902Z cuda train demucs 2025-09-07T09:32:30.1890953Z pass 2025-09-07T09:32:33.1840674Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:32:33.1842104Z import pynvml # type: ignore[import] 2025-09-07T09:32:36.1627629Z 2025-09-07T09:32:38.7690987Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:32:38.7691347Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:32:38.7691739Z cuda train densenet121 2025-09-07T09:32:58.0842860Z pass 2025-09-07T09:33:00.7616924Z accuracy pass_rate=92.31% 2025-09-07T09:33:00.7627017Z calls_captured gmean=0.00x mean=225.769x 2025-09-07T09:33:00.7634722Z unique_graphs gmean=0.00x mean=3.538x 2025-09-07T09:33:00.7641260Z graph_breaks gmean=0.00x mean=7.692x 2025-09-07T09:33:00.7648294Z unique_graph_breaks gmean=0.00x mean=4.846x 2025-09-07T09:33:00.7655721Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:33:00.7662676Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:33:00.7669893Z cudagraph_skips gmean=0.00x mean=0.769x 2025-09-07T09:33:00.7672050Z compilation_latency mean=8.370 seconds 2025-09-07T09:33:01.8444562Z + [[ 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* ]] 2025-09-07T09:33:01.8446079Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T09:33:01.8447594Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:33:02.4560920Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:33:02.4562404Z import pynvml # type: ignore[import] 2025-09-07T09:33:06.3035414Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:33:06.3037438Z import pynvml # type: ignore[import] 2025-09-07T09:33:08.9928813Z 2025-09-07T09:33:09.1847851Z loading model: 0it [00:00, ?it/s][rank0]:W0907 09:33:09.184000 17438 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T09:33:10.3608116Z 2025-09-07T09:33:10.3608700Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:33:10.3609391Z cuda train torchrec_dlrm 2025-09-07T09:33:32.3991182Z [rank0]:W0907 09:33:32.397000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4006327Z [rank0]:W0907 09:33:32.400000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4019601Z [rank0]:W0907 09:33:32.401000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4032646Z [rank0]:W0907 09:33:32.402000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4045916Z [rank0]:W0907 09:33:32.404000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4059520Z [rank0]:W0907 09:33:32.405000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4072322Z [rank0]:W0907 09:33:32.406000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4085567Z [rank0]:W0907 09:33:32.408000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4098560Z [rank0]:W0907 09:33:32.409000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4112208Z [rank0]:W0907 09:33:32.410000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4125021Z [rank0]:W0907 09:33:32.412000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4138373Z [rank0]:W0907 09:33:32.413000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4151488Z [rank0]:W0907 09:33:32.414000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4165082Z [rank0]:W0907 09:33:32.416000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4178493Z [rank0]:W0907 09:33:32.417000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4191552Z [rank0]:W0907 09:33:32.418000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4204537Z [rank0]:W0907 09:33:32.420000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4218454Z [rank0]:W0907 09:33:32.421000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4231419Z [rank0]:W0907 09:33:32.422000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4244225Z [rank0]:W0907 09:33:32.424000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4257642Z [rank0]:W0907 09:33:32.425000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4271348Z [rank0]:W0907 09:33:32.426000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4284017Z [rank0]:W0907 09:33:32.428000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4297366Z [rank0]:W0907 09:33:32.429000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4311160Z [rank0]:W0907 09:33:32.430000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:32.4324674Z [rank0]:W0907 09:33:32.432000 17438 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T09:33:38.1084992Z [rank0]:W0907 09:33:38.107000 17438 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:33:49.0022106Z pass 2025-09-07T09:33:51.2235669Z [rank0]:[W907 09:33:51.509854941 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T09:33:52.6436163Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:33:52.6438900Z import pynvml # type: ignore[import] 2025-09-07T09:33:55.4771182Z 2025-09-07T09:33:58.0922554Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:33:58.0922945Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:33:58.0923282Z cuda train BERT_pytorch 2025-09-07T09:35:09.0094283Z pass 2025-09-07T09:35:13.0826410Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:13.0827838Z import pynvml # type: ignore[import] 2025-09-07T09:35:15.9398841Z 2025-09-07T09:35:19.9145697Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:19.9146100Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:35:19.9150289Z cuda train Background_Matting 2025-09-07T09:35:19.9378048Z pass_due_to_skip 2025-09-07T09:35:21.6881339Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:21.6882760Z import pynvml # type: ignore[import] 2025-09-07T09:35:24.4154834Z 2025-09-07T09:35:27.8915443Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:27.8915843Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:35:27.8916181Z cuda train LearningToPaint 2025-09-07T09:35:55.6572661Z pass 2025-09-07T09:35:59.3226973Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:59.3228422Z import pynvml # type: ignore[import] 2025-09-07T09:36:02.1749671Z 2025-09-07T09:36:04.9413889Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:36:04.9414328Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:36:04.9414655Z cuda train Super_SloMo 2025-09-07T09:37:19.9853142Z W0907 09:37:19.984000 19118 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:37:40.8057270Z pass 2025-09-07T09:37:45.8995115Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:37:45.8996526Z import pynvml # type: ignore[import] 2025-09-07T09:37:48.7580388Z 2025-09-07T09:37:50.6247309Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:37:50.6247714Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:37:50.6248041Z cuda train alexnet 2025-09-07T09:38:13.2369741Z pass 2025-09-07T09:38:16.3211706Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:38:16.3213402Z import pynvml # type: ignore[import] 2025-09-07T09:38:19.2139831Z 2025-09-07T09:38:21.6807236Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:21.6807611Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:38:21.6807941Z cuda train basic_gnn_edgecnn 2025-09-07T09:38:39.3787072Z W0907 09:38:39.377000 19933 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T09:38:43.2272077Z pass 2025-09-07T09:38:46.4331719Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:38:46.4333426Z import pynvml # type: ignore[import] 2025-09-07T09:38:49.2471135Z 2025-09-07T09:38:51.8490390Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:51.8490780Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:38:51.8491094Z cuda train basic_gnn_gcn 2025-09-07T09:39:09.5919724Z W0907 09:39:09.591000 20329 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T09:39:12.3725195Z pass 2025-09-07T09:39:15.4716290Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:39:15.4726739Z import pynvml # type: ignore[import] 2025-09-07T09:39:18.3245105Z 2025-09-07T09:39:20.7266828Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:20.7267376Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:39:20.7267835Z cuda train basic_gnn_gin 2025-09-07T09:39:33.0839993Z W0907 09:39:33.083000 20745 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:39:36.6261056Z pass 2025-09-07T09:39:39.7443515Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:39:39.7444976Z import pynvml # type: ignore[import] 2025-09-07T09:39:42.8014469Z 2025-09-07T09:39:45.2711111Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:45.2711504Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:39:45.2711855Z cuda train basic_gnn_sage 2025-09-07T09:39:58.5220711Z W0907 09:39:58.521000 21029 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:40:02.0305790Z pass 2025-09-07T09:40:05.1358086Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:40:05.1360691Z import pynvml # type: ignore[import] 2025-09-07T09:40:07.9534249Z 2025-09-07T09:40:08.6730494Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:40:08.6730922Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:40:08.6731246Z cuda train dcgan 2025-09-07T09:40:25.0859626Z pass 2025-09-07T09:40:28.0999196Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:40:28.1000658Z import pynvml # type: ignore[import] 2025-09-07T09:40:31.1112751Z 2025-09-07T09:40:34.8248294Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:41:15.2126429Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:41:15.2126837Z cuda train demucs 2025-09-07T09:41:15.2127161Z pass 2025-09-07T09:41:18.7811047Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:41:18.7812449Z import pynvml # type: ignore[import] 2025-09-07T09:41:21.8286090Z 2025-09-07T09:41:24.5868323Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:41:24.5868730Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:41:24.5869048Z cuda train densenet121 2025-09-07T09:44:43.0739386Z pass 2025-09-07T09:44:48.6576850Z accuracy pass_rate=92.31% 2025-09-07T09:44:48.6582975Z calls_captured gmean=0.00x mean=225.615x 2025-09-07T09:44:48.6587566Z unique_graphs gmean=0.00x mean=3.538x 2025-09-07T09:44:48.6591806Z graph_breaks gmean=0.00x mean=7.692x 2025-09-07T09:44:48.6596733Z unique_graph_breaks gmean=0.00x mean=4.846x 2025-09-07T09:44:48.6600959Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:44:48.6605110Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:44:48.6609244Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:44:48.6616316Z compilation_latency mean=43.267 seconds 2025-09-07T09:44:49.7556468Z + [[ 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* ]] 2025-09-07T09:44:49.7559367Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:44:49.7562268Z + [[ 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* ]] 2025-09-07T09:44:49.7565221Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:44:49.7567984Z + [[ 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* ]] 2025-09-07T09:44:49.7570804Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:44:49.7573995Z + [[ 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* ]] 2025-09-07T09:44:49.7576819Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T09:44:49.7579572Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.csv 2025-09-07T09:44:50.3427180Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:44:50.3430456Z import pynvml # type: ignore[import] 2025-09-07T09:44:54.2508521Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:44:54.2511243Z import pynvml # type: ignore[import] 2025-09-07T09:44:57.0219339Z 2025-09-07T09:44:57.2165016Z loading model: 0it [00:00, ?it/s][rank0]:W0907 09:44:57.215000 23036 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T09:44:58.2422416Z 2025-09-07T09:44:58.2423129Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:44:58.2423534Z cuda train torchrec_dlrm 2025-09-07T09:45:08.2836715Z Autotune Choices Stats: 2025-09-07T09:45:08.2838258Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_63", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:45:08.2845984Z AUTOTUNE mm(4x512, 512x1728) 2025-09-07T09:45:08.2846647Z strides: [512, 1], [1, 512] 2025-09-07T09:45:08.2847265Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:08.2848564Z triton_mm_63 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 2025-09-07T09:45:08.2849920Z triton_mm_67 0.0102 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 2025-09-07T09:45:08.2854890Z mm 0.0113 ms 90.9% 2025-09-07T09:45:08.2856696Z triton_mm_60 0.0113 ms 90.9% 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 2025-09-07T09:45:08.2858927Z triton_mm_61 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:08.2860985Z triton_mm_62 0.0113 ms 90.9% 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 2025-09-07T09:45:08.2863116Z triton_mm_66 0.0113 ms 90.9% 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 2025-09-07T09:45:08.2865406Z triton_mm_70 0.0113 ms 90.9% 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 2025-09-07T09:45:08.2867598Z triton_mm_71 0.0113 ms 90.9% 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 2025-09-07T09:45:08.2869759Z triton_mm_73 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:45:08.2871636Z SingleProcess AUTOTUNE benchmarking takes 0.2594 seconds and 0.0006 seconds precompiling for 18 choices 2025-09-07T09:45:09.2602446Z Autotune Choices Stats: 2025-09-07T09:45:09.2604589Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_0", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:45:09.2609422Z AUTOTUNE mm(4x13, 13x512) 2025-09-07T09:45:09.2609927Z strides: [13, 1], [1, 13] 2025-09-07T09:45:09.2610395Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:09.2612192Z triton_mm_0 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:45:09.2614760Z triton_mm_1 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:45:09.2616931Z triton_mm_2 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:09.2619069Z triton_mm_3 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:45:09.2621229Z triton_mm_4 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:45:09.2623401Z triton_mm_5 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:09.2625620Z triton_mm_6 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:09.2627781Z triton_mm_7 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:45:09.2629946Z triton_mm_8 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:45:09.2632452Z triton_mm_9 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:45:09.2634351Z SingleProcess AUTOTUNE benchmarking takes 0.1764 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:45:09.8302087Z Autotune Choices Stats: 2025-09-07T09:45:09.8303326Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_148", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:45:09.8310594Z AUTOTUNE mm(4x1728, 1728x512) 2025-09-07T09:45:09.8310928Z strides: [1728, 1], [1, 1728] 2025-09-07T09:45:09.8311235Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:09.8312031Z triton_mm_148 0.0123 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 2025-09-07T09:45:09.8313304Z triton_mm_152 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 2025-09-07T09:45:09.8314060Z mm 0.0154 ms 80.0% 2025-09-07T09:45:09.8314736Z triton_mm_160 0.0164 ms 75.0% 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 2025-09-07T09:45:09.8315913Z triton_mm_147 0.0174 ms 70.6% 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 2025-09-07T09:45:09.8317083Z triton_mm_146 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:09.8318254Z triton_mm_151 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:09.8319753Z triton_mm_156 0.0184 ms 66.7% 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 2025-09-07T09:45:09.8320959Z triton_mm_145 0.0205 ms 60.0% 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=2, num_warps=2 2025-09-07T09:45:09.8322152Z triton_mm_155 0.0205 ms 60.0% 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 2025-09-07T09:45:09.8323167Z SingleProcess AUTOTUNE benchmarking takes 0.2669 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:45:10.0959371Z Autotune Choices Stats: 2025-09-07T09:45:10.0960600Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_165", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:45:10.0967982Z AUTOTUNE mm(4x512, 512x512) 2025-09-07T09:45:10.0968270Z strides: [512, 1], [1, 512] 2025-09-07T09:45:10.0968605Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:10.0969370Z triton_mm_165 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 2025-09-07T09:45:10.0970567Z triton_mm_169 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:10.0971313Z mm 0.0102 ms 80.0% 2025-09-07T09:45:10.0972006Z triton_mm_162 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0973706Z triton_mm_163 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0974857Z triton_mm_164 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0976026Z triton_mm_168 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0977197Z triton_mm_173 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0978375Z triton_mm_175 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0979547Z triton_mm_177 0.0102 ms 80.0% 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 2025-09-07T09:45:10.0980572Z SingleProcess AUTOTUNE benchmarking takes 0.2409 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:45:10.3575361Z Autotune Choices Stats: 2025-09-07T09:45:10.3576595Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_16", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:45:10.3584132Z AUTOTUNE mm(4x512, 512x256) 2025-09-07T09:45:10.3584422Z strides: [512, 1], [1, 512] 2025-09-07T09:45:10.3584749Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:10.3585935Z triton_mm_16 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 2025-09-07T09:45:10.3587110Z triton_mm_14 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=5, num_warps=4 2025-09-07T09:45:10.3588270Z triton_mm_15 0.0092 ms 88.9% 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 2025-09-07T09:45:10.3589434Z triton_mm_20 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:10.3590172Z mm 0.0102 ms 80.0% 2025-09-07T09:45:10.3590857Z triton_mm_13 0.0102 ms 80.0% 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 2025-09-07T09:45:10.3592035Z triton_mm_19 0.0102 ms 80.0% 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 2025-09-07T09:45:10.3593192Z triton_mm_23 0.0102 ms 80.0% 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 2025-09-07T09:45:10.3594368Z triton_mm_24 0.0102 ms 80.0% 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 2025-09-07T09:45:10.3595541Z triton_mm_26 0.0102 ms 80.0% 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 2025-09-07T09:45:10.3596739Z SingleProcess AUTOTUNE benchmarking takes 0.2380 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:45:10.8596120Z Autotune Choices Stats: 2025-09-07T09:45:10.8597368Z {"num_choices": 14, "num_triton_choices": 13, "best_kernel": "triton_mm_41", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:45:10.8604966Z AUTOTUNE mm(4x256, 256x64) 2025-09-07T09:45:10.8605247Z strides: [256, 1], [1, 256] 2025-09-07T09:45:10.8605528Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:10.8606289Z triton_mm_41 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=5, num_warps=4 2025-09-07T09:45:10.8607476Z triton_mm_30 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 2025-09-07T09:45:10.8608666Z triton_mm_31 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 2025-09-07T09:45:10.8609821Z triton_mm_32 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 2025-09-07T09:45:10.8610981Z triton_mm_33 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 2025-09-07T09:45:10.8612142Z triton_mm_36 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 2025-09-07T09:45:10.8613543Z triton_mm_37 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 2025-09-07T09:45:10.8615055Z triton_mm_39 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 2025-09-07T09:45:10.8616231Z triton_mm_40 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=4, num_warps=4 2025-09-07T09:45:10.8617399Z triton_mm_38 0.0092 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:10.8618421Z SingleProcess AUTOTUNE benchmarking takes 0.1848 seconds and 0.0002 seconds precompiling for 14 choices 2025-09-07T09:45:11.2635622Z Autotune Choices Stats: 2025-09-07T09:45:11.2636852Z {"num_choices": 12, "num_triton_choices": 11, "best_kernel": "triton_mm_197", "best_kernel_desc": "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", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:45:11.2645368Z AUTOTUNE addmm(4x1, 4x256, 256x1) 2025-09-07T09:45:11.2645741Z strides: [1, 1], [256, 1], [1, 0] 2025-09-07T09:45:11.2646090Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:45:11.2646922Z triton_mm_197 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 2025-09-07T09:45:11.2648128Z triton_mm_198 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 2025-09-07T09:45:11.2649320Z triton_mm_201 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 2025-09-07T09:45:11.2650870Z triton_mm_204 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 2025-09-07T09:45:11.2652054Z triton_mm_205 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 2025-09-07T09:45:11.2653508Z triton_mm_196 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T09:45:11.2654689Z triton_mm_202 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 2025-09-07T09:45:11.2655863Z triton_mm_203 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T09:45:11.2657100Z triton_mm_200 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 2025-09-07T09:45:11.2658278Z triton_mm_195 0.0113 ms 63.6% 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 2025-09-07T09:45:11.2659301Z SingleProcess AUTOTUNE benchmarking takes 0.1607 seconds and 0.0002 seconds precompiling for 12 choices 2025-09-07T09:45:17.6454194Z Autotune Choices Stats: 2025-09-07T09:45:17.6455733Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_318", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:45:17.6465175Z AUTOTUNE mm(512x4, 4x1728) 2025-09-07T09:45:17.6466028Z strides: [1, 512], [1728, 1] 2025-09-07T09:45:17.6469186Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:17.6470803Z triton_mm_318 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 2025-09-07T09:45:17.6472333Z triton_mm_319 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 2025-09-07T09:45:17.6473817Z triton_mm_313 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 2025-09-07T09:45:17.6475296Z triton_mm_314 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 2025-09-07T09:45:17.6476796Z triton_mm_315 0.0082 ms 87.5% 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 2025-09-07T09:45:17.6478135Z triton_mm_316 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 2025-09-07T09:45:17.6479459Z triton_mm_317 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 2025-09-07T09:45:17.6480795Z triton_mm_320 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 2025-09-07T09:45:17.6482141Z triton_mm_321 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 2025-09-07T09:45:17.6483755Z triton_mm_322 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 2025-09-07T09:45:17.6487266Z SingleProcess AUTOTUNE benchmarking takes 0.2382 seconds and 0.0008 seconds precompiling for 17 choices 2025-09-07T09:45:18.1167743Z Autotune Choices Stats: 2025-09-07T09:45:18.1168955Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_331", "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} 2025-09-07T09:45:18.1178347Z AUTOTUNE mm(1728x4, 4x512) 2025-09-07T09:45:18.1178653Z strides: [1, 1728], [512, 1] 2025-09-07T09:45:18.1178976Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:18.1179749Z triton_mm_331 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 2025-09-07T09:45:18.1180989Z triton_mm_334 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 2025-09-07T09:45:18.1182181Z triton_mm_335 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 2025-09-07T09:45:18.1183366Z triton_mm_336 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 2025-09-07T09:45:18.1184562Z triton_mm_337 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 2025-09-07T09:45:18.1185818Z triton_mm_329 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 2025-09-07T09:45:18.1187310Z triton_mm_330 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 2025-09-07T09:45:18.1188495Z triton_mm_332 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 2025-09-07T09:45:18.1189670Z triton_mm_333 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 2025-09-07T09:45:18.1190912Z triton_mm_338 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 2025-09-07T09:45:18.1191946Z SingleProcess AUTOTUNE benchmarking takes 0.2163 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:45:18.4290005Z Autotune Choices Stats: 2025-09-07T09:45:18.4291263Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_280", "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} 2025-09-07T09:45:18.4300896Z AUTOTUNE mm(512x4, 4x512) 2025-09-07T09:45:18.4301196Z strides: [1, 512], [512, 1] 2025-09-07T09:45:18.4301476Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:18.4302256Z triton_mm_280 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 2025-09-07T09:45:18.4303454Z triton_mm_283 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 2025-09-07T09:45:18.4305131Z triton_mm_284 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 2025-09-07T09:45:18.4306320Z triton_mm_285 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 2025-09-07T09:45:18.4307519Z triton_mm_292 0.0072 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 2025-09-07T09:45:18.4308692Z triton_mm_281 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 2025-09-07T09:45:18.4309864Z triton_mm_282 0.0082 ms 87.5% 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 2025-09-07T09:45:18.4311047Z triton_mm_286 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 2025-09-07T09:45:18.4312219Z triton_mm_287 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 2025-09-07T09:45:18.4313397Z triton_mm_288 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 2025-09-07T09:45:18.4314455Z SingleProcess AUTOTUNE benchmarking takes 0.2062 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:45:18.8486906Z Autotune Choices Stats: 2025-09-07T09:45:18.8488476Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_247", "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} 2025-09-07T09:45:18.8498050Z AUTOTUNE mm(256x4, 4x512) 2025-09-07T09:45:18.8498369Z strides: [1, 256], [512, 1] 2025-09-07T09:45:18.8498668Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:18.8499443Z triton_mm_247 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 2025-09-07T09:45:18.8500651Z triton_mm_248 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 2025-09-07T09:45:18.8501831Z triton_mm_249 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 2025-09-07T09:45:18.8503027Z triton_mm_250 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 2025-09-07T09:45:18.8504210Z triton_mm_251 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 2025-09-07T09:45:18.8505525Z triton_mm_252 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 2025-09-07T09:45:18.8506721Z triton_mm_253 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 2025-09-07T09:45:18.8507913Z triton_mm_254 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 2025-09-07T09:45:18.8509320Z triton_mm_255 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 2025-09-07T09:45:18.8510512Z triton_mm_256 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 2025-09-07T09:45:18.8511552Z SingleProcess AUTOTUNE benchmarking takes 0.2041 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:45:19.2657642Z Autotune Choices Stats: 2025-09-07T09:45:19.2659166Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "mm", "best_time": 0.0071680000983178616, "best_triton_pos": 1, "best_triton_time": 0.0071680000983178616, "best_triton_kernel": "triton_mm_544", "best_triton_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"} 2025-09-07T09:45:19.2669184Z AUTOTUNE mm(64x4, 4x256) 2025-09-07T09:45:19.2669516Z strides: [1, 64], [256, 1] 2025-09-07T09:45:19.2669836Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:19.2670146Z mm 0.0072 ms 100.0% 2025-09-07T09:45:19.2670855Z triton_mm_544 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 2025-09-07T09:45:19.2672065Z triton_mm_545 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 2025-09-07T09:45:19.2673262Z triton_mm_546 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 2025-09-07T09:45:19.2674450Z triton_mm_547 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 2025-09-07T09:45:19.2675973Z triton_mm_548 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 2025-09-07T09:45:19.2677172Z triton_mm_549 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 2025-09-07T09:45:19.2678350Z triton_mm_550 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 2025-09-07T09:45:19.2679541Z triton_mm_551 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 2025-09-07T09:45:19.2680736Z triton_mm_552 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 2025-09-07T09:45:19.2681785Z SingleProcess AUTOTUNE benchmarking takes 0.1927 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T09:45:19.6997541Z Autotune Choices Stats: 2025-09-07T09:45:19.6998729Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_382", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:45:19.7009134Z AUTOTUNE mm(4x512, 512x1728) 2025-09-07T09:45:19.7009449Z strides: [512, 1], [1728, 1] 2025-09-07T09:45:19.7009735Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:19.7010503Z triton_mm_382 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 2025-09-07T09:45:19.7012010Z triton_mm_386 0.0102 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 2025-09-07T09:45:19.7013450Z triton_mm_394 0.0102 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 2025-09-07T09:45:19.7014200Z mm 0.0113 ms 90.9% 2025-09-07T09:45:19.7014890Z triton_mm_379 0.0113 ms 90.9% 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 2025-09-07T09:45:19.7016054Z triton_mm_380 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:19.7017220Z triton_mm_381 0.0113 ms 90.9% 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 2025-09-07T09:45:19.7018393Z triton_mm_385 0.0113 ms 90.9% 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 2025-09-07T09:45:19.7019558Z triton_mm_389 0.0113 ms 90.9% 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 2025-09-07T09:45:19.7020739Z triton_mm_390 0.0113 ms 90.9% 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 2025-09-07T09:45:19.7021833Z SingleProcess AUTOTUNE benchmarking takes 0.2253 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:45:21.0813431Z Autotune Choices Stats: 2025-09-07T09:45:21.0815397Z {"num_choices": 12, "num_triton_choices": 11, "best_kernel": "mm", "best_time": 0.0071680000983178616, "best_triton_pos": 1, "best_triton_time": 0.0071680000983178616, "best_triton_kernel": "triton_mm_592", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2"} 2025-09-07T09:45:21.0826606Z AUTOTUNE mm(512x4, 4x13) 2025-09-07T09:45:21.0826903Z strides: [1, 512], [13, 1] 2025-09-07T09:45:21.0827183Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:21.0827493Z mm 0.0072 ms 100.0% 2025-09-07T09:45:21.0828202Z triton_mm_592 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:45:21.0829395Z triton_mm_593 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:45:21.0830597Z triton_mm_594 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:45:21.0831775Z triton_mm_595 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:21.0832955Z triton_mm_596 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:45:21.0834141Z triton_mm_597 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:21.0835321Z triton_mm_598 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:45:21.0836748Z triton_mm_599 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:21.0837957Z triton_mm_600 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:45:21.0839003Z SingleProcess AUTOTUNE benchmarking takes 0.1477 seconds and 0.0002 seconds precompiling for 12 choices 2025-09-07T09:45:21.5139314Z Autotune Choices Stats: 2025-09-07T09:45:21.5140559Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_231", "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} 2025-09-07T09:45:21.5152451Z AUTOTUNE mm(4x256, 256x512) 2025-09-07T09:45:21.5152804Z strides: [256, 1], [512, 1] 2025-09-07T09:45:21.5153095Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:21.5153861Z triton_mm_231 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 2025-09-07T09:45:21.5155065Z triton_mm_232 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 2025-09-07T09:45:21.5156237Z triton_mm_233 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 2025-09-07T09:45:21.5157416Z triton_mm_234 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 2025-09-07T09:45:21.5158589Z triton_mm_237 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 2025-09-07T09:45:21.5160102Z triton_mm_238 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 2025-09-07T09:45:21.5161293Z triton_mm_244 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 2025-09-07T09:45:21.5162458Z triton_mm_240 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 2025-09-07T09:45:21.5163633Z triton_mm_241 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 2025-09-07T09:45:21.5164817Z triton_mm_242 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 2025-09-07T09:45:21.5165856Z SingleProcess AUTOTUNE benchmarking takes 0.2229 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:45:21.9821685Z Autotune Choices Stats: 2025-09-07T09:45:21.9822919Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_267", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:45:21.9835189Z AUTOTUNE mm(4x512, 512x512) 2025-09-07T09:45:21.9835499Z strides: [512, 1], [512, 1] 2025-09-07T09:45:21.9835780Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:21.9836556Z triton_mm_267 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 2025-09-07T09:45:21.9842321Z triton_mm_266 0.0092 ms 88.9% 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 2025-09-07T09:45:21.9843500Z triton_mm_271 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:21.9844240Z mm 0.0102 ms 80.0% 2025-09-07T09:45:21.9844924Z triton_mm_264 0.0102 ms 80.0% 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 2025-09-07T09:45:21.9846081Z triton_mm_265 0.0102 ms 80.0% 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 2025-09-07T09:45:21.9847247Z triton_mm_270 0.0102 ms 80.0% 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 2025-09-07T09:45:21.9848429Z triton_mm_275 0.0102 ms 80.0% 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 2025-09-07T09:45:21.9849602Z triton_mm_279 0.0102 ms 80.0% 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 2025-09-07T09:45:21.9850778Z triton_mm_273 0.0113 ms 72.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:45:21.9851798Z SingleProcess AUTOTUNE benchmarking takes 0.2279 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:45:22.1731935Z Autotune Choices Stats: 2025-09-07T09:45:22.1734064Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "mm", "best_time": 0.006144000217318535, "best_triton_pos": 1, "best_triton_time": 0.006144000217318535, "best_triton_kernel": "triton_mm_206", "best_triton_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"} 2025-09-07T09:45:22.1746087Z AUTOTUNE mm(4x1, 1x256) 2025-09-07T09:45:22.1746436Z strides: [1, 1], [256, 1] 2025-09-07T09:45:22.1746732Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:22.1747027Z mm 0.0061 ms 100.0% 2025-09-07T09:45:22.1747732Z triton_mm_206 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 2025-09-07T09:45:22.1748938Z triton_mm_207 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 2025-09-07T09:45:22.1750137Z triton_mm_208 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 2025-09-07T09:45:22.1751321Z triton_mm_209 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 2025-09-07T09:45:22.1752504Z triton_mm_210 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 2025-09-07T09:45:22.1753671Z triton_mm_211 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 2025-09-07T09:45:22.1754862Z triton_mm_212 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 2025-09-07T09:45:22.1756270Z triton_mm_213 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 2025-09-07T09:45:22.1757464Z triton_mm_214 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 2025-09-07T09:45:22.1758501Z SingleProcess AUTOTUNE benchmarking takes 0.1566 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:45:22.6276881Z Autotune Choices Stats: 2025-09-07T09:45:22.6278066Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_528", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:45:22.6293587Z AUTOTUNE mm(4x64, 64x256) 2025-09-07T09:45:22.6293917Z strides: [64, 1], [256, 1] 2025-09-07T09:45:22.6294207Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:22.6294972Z triton_mm_528 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=2, num_warps=2 2025-09-07T09:45:22.6296160Z triton_mm_529 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 2025-09-07T09:45:22.6297339Z triton_mm_530 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 2025-09-07T09:45:22.6298513Z triton_mm_531 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 2025-09-07T09:45:22.6299680Z triton_mm_534 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 2025-09-07T09:45:22.6301130Z triton_mm_535 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=5, num_warps=4 2025-09-07T09:45:22.6302333Z triton_mm_536 0.0072 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 2025-09-07T09:45:22.6303510Z triton_mm_537 0.0072 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 2025-09-07T09:45:22.6304700Z triton_mm_538 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 2025-09-07T09:45:22.6305975Z triton_mm_539 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=4, num_warps=4 2025-09-07T09:45:22.6307015Z SingleProcess AUTOTUNE benchmarking takes 0.2164 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:45:22.8095422Z Autotune Choices Stats: 2025-09-07T09:45:22.8096644Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_218", "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} 2025-09-07T09:45:22.8111142Z AUTOTUNE mm(1x4, 4x256) 2025-09-07T09:45:22.8111447Z strides: [1, 1], [256, 1] 2025-09-07T09:45:22.8111758Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:22.8112525Z triton_mm_218 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 2025-09-07T09:45:22.8114087Z triton_mm_219 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 2025-09-07T09:45:22.8115290Z triton_mm_220 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 2025-09-07T09:45:22.8116466Z triton_mm_221 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 2025-09-07T09:45:22.8117652Z triton_mm_223 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 2025-09-07T09:45:22.8118837Z triton_mm_222 0.0072 ms 85.7% 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 2025-09-07T09:45:22.8120031Z triton_mm_224 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:22.8121217Z triton_mm_225 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:45:22.8122400Z triton_mm_226 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:45:22.8123575Z triton_mm_227 0.0072 ms 85.7% 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 2025-09-07T09:45:22.8124589Z SingleProcess AUTOTUNE benchmarking takes 0.1565 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:45:23.4711955Z Autotune Choices Stats: 2025-09-07T09:45:23.4713571Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_353", "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} 2025-09-07T09:45:23.4726943Z AUTOTUNE mm(4x1728, 1728x512) 2025-09-07T09:45:23.4727260Z strides: [1728, 1], [512, 1] 2025-09-07T09:45:23.4727546Z dtypes: torch.float16, torch.float16 2025-09-07T09:45:23.4728317Z triton_mm_353 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 2025-09-07T09:45:23.4729521Z triton_mm_349 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 2025-09-07T09:45:23.4730285Z mm 0.0154 ms 80.0% 2025-09-07T09:45:23.4730987Z triton_mm_357 0.0154 ms 80.0% 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 2025-09-07T09:45:23.4732158Z triton_mm_348 0.0174 ms 70.6% 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 2025-09-07T09:45:23.4733582Z triton_mm_361 0.0174 ms 70.6% 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 2025-09-07T09:45:23.4734762Z triton_mm_347 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:45:23.4735938Z triton_mm_352 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:45:23.4737325Z triton_mm_346 0.0205 ms 60.0% 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=2, num_warps=2 2025-09-07T09:45:23.4738504Z triton_mm_359 0.0215 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:45:23.4739523Z SingleProcess AUTOTUNE benchmarking takes 0.2519 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:45:26.0901892Z [rank0]:W0907 09:45:26.089000 23036 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:45:32.7878654Z pass 2025-09-07T09:45:35.2289430Z [rank0]:[W907 09:45:35.515267381 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T09:45:36.5265210Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:45:36.5266647Z import pynvml # type: ignore[import] 2025-09-07T09:45:39.2870433Z 2025-09-07T09:45:41.8276419Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:45:41.8276820Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:45:41.8277137Z cuda train BERT_pytorch 2025-09-07T09:46:07.3661787Z Autotune Choices Stats: 2025-09-07T09:46:07.3663769Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_mm_120", "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"} 2025-09-07T09:46:07.3678331Z AUTOTUNE addmm(512x3072, 512x768, 768x3072) 2025-09-07T09:46:07.3678706Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T09:46:07.3679048Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:46:07.3679429Z bias_addmm 0.0225 ms 100.0% 2025-09-07T09:46:07.3680163Z triton_mm_120 0.0225 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 2025-09-07T09:46:07.3681365Z triton_mm_126 0.0225 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 2025-09-07T09:46:07.3682559Z triton_mm_118 0.0246 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 2025-09-07T09:46:07.3683749Z triton_mm_121 0.0246 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 2025-09-07T09:46:07.3684918Z triton_mm_125 0.0246 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 2025-09-07T09:46:07.3686096Z triton_mm_119 0.0256 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:07.3687267Z triton_mm_122 0.0256 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:07.3688710Z triton_mm_124 0.0266 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 2025-09-07T09:46:07.3689891Z triton_mm_116 0.0297 ms 75.9% 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 2025-09-07T09:46:07.3690908Z SingleProcess AUTOTUNE benchmarking takes 0.3296 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T09:46:08.2395782Z Autotune Choices Stats: 2025-09-07T09:46:08.2397021Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1730", "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": 0.025599999353289604, "best_triton_pos": 0} 2025-09-07T09:46:08.2413201Z AUTOTUNE mm(512x3072, 3072x768) 2025-09-07T09:46:08.2413552Z strides: [3072, 1], [1, 3072] 2025-09-07T09:46:08.2413850Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:08.2414625Z triton_mm_1730 0.0256 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 2025-09-07T09:46:08.2415394Z mm 0.0287 ms 89.3% 2025-09-07T09:46:08.2416087Z triton_mm_1729 0.0369 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 2025-09-07T09:46:08.2417273Z triton_mm_1733 0.0399 ms 64.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:08.2418465Z triton_mm_1723 0.0451 ms 56.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:08.2419641Z triton_mm_1725 0.0451 ms 56.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:08.2421177Z triton_mm_1726 0.0451 ms 56.8% 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 2025-09-07T09:46:08.2422372Z triton_mm_1732 0.0451 ms 56.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:08.2423560Z triton_mm_1724 0.0461 ms 55.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:08.2424751Z triton_mm_1735 0.0461 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 2025-09-07T09:46:08.2425892Z SingleProcess AUTOTUNE benchmarking takes 0.3471 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:46:09.6054202Z Autotune Choices Stats: 2025-09-07T09:46:09.6055448Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_8", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T09:46:09.6072191Z AUTOTUNE mm(512x768, 768x768) 2025-09-07T09:46:09.6072502Z strides: [768, 1], [1, 768] 2025-09-07T09:46:09.6072795Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:09.6073556Z triton_mm_8 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 2025-09-07T09:46:09.6074308Z mm 0.0143 ms 92.9% 2025-09-07T09:46:09.6074991Z triton_mm_7 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 2025-09-07T09:46:09.6076515Z triton_mm_11 0.0154 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:09.6077695Z triton_mm_4 0.0164 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:46:09.6078863Z triton_mm_10 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=4, num_warps=8 2025-09-07T09:46:09.6080031Z triton_mm_13 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=4, num_warps=8 2025-09-07T09:46:09.6081201Z triton_mm_1 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:09.6082360Z triton_mm_2 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:09.6083516Z triton_mm_3 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:09.6084513Z SingleProcess AUTOTUNE benchmarking takes 0.2596 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:46:09.8608789Z Autotune Choices Stats: 2025-09-07T09:46:09.8610002Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_55", "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} 2025-09-07T09:46:09.8627911Z AUTOTUNE bmm(48x128x64, 48x64x128) 2025-09-07T09:46:09.8628253Z strides: [8192, 64, 1], [8192, 128, 1] 2025-09-07T09:46:09.8628932Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:09.8629710Z triton_bmm_55 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 2025-09-07T09:46:09.8630908Z triton_bmm_58 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 2025-09-07T09:46:09.8632097Z triton_bmm_60 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 2025-09-07T09:46:09.8633289Z triton_bmm_61 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 2025-09-07T09:46:09.8634483Z triton_bmm_62 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 2025-09-07T09:46:09.8635665Z triton_bmm_63 0.0102 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 2025-09-07T09:46:09.8636839Z triton_bmm_64 0.0102 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 2025-09-07T09:46:09.8638031Z triton_bmm_65 0.0102 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 2025-09-07T09:46:09.8639227Z triton_bmm_66 0.0102 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 2025-09-07T09:46:09.8640626Z triton_bmm_67 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 2025-09-07T09:46:09.8641710Z SingleProcess AUTOTUNE benchmarking takes 0.2537 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:46:10.1010659Z Autotune Choices Stats: 2025-09-07T09:46:10.1011823Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_81", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:46:10.1030262Z AUTOTUNE bmm(48x128x128, 48x128x64) 2025-09-07T09:46:10.1030591Z strides: [16384, 128, 1], [8192, 64, 1] 2025-09-07T09:46:10.1030942Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:10.1031705Z triton_bmm_81 0.0102 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 2025-09-07T09:46:10.1032903Z triton_bmm_82 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 2025-09-07T09:46:10.1034087Z triton_bmm_83 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 2025-09-07T09:46:10.1035266Z triton_bmm_84 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 2025-09-07T09:46:10.1036447Z triton_bmm_85 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:46:10.1037859Z triton_bmm_74 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:10.1039035Z triton_bmm_75 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:10.1040192Z triton_bmm_76 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:10.1041448Z triton_bmm_77 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:46:10.1042619Z triton_bmm_79 0.0113 ms 90.9% 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 2025-09-07T09:46:10.1043643Z SingleProcess AUTOTUNE benchmarking takes 0.2396 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:46:10.9592419Z Autotune Choices Stats: 2025-09-07T09:46:10.9593649Z {"num_choices": 16, "num_triton_choices": 11, "best_kernel": "triton_mm_1743", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:46:10.9617707Z AUTOTUNE mm(4x768, 768x2) 2025-09-07T09:46:10.9618007Z strides: [768, 1], [1, 768] 2025-09-07T09:46:10.9618366Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:10.9619131Z triton_mm_1743 0.0082 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 2025-09-07T09:46:10.9620711Z triton_mm_1749 0.0082 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 2025-09-07T09:46:10.9621918Z triton_mm_1750 0.0082 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 2025-09-07T09:46:10.9623107Z triton_mm_1742 0.0092 ms 88.9% 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 2025-09-07T09:46:10.9624291Z triton_mm_1741 0.0102 ms 80.0% 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 2025-09-07T09:46:10.9625534Z triton_mm_1746 0.0102 ms 80.0% 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 2025-09-07T09:46:10.9626722Z triton_mm_1748 0.0102 ms 80.0% 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 2025-09-07T09:46:10.9627515Z decompose_k_mm_6_split_1 0.0113 ms 72.7% k_split=6 2025-09-07T09:46:10.9627921Z decompose_k_mm_4_split_3 0.0113 ms 72.7% k_split=4 2025-09-07T09:46:10.9628714Z triton_mm_1747 0.0123 ms 66.7% 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 2025-09-07T09:46:10.9629743Z SingleProcess AUTOTUNE benchmarking takes 0.8103 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T09:46:11.5099847Z Autotune Choices Stats: 2025-09-07T09:46:11.5101066Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1767", "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": 0.08908800035715103, "best_triton_pos": 0} 2025-09-07T09:46:11.5119953Z AUTOTUNE mm(512x768, 768x20005) 2025-09-07T09:46:11.5120320Z strides: [768, 1], [1, 768] 2025-09-07T09:46:11.5120953Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:11.5121743Z triton_mm_1767 0.0891 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 2025-09-07T09:46:11.5122957Z triton_mm_1762 0.0942 ms 94.6% 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 2025-09-07T09:46:11.5124163Z triton_mm_1766 0.0983 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:11.5125358Z triton_mm_1760 0.1034 ms 86.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:11.5126560Z triton_mm_1768 0.1085 ms 82.1% 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 2025-09-07T09:46:11.5127746Z triton_mm_1763 0.1116 ms 79.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:11.5128911Z triton_mm_1761 0.1249 ms 71.3% 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 2025-09-07T09:46:11.5130089Z triton_mm_1757 0.1362 ms 65.4% 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 2025-09-07T09:46:11.5131272Z triton_mm_1765 0.1362 ms 65.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:46:11.5132621Z triton_mm_1764 0.1372 ms 64.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:11.5133900Z SingleProcess AUTOTUNE benchmarking takes 0.5496 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:46:32.2062021Z Autotune Choices Stats: 2025-09-07T09:46:32.2064609Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.0798719972372055, "best_triton_pos": 1, "best_triton_time": 0.12697599828243256, "best_triton_kernel": "triton_mm_1803", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:46:32.2084491Z AUTOTUNE mm(20005x512, 512x768) 2025-09-07T09:46:32.2084856Z strides: [1, 20032], [768, 1] 2025-09-07T09:46:32.2085148Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:32.2085462Z mm 0.0799 ms 100.0% 2025-09-07T09:46:32.2086188Z triton_mm_1803 0.1270 ms 62.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.2087415Z triton_mm_1801 0.1403 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 2025-09-07T09:46:32.2088628Z triton_mm_1798 0.1454 ms 54.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.2089812Z triton_mm_1802 0.1495 ms 53.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.2091024Z triton_mm_1804 0.1597 ms 50.0% 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 2025-09-07T09:46:32.2092566Z triton_mm_1796 0.1751 ms 45.6% 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 2025-09-07T09:46:32.2094029Z triton_mm_1797 0.1772 ms 45.1% 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 2025-09-07T09:46:32.2095206Z triton_mm_1793 0.1812 ms 44.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:32.2096401Z triton_mm_1799 0.1833 ms 43.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.2097441Z SingleProcess AUTOTUNE benchmarking takes 0.6398 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T09:46:32.7356708Z Autotune Choices Stats: 2025-09-07T09:46:32.7357974Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1858", "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": 0.021503999829292297, "best_triton_pos": 0} 2025-09-07T09:46:32.7377415Z AUTOTUNE mm(768x512, 512x3072) 2025-09-07T09:46:32.7377695Z strides: [1, 768], [3072, 1] 2025-09-07T09:46:32.7377998Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:32.7378775Z triton_mm_1858 0.0215 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 2025-09-07T09:46:32.7379537Z mm 0.0225 ms 95.5% 2025-09-07T09:46:32.7380584Z triton_mm_1856 0.0225 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.7381778Z triton_mm_1862 0.0225 ms 95.5% 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 2025-09-07T09:46:32.7382979Z triton_mm_1857 0.0246 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:32.7384167Z triton_mm_1859 0.0246 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.7385516Z triton_mm_1860 0.0246 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:32.7386719Z triton_mm_1863 0.0246 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:32.7387927Z triton_mm_1864 0.0276 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=5, num_warps=8 2025-09-07T09:46:32.7389129Z triton_mm_1853 0.0287 ms 75.0% 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 2025-09-07T09:46:32.7390153Z SingleProcess AUTOTUNE benchmarking takes 0.2759 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:46:33.2334092Z Autotune Choices Stats: 2025-09-07T09:46:33.2335317Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1892", "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": 0.02252800017595291, "best_triton_pos": 0} 2025-09-07T09:46:33.2354037Z AUTOTUNE mm(3072x512, 512x768) 2025-09-07T09:46:33.2355028Z strides: [1, 3072], [768, 1] 2025-09-07T09:46:33.2355564Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:33.2356978Z triton_mm_1892 0.0225 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 2025-09-07T09:46:33.2359217Z triton_mm_1894 0.0225 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 2025-09-07T09:46:33.2361457Z triton_mm_1895 0.0225 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 2025-09-07T09:46:33.2363759Z triton_mm_1898 0.0225 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 2025-09-07T09:46:33.2365174Z mm 0.0236 ms 95.7% 2025-09-07T09:46:33.2366442Z triton_mm_1896 0.0246 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 2025-09-07T09:46:33.2368607Z triton_mm_1899 0.0246 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 2025-09-07T09:46:33.2370805Z triton_mm_1893 0.0256 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:33.2373206Z triton_mm_1900 0.0276 ms 81.5% 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 2025-09-07T09:46:33.2375803Z triton_mm_1889 0.0287 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:33.2377751Z SingleProcess AUTOTUNE benchmarking takes 0.2789 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:33.8174185Z Autotune Choices Stats: 2025-09-07T09:46:33.8176268Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.020479999482631683, "best_triton_kernel": "triton_mm_1845", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:46:33.8195209Z AUTOTUNE mm(512x768, 768x3072) 2025-09-07T09:46:33.8195538Z strides: [768, 1], [3072, 1] 2025-09-07T09:46:33.8195874Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:33.8196171Z mm 0.0205 ms 100.0% 2025-09-07T09:46:33.8196918Z triton_mm_1845 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 2025-09-07T09:46:33.8198127Z triton_mm_1840 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 2025-09-07T09:46:33.8199327Z triton_mm_1846 0.0215 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:33.8200521Z triton_mm_1838 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=3, num_warps=4 2025-09-07T09:46:33.8201714Z triton_mm_1839 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 2025-09-07T09:46:33.8203266Z triton_mm_1841 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=3, num_warps=4 2025-09-07T09:46:33.8204457Z triton_mm_1844 0.0246 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:33.8205653Z triton_mm_1842 0.0256 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:33.8206847Z triton_mm_1836 0.0287 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:46:33.8207885Z SingleProcess AUTOTUNE benchmarking takes 0.2801 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:34.6366685Z Autotune Choices Stats: 2025-09-07T09:46:34.6368228Z {"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_1930", "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"} 2025-09-07T09:46:34.6389753Z AUTOTUNE mm(768x512, 512x768) 2025-09-07T09:46:34.6390117Z strides: [1, 768], [768, 1] 2025-09-07T09:46:34.6390396Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:34.6390701Z mm 0.0133 ms 100.0% 2025-09-07T09:46:34.6391410Z triton_mm_1930 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 2025-09-07T09:46:34.6392993Z triton_mm_1926 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 2025-09-07T09:46:34.6394196Z triton_mm_1929 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 2025-09-07T09:46:34.6395365Z triton_mm_1932 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 2025-09-07T09:46:34.6396561Z triton_mm_1928 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 2025-09-07T09:46:34.6397751Z triton_mm_1931 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 2025-09-07T09:46:34.6398943Z triton_mm_1935 0.0154 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:34.6400141Z triton_mm_1927 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 2025-09-07T09:46:34.6401329Z triton_mm_1936 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=5, num_warps=8 2025-09-07T09:46:34.6402356Z SingleProcess AUTOTUNE benchmarking takes 0.2514 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:36.0419226Z Autotune Choices Stats: 2025-09-07T09:46:36.0420757Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.11059200018644333, "best_triton_pos": 1, "best_triton_time": 0.13312000036239624, "best_triton_kernel": "triton_mm_1777", "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"} 2025-09-07T09:46:36.0443757Z AUTOTUNE mm(512x20008, 20008x768) 2025-09-07T09:46:36.0444080Z strides: [20032, 1], [768, 1] 2025-09-07T09:46:36.0444382Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:36.0444678Z mm 0.1106 ms 100.0% 2025-09-07T09:46:36.0445392Z triton_mm_1777 0.1331 ms 83.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:46:36.0446598Z triton_mm_1773 0.1761 ms 62.8% 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 2025-09-07T09:46:36.0447790Z triton_mm_1776 0.1894 ms 58.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:46:36.0448999Z triton_mm_1780 0.2099 ms 52.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:36.0450195Z triton_mm_1770 0.2243 ms 49.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:36.0451390Z triton_mm_1771 0.2437 ms 45.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:36.0452570Z triton_mm_1779 0.2468 ms 44.8% 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 2025-09-07T09:46:36.0454007Z triton_mm_1772 0.2488 ms 44.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:36.0455422Z triton_mm_1782 0.2519 ms 43.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:36.0456456Z SingleProcess AUTOTUNE benchmarking takes 0.6660 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:36.4336175Z Autotune Choices Stats: 2025-09-07T09:46:36.4337409Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_1817", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:46:36.4359175Z AUTOTUNE mm(2x4, 4x768) 2025-09-07T09:46:36.4359517Z strides: [1, 2], [768, 1] 2025-09-07T09:46:36.4359813Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:36.4360630Z triton_mm_1817 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:46:36.4361862Z triton_mm_1818 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:46:36.4363073Z triton_mm_1819 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:46:36.4364270Z triton_mm_1820 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:46:36.4365459Z triton_mm_1821 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:36.4374534Z triton_mm_1822 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:36.4375788Z triton_mm_1823 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:36.4376999Z triton_mm_1824 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:36.4378213Z triton_mm_1825 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:46:36.4379427Z triton_mm_1826 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:46:36.4380478Z SingleProcess AUTOTUNE benchmarking takes 0.1616 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:46:37.3457931Z Autotune Choices Stats: 2025-09-07T09:46:37.3459140Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_1807", "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} 2025-09-07T09:46:37.3481199Z AUTOTUNE mm(4x2, 2x768) 2025-09-07T09:46:37.3481474Z strides: [2, 1], [768, 1] 2025-09-07T09:46:37.3481765Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:37.3482540Z triton_mm_1807 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 2025-09-07T09:46:37.3484075Z triton_mm_1814 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 2025-09-07T09:46:37.3485281Z triton_mm_1805 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 2025-09-07T09:46:37.3486466Z triton_mm_1806 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 2025-09-07T09:46:37.3487638Z triton_mm_1808 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 2025-09-07T09:46:37.3488823Z triton_mm_1809 0.0072 ms 85.7% 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 2025-09-07T09:46:37.3490012Z triton_mm_1810 0.0072 ms 85.7% 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 2025-09-07T09:46:37.3491209Z triton_mm_1811 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:37.3492402Z triton_mm_1812 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:37.3493843Z triton_mm_1813 0.0072 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:46:37.3494876Z SingleProcess AUTOTUNE benchmarking takes 0.1574 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T09:46:37.6771000Z Autotune Choices Stats: 2025-09-07T09:46:37.6773025Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "mm", "best_time": 0.025599999353289604, "best_triton_pos": 1, "best_triton_time": 0.025599999353289604, "best_triton_kernel": "triton_mm_1873", "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"} 2025-09-07T09:46:37.6795204Z AUTOTUNE mm(512x3072, 3072x768) 2025-09-07T09:46:37.6795532Z strides: [3072, 1], [768, 1] 2025-09-07T09:46:37.6795839Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:37.6796134Z mm 0.0256 ms 100.0% 2025-09-07T09:46:37.6796856Z triton_mm_1873 0.0256 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 2025-09-07T09:46:37.6798052Z triton_mm_1869 0.0338 ms 75.8% 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 2025-09-07T09:46:37.6799252Z triton_mm_1872 0.0358 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:46:37.6800428Z triton_mm_1876 0.0379 ms 67.6% 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 2025-09-07T09:46:37.6801610Z triton_mm_1866 0.0440 ms 58.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:37.6802779Z triton_mm_1867 0.0451 ms 56.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:37.6803955Z triton_mm_1868 0.0451 ms 56.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:37.6805357Z triton_mm_1875 0.0461 ms 55.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:46:37.6806545Z triton_mm_1878 0.0492 ms 52.1% 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 2025-09-07T09:46:37.6807566Z SingleProcess AUTOTUNE benchmarking takes 0.3301 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:37.9294980Z Autotune Choices Stats: 2025-09-07T09:46:37.9296146Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1909", "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} 2025-09-07T09:46:37.9320097Z AUTOTUNE mm(512x768, 768x768) 2025-09-07T09:46:37.9320399Z strides: [768, 1], [768, 1] 2025-09-07T09:46:37.9320704Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:37.9321493Z triton_mm_1909 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 2025-09-07T09:46:37.9322253Z mm 0.0143 ms 92.9% 2025-09-07T09:46:37.9322931Z triton_mm_1908 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 2025-09-07T09:46:37.9324114Z triton_mm_1912 0.0154 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:46:37.9325301Z triton_mm_1905 0.0164 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:46:37.9326802Z triton_mm_1911 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=4, num_warps=8 2025-09-07T09:46:37.9328003Z triton_mm_1902 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:37.9329197Z triton_mm_1903 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:37.9330379Z triton_mm_1904 0.0174 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:37.9331554Z triton_mm_1914 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=4, num_warps=8 2025-09-07T09:46:37.9332592Z SingleProcess AUTOTUNE benchmarking takes 0.2512 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:38.1651277Z Autotune Choices Stats: 2025-09-07T09:46:38.1652486Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_1944", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:46:38.1676865Z AUTOTUNE bmm(48x128x128, 48x128x64) 2025-09-07T09:46:38.1677194Z strides: [16384, 1, 128], [8192, 64, 1] 2025-09-07T09:46:38.1677522Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:38.1678291Z triton_bmm_1944 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 2025-09-07T09:46:38.1679845Z triton_bmm_1945 0.0102 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 2025-09-07T09:46:38.1681052Z triton_bmm_1946 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 2025-09-07T09:46:38.1682247Z triton_bmm_1947 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 2025-09-07T09:46:38.1683429Z triton_bmm_1948 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 2025-09-07T09:46:38.1684635Z triton_bmm_1949 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:46:38.1685851Z triton_bmm_1951 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=4, num_warps=8 2025-09-07T09:46:38.1687050Z triton_bmm_1938 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:38.1688244Z triton_bmm_1939 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:38.1689434Z triton_bmm_1940 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:38.1690460Z SingleProcess AUTOTUNE benchmarking takes 0.2350 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:46:38.4092780Z Autotune Choices Stats: 2025-09-07T09:46:38.4094522Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_1956", "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} 2025-09-07T09:46:38.4118883Z AUTOTUNE bmm(48x128x64, 48x64x128) 2025-09-07T09:46:38.4119257Z strides: [8192, 64, 1], [8192, 1, 64] 2025-09-07T09:46:38.4119589Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:38.4120373Z triton_bmm_1956 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 2025-09-07T09:46:38.4121583Z triton_bmm_1959 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 2025-09-07T09:46:38.4122830Z triton_bmm_1960 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:38.4124032Z triton_bmm_1961 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 2025-09-07T09:46:38.4125233Z triton_bmm_1962 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 2025-09-07T09:46:38.4126440Z triton_bmm_1963 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 2025-09-07T09:46:38.4127649Z triton_bmm_1964 0.0102 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 2025-09-07T09:46:38.4129207Z triton_bmm_1965 0.0102 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 2025-09-07T09:46:38.4130407Z triton_bmm_1966 0.0102 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 2025-09-07T09:46:38.4131625Z triton_bmm_1967 0.0102 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 2025-09-07T09:46:38.4132668Z SingleProcess AUTOTUNE benchmarking takes 0.2436 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:46:38.6191954Z Autotune Choices Stats: 2025-09-07T09:46:38.6193149Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_bmm_1982", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:46:38.6224083Z AUTOTUNE bmm(48x64x128, 48x128x128) 2025-09-07T09:46:38.6224428Z strides: [8192, 1, 64], [16384, 128, 1] 2025-09-07T09:46:38.6224756Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:38.6225586Z triton_bmm_1982 0.0102 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 2025-09-07T09:46:38.6226812Z triton_bmm_1983 0.0102 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 2025-09-07T09:46:38.6228020Z triton_bmm_1984 0.0102 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 2025-09-07T09:46:38.6229485Z triton_bmm_1986 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 2025-09-07T09:46:38.6230691Z triton_bmm_1987 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 2025-09-07T09:46:38.6231895Z triton_bmm_1975 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:38.6233084Z triton_bmm_1976 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:38.6234260Z triton_bmm_1977 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:38.6235468Z triton_bmm_1978 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:46:38.6236658Z triton_bmm_1980 0.0113 ms 90.9% 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 2025-09-07T09:46:38.6237686Z SingleProcess AUTOTUNE benchmarking takes 0.2100 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:46:38.8546620Z Autotune Choices Stats: 2025-09-07T09:46:38.8547840Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_1994", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T09:46:38.8577005Z AUTOTUNE bmm(48x128x128, 48x128x64) 2025-09-07T09:46:38.8577345Z strides: [16384, 128, 1], [8192, 1, 128] 2025-09-07T09:46:38.8577677Z dtypes: torch.float16, torch.float16 2025-09-07T09:46:38.8578474Z triton_bmm_1994 0.0102 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 2025-09-07T09:46:38.8579702Z triton_bmm_1997 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 2025-09-07T09:46:38.8580927Z triton_bmm_1998 0.0102 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 2025-09-07T09:46:38.8582132Z triton_bmm_1999 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 2025-09-07T09:46:38.8583324Z triton_bmm_2000 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 2025-09-07T09:46:38.8584527Z triton_bmm_2001 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 2025-09-07T09:46:38.8585802Z triton_bmm_2002 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:46:38.8587008Z triton_bmm_1991 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:46:38.8588201Z triton_bmm_1992 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:38.8589603Z triton_bmm_1993 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:46:38.8590638Z SingleProcess AUTOTUNE benchmarking takes 0.2345 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:46:44.2582281Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:46:44.2583528Z pred = mod(*cloned_inputs) 2025-09-07T09:46:44.2584160Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward 2025-09-07T09:46:44.2584820Z x = self.bert(x, segment_label) 2025-09-07T09:46:44.2585467Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward 2025-09-07T09:46:44.2586112Z x = self.embedding(x, segment_info) 2025-09-07T09:46:44.2586749Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward 2025-09-07T09:46:44.2587544Z x = self.token(sequence) + self.position(sequence) + self.segment(segment_label) 2025-09-07T09:46:44.2587928Z 2025-09-07T09:46:44.2587933Z 2025-09-07T09:46:45.7206409Z pass 2025-09-07T09:46:50.4674148Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:46:50.4676753Z import pynvml # type: ignore[import] 2025-09-07T09:46:53.2645075Z 2025-09-07T09:46:57.1904550Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:46:57.1905008Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:46:57.1905836Z cuda train Background_Matting 2025-09-07T09:46:57.2138028Z pass_due_to_skip 2025-09-07T09:46:59.0923864Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:46:59.0925282Z import pynvml # type: ignore[import] 2025-09-07T09:47:01.9054630Z 2025-09-07T09:47:05.3875562Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:05.3875954Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:47:05.3876292Z cuda train LearningToPaint 2025-09-07T09:47:16.6656871Z Autotune Choices Stats: 2025-09-07T09:47:16.6658108Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_150", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:47:16.6683981Z AUTOTUNE mm(4x512, 512x65) 2025-09-07T09:47:16.6684328Z strides: [512, 1], [1, 512] 2025-09-07T09:47:16.6684639Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:16.6685421Z triton_mm_150 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 2025-09-07T09:47:16.6686622Z triton_mm_148 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=5, num_warps=4 2025-09-07T09:47:16.6687794Z triton_mm_149 0.0092 ms 88.9% 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 2025-09-07T09:47:16.6688963Z triton_mm_153 0.0092 ms 88.9% 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 2025-09-07T09:47:16.6690523Z triton_mm_154 0.0092 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:47:16.6691694Z triton_mm_147 0.0102 ms 80.0% 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 2025-09-07T09:47:16.6693141Z triton_mm_157 0.0102 ms 80.0% 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 2025-09-07T09:47:16.6694328Z triton_mm_158 0.0102 ms 80.0% 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 2025-09-07T09:47:16.6695507Z triton_mm_160 0.0102 ms 80.0% 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 2025-09-07T09:47:16.6696688Z triton_mm_162 0.0102 ms 80.0% 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 2025-09-07T09:47:16.6697708Z SingleProcess AUTOTUNE benchmarking takes 0.2419 seconds and 0.9262 seconds precompiling for 18 choices 2025-09-07T09:47:17.5577729Z Autotune Choices Stats: 2025-09-07T09:47:17.5579086Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_4", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T09:47:17.5604161Z AUTOTUNE convolution(4x9x128x128, 64x9x3x3) 2025-09-07T09:47:17.5604933Z strides: [147456, 1, 1152, 9], [81, 1, 27, 9] 2025-09-07T09:47:17.5605273Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:17.5606192Z triton_convolution2d_4 0.0154 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:17.5607663Z triton_convolution2d_0 0.0164 ms 93.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:17.5609130Z triton_convolution2d_3 0.0174 ms 88.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:17.5610595Z triton_convolution2d_5 0.0195 ms 78.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:17.5611500Z convolution 0.0205 ms 75.0% 2025-09-07T09:47:17.5612365Z triton_convolution2d_2 0.0256 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:47:17.5614099Z triton_convolution2d_1 0.0297 ms 51.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:17.5615267Z SingleProcess AUTOTUNE benchmarking takes 0.1512 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:47:17.6866311Z Autotune Choices Stats: 2025-09-07T09:47:17.6868320Z {"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_10", "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"} 2025-09-07T09:47:17.6894249Z AUTOTUNE convolution(4x64x64x64, 64x64x3x3) 2025-09-07T09:47:17.6894649Z strides: [262144, 1, 4096, 64], [576, 1, 192, 64] 2025-09-07T09:47:17.6894992Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:17.6895308Z convolution 0.0133 ms 100.0% 2025-09-07T09:47:17.6896185Z triton_convolution2d_10 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 2025-09-07T09:47:17.6897660Z triton_convolution2d_11 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=8 2025-09-07T09:47:17.6899143Z triton_convolution2d_9 0.0236 ms 56.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:17.6900602Z triton_convolution2d_6 0.0276 ms 48.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:17.6902056Z triton_convolution2d_12 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 2025-09-07T09:47:17.6903528Z triton_convolution2d_7 0.0410 ms 32.5% 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 2025-09-07T09:47:17.6905278Z triton_convolution2d_8 0.0676 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 2025-09-07T09:47:17.6906457Z SingleProcess AUTOTUNE benchmarking takes 0.1284 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:17.8134547Z Autotune Choices Stats: 2025-09-07T09:47:17.8136156Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01228800043463707, "best_triton_pos": 1, "best_triton_time": 0.020479999482631683, "best_triton_kernel": "triton_convolution2d_17", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:17.8161872Z AUTOTUNE convolution(4x64x32x32, 64x64x3x3) 2025-09-07T09:47:17.8162259Z strides: [65536, 1, 2048, 64], [576, 1, 192, 64] 2025-09-07T09:47:17.8162611Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:17.8162931Z convolution 0.0123 ms 100.0% 2025-09-07T09:47:17.8163810Z triton_convolution2d_17 0.0205 ms 60.0% 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 2025-09-07T09:47:17.8165281Z triton_convolution2d_18 0.0205 ms 60.0% 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 2025-09-07T09:47:17.8166751Z triton_convolution2d_16 0.0225 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 2025-09-07T09:47:17.8168220Z triton_convolution2d_13 0.0266 ms 46.2% 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 2025-09-07T09:47:17.8169871Z triton_convolution2d_19 0.0317 ms 38.7% 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 2025-09-07T09:47:17.8171361Z triton_convolution2d_14 0.0389 ms 31.6% 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 2025-09-07T09:47:17.8173067Z triton_convolution2d_15 0.0604 ms 20.3% 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 2025-09-07T09:47:17.8174252Z SingleProcess AUTOTUNE benchmarking takes 0.1259 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:17.9245617Z Autotune Choices Stats: 2025-09-07T09:47:17.9246913Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_24", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:47:17.9273873Z AUTOTUNE convolution(4x64x64x64, 64x64x1x1) 2025-09-07T09:47:17.9274232Z strides: [262144, 1, 4096, 64], [64, 1, 64, 64] 2025-09-07T09:47:17.9274585Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:17.9275485Z triton_convolution2d_24 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 2025-09-07T09:47:17.9276955Z triton_convolution2d_25 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=8 2025-09-07T09:47:17.9278078Z convolution 0.0092 ms 88.9% 2025-09-07T09:47:17.9278938Z triton_convolution2d_20 0.0092 ms 88.9% 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 2025-09-07T09:47:17.9280386Z triton_convolution2d_23 0.0092 ms 88.9% 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 2025-09-07T09:47:17.9281859Z triton_convolution2d_26 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 2025-09-07T09:47:17.9283322Z triton_convolution2d_21 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 2025-09-07T09:47:17.9284807Z triton_convolution2d_22 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 2025-09-07T09:47:17.9285974Z SingleProcess AUTOTUNE benchmarking takes 0.1103 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.0546237Z Autotune Choices Stats: 2025-09-07T09:47:18.0547886Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01228800043463707, "best_triton_pos": 1, "best_triton_time": 0.020479999482631683, "best_triton_kernel": "triton_convolution2d_45", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:18.0573321Z AUTOTUNE convolution(4x64x32x32, 128x64x3x3) 2025-09-07T09:47:18.0573700Z strides: [65536, 1, 2048, 64], [576, 1, 192, 64] 2025-09-07T09:47:18.0574053Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.0574660Z convolution 0.0123 ms 100.0% 2025-09-07T09:47:18.0575521Z triton_convolution2d_45 0.0205 ms 60.0% 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 2025-09-07T09:47:18.0577006Z triton_convolution2d_46 0.0236 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:18.0578490Z triton_convolution2d_41 0.0287 ms 42.9% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:18.0579976Z triton_convolution2d_44 0.0297 ms 41.4% 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 2025-09-07T09:47:18.0581459Z triton_convolution2d_47 0.0317 ms 38.7% 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 2025-09-07T09:47:18.0582935Z triton_convolution2d_42 0.0399 ms 30.8% 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 2025-09-07T09:47:18.0584418Z triton_convolution2d_43 0.0666 ms 18.5% 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 2025-09-07T09:47:18.0585843Z SingleProcess AUTOTUNE benchmarking takes 0.1272 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.2021615Z Autotune Choices Stats: 2025-09-07T09:47:18.2023277Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.03686400130391121, "best_triton_kernel": "triton_convolution2d_52", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:18.2048780Z AUTOTUNE convolution(4x128x16x16, 128x128x3x3) 2025-09-07T09:47:18.2049209Z strides: [32768, 1, 2048, 128], [1152, 1, 384, 128] 2025-09-07T09:47:18.2049569Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.2049878Z convolution 0.0143 ms 100.0% 2025-09-07T09:47:18.2050751Z triton_convolution2d_52 0.0369 ms 38.9% 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 2025-09-07T09:47:18.2052246Z triton_convolution2d_53 0.0399 ms 35.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:18.2053961Z triton_convolution2d_51 0.0532 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 2025-09-07T09:47:18.2055453Z triton_convolution2d_48 0.0553 ms 25.9% 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 2025-09-07T09:47:18.2056925Z triton_convolution2d_54 0.0553 ms 25.9% 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 2025-09-07T09:47:18.2058632Z triton_convolution2d_49 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:18.2060116Z triton_convolution2d_50 0.1188 ms 12.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:47:18.2061275Z SingleProcess AUTOTUNE benchmarking takes 0.1468 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.3125637Z Autotune Choices Stats: 2025-09-07T09:47:18.3126919Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_59", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.008191999979317188, "best_triton_pos": 0} 2025-09-07T09:47:18.3152576Z AUTOTUNE convolution(4x64x32x32, 128x64x1x1) 2025-09-07T09:47:18.3152969Z strides: [65536, 1, 2048, 64], [64, 1, 64, 64] 2025-09-07T09:47:18.3153314Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.3154203Z triton_convolution2d_59 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 2025-09-07T09:47:18.3155110Z convolution 0.0092 ms 88.9% 2025-09-07T09:47:18.3155974Z triton_convolution2d_55 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 2025-09-07T09:47:18.3157441Z triton_convolution2d_60 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 2025-09-07T09:47:18.3159157Z triton_convolution2d_58 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 2025-09-07T09:47:18.3160640Z triton_convolution2d_61 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 2025-09-07T09:47:18.3162114Z triton_convolution2d_56 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 2025-09-07T09:47:18.3163583Z triton_convolution2d_57 0.0143 ms 57.1% 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 2025-09-07T09:47:18.3164756Z SingleProcess AUTOTUNE benchmarking takes 0.1096 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.4633738Z Autotune Choices Stats: 2025-09-07T09:47:18.4635358Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.03686400130391121, "best_triton_kernel": "triton_convolution2d_80", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:18.4661038Z AUTOTUNE convolution(4x128x16x16, 256x128x3x3) 2025-09-07T09:47:18.4661435Z strides: [32768, 1, 2048, 128], [1152, 1, 384, 128] 2025-09-07T09:47:18.4661793Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.4662102Z convolution 0.0143 ms 100.0% 2025-09-07T09:47:18.4663230Z triton_convolution2d_80 0.0369 ms 38.9% 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 2025-09-07T09:47:18.4664720Z triton_convolution2d_79 0.0563 ms 25.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:18.4666311Z triton_convolution2d_81 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 2025-09-07T09:47:18.4667791Z triton_convolution2d_82 0.0573 ms 25.0% 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 2025-09-07T09:47:18.4669267Z triton_convolution2d_76 0.0727 ms 19.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:18.4670739Z triton_convolution2d_77 0.0737 ms 19.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:18.4672203Z triton_convolution2d_78 0.0870 ms 16.5% 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 2025-09-07T09:47:18.4673373Z SingleProcess AUTOTUNE benchmarking takes 0.1481 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.6466867Z Autotune Choices Stats: 2025-09-07T09:47:18.6468539Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.06860800087451935, "best_triton_kernel": "triton_convolution2d_87", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:18.6494038Z AUTOTUNE convolution(4x256x8x8, 256x256x3x3) 2025-09-07T09:47:18.6494443Z strides: [16384, 1, 2048, 256], [2304, 1, 768, 256] 2025-09-07T09:47:18.6494806Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.6495112Z convolution 0.0195 ms 100.0% 2025-09-07T09:47:18.6495998Z triton_convolution2d_87 0.0686 ms 28.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:18.6497475Z triton_convolution2d_86 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:18.6498968Z triton_convolution2d_88 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 2025-09-07T09:47:18.6500448Z triton_convolution2d_89 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 2025-09-07T09:47:18.6501917Z triton_convolution2d_85 0.1116 ms 17.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:47:18.6503389Z triton_convolution2d_84 0.1331 ms 14.6% 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 2025-09-07T09:47:18.6505134Z triton_convolution2d_83 0.1372 ms 14.2% 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 2025-09-07T09:47:18.6506296Z SingleProcess AUTOTUNE benchmarking takes 0.1825 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.7589150Z Autotune Choices Stats: 2025-09-07T09:47:18.7590765Z {"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_94", "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"} 2025-09-07T09:47:18.7617205Z AUTOTUNE convolution(4x128x16x16, 256x128x1x1) 2025-09-07T09:47:18.7617634Z strides: [32768, 1, 2048, 128], [128, 1, 128, 128] 2025-09-07T09:47:18.7617989Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.7618294Z convolution 0.0092 ms 100.0% 2025-09-07T09:47:18.7619180Z triton_convolution2d_94 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 2025-09-07T09:47:18.7620657Z triton_convolution2d_93 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 2025-09-07T09:47:18.7622130Z triton_convolution2d_95 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 2025-09-07T09:47:18.7623594Z triton_convolution2d_96 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 2025-09-07T09:47:18.7625317Z triton_convolution2d_90 0.0143 ms 64.3% 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:47:18.7626796Z triton_convolution2d_91 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 2025-09-07T09:47:18.7628261Z triton_convolution2d_92 0.0143 ms 64.3% 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 2025-09-07T09:47:18.7629436Z SingleProcess AUTOTUNE benchmarking takes 0.1115 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:18.9457218Z Autotune Choices Stats: 2025-09-07T09:47:18.9458908Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 1, "best_triton_time": 0.06963200122117996, "best_triton_kernel": "triton_convolution2d_115", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:18.9485774Z AUTOTUNE convolution(4x256x8x8, 512x256x3x3) 2025-09-07T09:47:18.9486146Z strides: [16384, 1, 2048, 256], [2304, 1, 768, 256] 2025-09-07T09:47:18.9486510Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:18.9486835Z convolution 0.0184 ms 100.0% 2025-09-07T09:47:18.9487713Z triton_convolution2d_115 0.0696 ms 26.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:18.9489506Z triton_convolution2d_117 0.0993 ms 18.6% 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 2025-09-07T09:47:18.9490998Z triton_convolution2d_114 0.1034 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:18.9492494Z triton_convolution2d_113 0.1096 ms 16.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:47:18.9494238Z triton_convolution2d_116 0.1096 ms 16.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:18.9495746Z triton_convolution2d_112 0.1331 ms 13.8% 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 2025-09-07T09:47:18.9497224Z triton_convolution2d_111 0.1403 ms 13.1% 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 2025-09-07T09:47:18.9498393Z SingleProcess AUTOTUNE benchmarking takes 0.1837 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:19.1891630Z Autotune Choices Stats: 2025-09-07T09:47:19.1893488Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.13619199395179749, "best_triton_kernel": "triton_convolution2d_122", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:47:19.1920775Z AUTOTUNE convolution(4x512x4x4, 512x512x3x3) 2025-09-07T09:47:19.1921159Z strides: [8192, 1, 2048, 512], [4608, 1, 1536, 512] 2025-09-07T09:47:19.1921516Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:19.1921825Z convolution 0.0225 ms 100.0% 2025-09-07T09:47:19.1922694Z triton_convolution2d_122 0.1362 ms 16.5% 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 2025-09-07T09:47:19.1924185Z triton_convolution2d_124 0.1454 ms 15.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:19.1925666Z triton_convolution2d_121 0.1577 ms 14.3% 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 2025-09-07T09:47:19.1927156Z triton_convolution2d_120 0.1905 ms 11.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=4 2025-09-07T09:47:19.1928629Z triton_convolution2d_123 0.2089 ms 10.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:47:19.1930097Z triton_convolution2d_119 0.2253 ms 10.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:47:19.1931571Z triton_convolution2d_118 0.2642 ms 8.5% 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 2025-09-07T09:47:19.1933050Z SingleProcess AUTOTUNE benchmarking takes 0.2426 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:19.3078153Z Autotune Choices Stats: 2025-09-07T09:47:19.3079769Z {"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_129", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:47:19.3106389Z AUTOTUNE convolution(4x256x8x8, 512x256x1x1) 2025-09-07T09:47:19.3106786Z strides: [16384, 1, 2048, 256], [256, 1, 256, 256] 2025-09-07T09:47:19.3107148Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:19.3107492Z convolution 0.0102 ms 100.0% 2025-09-07T09:47:19.3108351Z triton_convolution2d_129 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 2025-09-07T09:47:19.3109835Z triton_convolution2d_127 0.0143 ms 71.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:47:19.3111315Z triton_convolution2d_126 0.0164 ms 62.5% 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 2025-09-07T09:47:19.3112803Z triton_convolution2d_128 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 2025-09-07T09:47:19.3114501Z triton_convolution2d_131 0.0164 ms 62.5% 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 2025-09-07T09:47:19.3115989Z triton_convolution2d_130 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 2025-09-07T09:47:19.3117467Z triton_convolution2d_125 0.0205 ms 50.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:47:19.3118633Z SingleProcess AUTOTUNE benchmarking takes 0.1177 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:47:24.4476911Z Autotune Choices Stats: 2025-09-07T09:47:24.4478173Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_180", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:47:24.4506207Z AUTOTUNE mm(65x4, 4x512) 2025-09-07T09:47:24.4506548Z strides: [1, 65], [512, 1] 2025-09-07T09:47:24.4506841Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:24.4507616Z triton_mm_180 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 2025-09-07T09:47:24.4508827Z triton_mm_181 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 2025-09-07T09:47:24.4510003Z triton_mm_182 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 2025-09-07T09:47:24.4511577Z triton_mm_183 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 2025-09-07T09:47:24.4512768Z triton_mm_184 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 2025-09-07T09:47:24.4513957Z triton_mm_185 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 2025-09-07T09:47:24.4515141Z triton_mm_186 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 2025-09-07T09:47:24.4516327Z triton_mm_187 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 2025-09-07T09:47:24.4517527Z triton_mm_188 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 2025-09-07T09:47:24.4518713Z triton_mm_189 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 2025-09-07T09:47:24.4519757Z SingleProcess AUTOTUNE benchmarking takes 0.2063 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:47:25.1718377Z Autotune Choices Stats: 2025-09-07T09:47:25.1719612Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_165", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T09:47:25.1747752Z AUTOTUNE mm(4x65, 65x512) 2025-09-07T09:47:25.1748064Z strides: [65, 1], [512, 1] 2025-09-07T09:47:25.1748360Z dtypes: torch.float16, torch.float16 2025-09-07T09:47:25.1749149Z triton_mm_165 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:47:25.1750338Z triton_mm_166 0.0072 ms 100.0% 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 2025-09-07T09:47:25.1751524Z triton_mm_170 0.0072 ms 100.0% 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 2025-09-07T09:47:25.1752720Z triton_mm_171 0.0072 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 2025-09-07T09:47:25.1753915Z triton_mm_177 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:47:25.1755101Z triton_mm_164 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:47:25.1756282Z triton_mm_167 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:47:25.1757453Z triton_mm_169 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:47:25.1758621Z triton_mm_172 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:47:25.1760030Z triton_mm_173 0.0082 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:47:25.1761066Z SingleProcess AUTOTUNE benchmarking takes 0.2170 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:47:28.1081637Z pass 2025-09-07T09:47:31.8677808Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:47:31.8679224Z import pynvml # type: ignore[import] 2025-09-07T09:47:34.6064518Z 2025-09-07T09:47:37.5133163Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:47:37.5133554Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:47:37.5133919Z cuda train Super_SloMo 2025-09-07T09:48:53.3431157Z Autotune Choices Stats: 2025-09-07T09:48:53.3433870Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_324", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.09625600278377533, "best_triton_pos": 0} 2025-09-07T09:48:53.3461890Z AUTOTUNE convolution(4x3x352x352, 64x3x3x3) 2025-09-07T09:48:53.3462658Z strides: [371712, 123904, 352, 1], [27, 9, 3, 1] 2025-09-07T09:48:53.3463378Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:53.3465355Z triton_convolution2d_324 0.0963 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 2025-09-07T09:48:53.3468357Z triton_convolution2d_320 0.1024 ms 94.0% 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 2025-09-07T09:48:53.3471857Z triton_convolution2d_319 0.1188 ms 81.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:53.3474815Z triton_convolution2d_322 0.1290 ms 74.6% 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 2025-09-07T09:48:53.3477755Z triton_convolution2d_323 0.1352 ms 71.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:53.3480751Z triton_convolution2d_321 0.1567 ms 61.4% 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 2025-09-07T09:48:53.3482618Z convolution 0.1638 ms 58.8% 2025-09-07T09:48:53.3483746Z SingleProcess AUTOTUNE benchmarking takes 0.1854 seconds and 0.0004 seconds precompiling for 7 choices 2025-09-07T09:48:54.0214332Z Autotune Choices Stats: 2025-09-07T09:48:54.0217382Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.43212801218032837, "best_triton_pos": 1, "best_triton_time": 0.4853760004043579, "best_triton_kernel": "triton_convolution2d_326", "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"} 2025-09-07T09:48:54.0245187Z AUTOTUNE convolution(4x64x352x352, 64x64x3x3) 2025-09-07T09:48:54.0245915Z strides: [7929856, 123904, 352, 1], [576, 9, 3, 1] 2025-09-07T09:48:54.0246641Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:54.0247209Z convolution 0.4321 ms 100.0% 2025-09-07T09:48:54.0249326Z triton_convolution2d_326 0.4854 ms 89.0% 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 2025-09-07T09:48:54.0252009Z triton_convolution2d_331 0.4997 ms 86.5% 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 2025-09-07T09:48:54.0254939Z triton_convolution2d_328 0.5437 ms 79.5% 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 2025-09-07T09:48:54.0257720Z triton_convolution2d_329 0.6420 ms 67.3% 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 2025-09-07T09:48:54.0260228Z triton_convolution2d_330 0.6605 ms 65.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:54.0262777Z triton_convolution2d_325 0.7137 ms 60.5% 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 2025-09-07T09:48:54.0265697Z triton_convolution2d_327 1.7029 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 2025-09-07T09:48:54.0267902Z SingleProcess AUTOTUNE benchmarking takes 0.3049 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:54.3471406Z Autotune Choices Stats: 2025-09-07T09:48:54.3474836Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.26009601354599, "best_triton_pos": 1, "best_triton_time": 0.26214399933815, "best_triton_kernel": "triton_convolution2d_1", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:48:54.3502377Z AUTOTUNE convolution(4x6x352x352, 32x6x7x7) 2025-09-07T09:48:54.3503099Z strides: [743424, 123904, 352, 1], [294, 49, 7, 1] 2025-09-07T09:48:54.3503752Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:54.3504312Z convolution 0.2601 ms 100.0% 2025-09-07T09:48:54.3505998Z triton_convolution2d_1 0.2621 ms 99.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:54.3508821Z triton_convolution2d_5 0.2816 ms 92.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:54.3511622Z triton_convolution2d_3 0.3604 ms 72.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:54.3514395Z triton_convolution2d_0 0.3963 ms 65.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:54.3517008Z triton_convolution2d_4 0.4639 ms 56.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:54.3519764Z triton_convolution2d_2 0.5560 ms 46.8% 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 2025-09-07T09:48:54.3522300Z SingleProcess AUTOTUNE benchmarking takes 0.2636 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:48:55.0137938Z Autotune Choices Stats: 2025-09-07T09:48:55.0139626Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.5007359981536865, "best_triton_pos": 1, "best_triton_time": 0.9994239807128906, "best_triton_kernel": "triton_convolution2d_7", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:48:55.0169145Z AUTOTUNE convolution(4x32x352x352, 32x32x7x7) 2025-09-07T09:48:55.0169539Z strides: [3964928, 123904, 352, 1], [1568, 49, 7, 1] 2025-09-07T09:48:55.0169894Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:55.0170251Z convolution 0.5007 ms 100.0% 2025-09-07T09:48:55.0171146Z triton_convolution2d_7 0.9994 ms 50.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:55.0172632Z triton_convolution2d_12 1.5237 ms 32.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:55.0174359Z triton_convolution2d_6 1.7132 ms 29.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:55.0175835Z triton_convolution2d_8 2.0992 ms 23.9% 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 2025-09-07T09:48:55.0177675Z triton_convolution2d_11 2.2333 ms 22.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:55.0179140Z triton_convolution2d_9 2.4648 ms 20.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:55.0180612Z triton_convolution2d_10 4.2271 ms 11.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:55.0181776Z SingleProcess AUTOTUNE benchmarking takes 0.3552 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:55.3302035Z Autotune Choices Stats: 2025-09-07T09:48:55.3303748Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.3389439880847931, "best_triton_pos": 1, "best_triton_time": 0.3491840064525604, "best_triton_kernel": "triton_convolution2d_140", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:48:55.3334231Z AUTOTUNE convolution(4x64x352x352, 32x64x3x3) 2025-09-07T09:48:55.3334640Z strides: [7929856, 123904, 352, 1], [576, 9, 3, 1] 2025-09-07T09:48:55.3335012Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:55.3335334Z convolution 0.3389 ms 100.0% 2025-09-07T09:48:55.3336238Z triton_convolution2d_140 0.3492 ms 97.1% 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 2025-09-07T09:48:55.3337743Z triton_convolution2d_145 0.4536 ms 74.7% 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 2025-09-07T09:48:55.3348659Z triton_convolution2d_139 0.4936 ms 68.7% 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 2025-09-07T09:48:55.3350315Z triton_convolution2d_142 0.4997 ms 67.8% 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 2025-09-07T09:48:55.3351793Z triton_convolution2d_143 0.5622 ms 60.3% 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 2025-09-07T09:48:55.3353258Z triton_convolution2d_144 0.5765 ms 58.8% 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 2025-09-07T09:48:55.3354753Z triton_convolution2d_141 0.8622 ms 39.3% 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 2025-09-07T09:48:55.3355937Z SingleProcess AUTOTUNE benchmarking takes 0.3004 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:55.9326170Z Autotune Choices Stats: 2025-09-07T09:48:55.9328656Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_160", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.7895039916038513, "best_triton_pos": 0} 2025-09-07T09:48:55.9360276Z AUTOTUNE convolution(4x20x352x352, 32x20x7x7) 2025-09-07T09:48:55.9361434Z strides: [2478080, 123904, 352, 1], [980, 49, 7, 1] 2025-09-07T09:48:55.9362012Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:55.9363559Z triton_convolution2d_160 0.7895 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:55.9365049Z convolution 0.8376 ms 94.3% 2025-09-07T09:48:55.9366678Z triton_convolution2d_165 0.9011 ms 87.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:55.9369482Z triton_convolution2d_162 1.1909 ms 66.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:55.9372270Z triton_convolution2d_159 1.2739 ms 62.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:55.9375430Z triton_convolution2d_164 1.2851 ms 61.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:55.9378197Z triton_convolution2d_163 1.4602 ms 54.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:55.9380902Z triton_convolution2d_161 1.7695 ms 44.6% 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=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:48:55.9383086Z SingleProcess AUTOTUNE benchmarking takes 0.3256 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:56.3282982Z Autotune Choices Stats: 2025-09-07T09:48:56.3286573Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.18636800348758698, "best_triton_pos": 1, "best_triton_time": 0.24985599517822266, "best_triton_kernel": "triton_convolution2d_338", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:48:56.3316023Z AUTOTUNE convolution(4x64x176x176, 128x64x3x3) 2025-09-07T09:48:56.3316720Z strides: [1982464, 30976, 176, 1], [576, 9, 3, 1] 2025-09-07T09:48:56.3317355Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:56.3317905Z convolution 0.1864 ms 100.0% 2025-09-07T09:48:56.3319550Z triton_convolution2d_338 0.2499 ms 74.6% 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 2025-09-07T09:48:56.3322378Z triton_convolution2d_333 0.2652 ms 70.3% 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 2025-09-07T09:48:56.3325054Z triton_convolution2d_335 0.2816 ms 66.2% 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 2025-09-07T09:48:56.3327826Z triton_convolution2d_332 0.3410 ms 54.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:56.3330596Z triton_convolution2d_336 0.3512 ms 53.1% 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 2025-09-07T09:48:56.3334106Z triton_convolution2d_337 0.4649 ms 40.1% 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 2025-09-07T09:48:56.3336647Z triton_convolution2d_334 0.8253 ms 22.6% 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 2025-09-07T09:48:56.3338649Z SingleProcess AUTOTUNE benchmarking takes 0.2990 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:56.9181311Z Autotune Choices Stats: 2025-09-07T09:48:56.9184359Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2734079957008362, "best_triton_pos": 1, "best_triton_time": 0.5693439841270447, "best_triton_kernel": "triton_convolution2d_340", "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"} 2025-09-07T09:48:56.9218947Z AUTOTUNE convolution(4x128x176x176, 128x128x3x3) 2025-09-07T09:48:56.9219672Z strides: [3964928, 30976, 176, 1], [1152, 9, 3, 1] 2025-09-07T09:48:56.9220273Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:56.9220792Z convolution 0.2734 ms 100.0% 2025-09-07T09:48:56.9222374Z triton_convolution2d_340 0.5693 ms 48.0% 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 2025-09-07T09:48:56.9225246Z triton_convolution2d_345 0.6134 ms 44.6% 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 2025-09-07T09:48:56.9227951Z triton_convolution2d_339 0.6912 ms 39.6% 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 2025-09-07T09:48:56.9231189Z triton_convolution2d_342 0.8069 ms 33.9% 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 2025-09-07T09:48:56.9233925Z triton_convolution2d_343 0.9431 ms 29.0% 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 2025-09-07T09:48:56.9236669Z triton_convolution2d_344 1.0301 ms 26.5% 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 2025-09-07T09:48:56.9239444Z triton_convolution2d_341 1.7664 ms 15.5% 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 2025-09-07T09:48:56.9241620Z SingleProcess AUTOTUNE benchmarking takes 0.3113 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:57.2216426Z Autotune Choices Stats: 2025-09-07T09:48:57.2219367Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.1157120019197464, "best_triton_pos": 1, "best_triton_time": 0.18432000279426575, "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=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:48:57.2248690Z AUTOTUNE convolution(4x32x176x176, 64x32x5x5) 2025-09-07T09:48:57.2249390Z strides: [991232, 30976, 176, 1], [800, 25, 5, 1] 2025-09-07T09:48:57.2250017Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:57.2251047Z convolution 0.1157 ms 100.0% 2025-09-07T09:48:57.2252652Z triton_convolution2d_19 0.1843 ms 62.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:57.2255844Z triton_convolution2d_16 0.2048 ms 56.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:57.2258490Z triton_convolution2d_14 0.2161 ms 53.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:57.2261154Z triton_convolution2d_13 0.2611 ms 44.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:57.2263952Z triton_convolution2d_18 0.2621 ms 44.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:57.2266808Z triton_convolution2d_17 0.5018 ms 23.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:57.2269596Z triton_convolution2d_15 0.5673 ms 20.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:48:57.2271642Z SingleProcess AUTOTUNE benchmarking takes 0.2726 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:57.8095367Z Autotune Choices Stats: 2025-09-07T09:48:57.8099043Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.18943999707698822, "best_triton_pos": 1, "best_triton_time": 0.5089280009269714, "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=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:48:57.8127453Z AUTOTUNE convolution(4x64x176x176, 64x64x5x5) 2025-09-07T09:48:57.8128153Z strides: [1982464, 30976, 176, 1], [1600, 25, 5, 1] 2025-09-07T09:48:57.8128796Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:57.8129391Z convolution 0.1894 ms 100.0% 2025-09-07T09:48:57.8130960Z triton_convolution2d_21 0.5089 ms 37.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:57.8134122Z triton_convolution2d_26 0.5837 ms 32.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:57.8136988Z triton_convolution2d_23 0.7864 ms 24.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:57.8139833Z triton_convolution2d_20 0.9708 ms 19.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:57.8142474Z triton_convolution2d_22 1.2831 ms 14.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:48:57.8145271Z triton_convolution2d_25 1.3302 ms 14.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:57.8148307Z triton_convolution2d_24 1.4838 ms 12.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:57.8150481Z SingleProcess AUTOTUNE benchmarking takes 0.3054 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:58.1248044Z Autotune Choices Stats: 2025-09-07T09:48:58.1251001Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.187391996383667, "best_triton_pos": 1, "best_triton_time": 0.3389439880847931, "best_triton_kernel": "triton_convolution2d_126", "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"} 2025-09-07T09:48:58.1282592Z AUTOTUNE convolution(4x128x176x176, 64x128x3x3) 2025-09-07T09:48:58.1283273Z strides: [3964928, 30976, 176, 1], [1152, 9, 3, 1] 2025-09-07T09:48:58.1283929Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:58.1284470Z convolution 0.1874 ms 100.0% 2025-09-07T09:48:58.1286010Z triton_convolution2d_126 0.3389 ms 55.3% 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 2025-09-07T09:48:58.1288801Z triton_convolution2d_128 0.3410 ms 55.0% 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 2025-09-07T09:48:58.1291564Z triton_convolution2d_131 0.3553 ms 52.7% 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 2025-09-07T09:48:58.1294905Z triton_convolution2d_125 0.4055 ms 46.2% 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 2025-09-07T09:48:58.1297680Z triton_convolution2d_130 0.4536 ms 41.3% 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 2025-09-07T09:48:58.1300477Z triton_convolution2d_129 0.5509 ms 34.0% 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 2025-09-07T09:48:58.1303345Z triton_convolution2d_127 0.9687 ms 19.3% 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 2025-09-07T09:48:58.1305663Z SingleProcess AUTOTUNE benchmarking takes 0.2998 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:58.7014598Z Autotune Choices Stats: 2025-09-07T09:48:58.7017753Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.131071999669075, "best_triton_pos": 1, "best_triton_time": 0.317440003156662, "best_triton_kernel": "triton_convolution2d_347", "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"} 2025-09-07T09:48:58.7049947Z AUTOTUNE convolution(4x128x88x88, 256x128x3x3) 2025-09-07T09:48:58.7050663Z strides: [991232, 7744, 88, 1], [1152, 9, 3, 1] 2025-09-07T09:48:58.7051284Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:58.7051836Z convolution 0.1311 ms 100.0% 2025-09-07T09:48:58.7053875Z triton_convolution2d_347 0.3174 ms 41.3% 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 2025-09-07T09:48:58.7057159Z triton_convolution2d_352 0.3389 ms 38.7% 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 2025-09-07T09:48:58.7060007Z triton_convolution2d_349 0.4465 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 2025-09-07T09:48:58.7062877Z triton_convolution2d_350 0.5335 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 2025-09-07T09:48:58.7065842Z triton_convolution2d_346 0.5673 ms 23.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:48:58.7068544Z triton_convolution2d_351 0.7496 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:58.7071291Z triton_convolution2d_348 0.9134 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 2025-09-07T09:48:58.7073414Z SingleProcess AUTOTUNE benchmarking takes 0.2969 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:48:59.3018136Z Autotune Choices Stats: 2025-09-07T09:48:59.3021723Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.21913599967956543, "best_triton_pos": 1, "best_triton_time": 0.6287360191345215, "best_triton_kernel": "triton_convolution2d_354", "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"} 2025-09-07T09:48:59.3051912Z AUTOTUNE convolution(4x256x88x88, 256x256x3x3) 2025-09-07T09:48:59.3052591Z strides: [1982464, 7744, 88, 1], [2304, 9, 3, 1] 2025-09-07T09:48:59.3053572Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:59.3054115Z convolution 0.2191 ms 100.0% 2025-09-07T09:48:59.3055744Z triton_convolution2d_354 0.6287 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 2025-09-07T09:48:59.3058545Z triton_convolution2d_359 0.6902 ms 31.8% 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 2025-09-07T09:48:59.3061332Z triton_convolution2d_356 0.8673 ms 25.3% 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 2025-09-07T09:48:59.3064177Z triton_convolution2d_357 1.0936 ms 20.0% 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 2025-09-07T09:48:59.3067093Z triton_convolution2d_353 1.1930 ms 18.4% 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 2025-09-07T09:48:59.3069936Z triton_convolution2d_358 1.4459 ms 15.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:59.3073162Z triton_convolution2d_355 1.8391 ms 11.9% 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 2025-09-07T09:48:59.3075425Z SingleProcess AUTOTUNE benchmarking takes 0.3167 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:48:59.5468595Z Autotune Choices Stats: 2025-09-07T09:48:59.5471604Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.060416001826524734, "best_triton_pos": 1, "best_triton_time": 0.08294399827718735, "best_triton_kernel": "triton_convolution2d_33", "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"} 2025-09-07T09:48:59.5502275Z AUTOTUNE convolution(4x64x88x88, 128x64x3x3) 2025-09-07T09:48:59.5502929Z strides: [495616, 7744, 88, 1], [576, 9, 3, 1] 2025-09-07T09:48:59.5503546Z dtypes: torch.float16, torch.float16 2025-09-07T09:48:59.5504076Z convolution 0.0604 ms 100.0% 2025-09-07T09:48:59.5505768Z triton_convolution2d_33 0.0829 ms 72.8% 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 2025-09-07T09:48:59.5508483Z triton_convolution2d_30 0.0973 ms 62.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:59.5511187Z triton_convolution2d_31 0.1014 ms 59.6% 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 2025-09-07T09:48:59.5513969Z triton_convolution2d_28 0.1055 ms 57.3% 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 2025-09-07T09:48:59.5517152Z triton_convolution2d_27 0.1106 ms 54.6% 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 2025-09-07T09:48:59.5519862Z triton_convolution2d_32 0.1352 ms 44.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:48:59.5522614Z triton_convolution2d_29 0.2683 ms 22.5% 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 2025-09-07T09:48:59.5524765Z SingleProcess AUTOTUNE benchmarking takes 0.1949 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:00.1052778Z Autotune Choices Stats: 2025-09-07T09:49:00.1056100Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.08806400001049042, "best_triton_pos": 1, "best_triton_time": 0.19660800695419312, "best_triton_kernel": "triton_convolution2d_40", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:49:00.1086466Z AUTOTUNE convolution(4x128x88x88, 128x128x3x3) 2025-09-07T09:49:00.1087133Z strides: [991232, 7744, 88, 1], [1152, 9, 3, 1] 2025-09-07T09:49:00.1087741Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:00.1088318Z convolution 0.0881 ms 100.0% 2025-09-07T09:49:00.1089939Z triton_convolution2d_40 0.1966 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 2025-09-07T09:49:00.1093315Z triton_convolution2d_34 0.2130 ms 41.3% 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 2025-09-07T09:49:00.1095993Z triton_convolution2d_35 0.2140 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 2025-09-07T09:49:00.1098725Z triton_convolution2d_38 0.2406 ms 36.6% 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 2025-09-07T09:49:00.1101549Z triton_convolution2d_37 0.2560 ms 34.4% 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 2025-09-07T09:49:00.1104388Z triton_convolution2d_39 0.3041 ms 29.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:00.1107234Z triton_convolution2d_36 0.5509 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 2025-09-07T09:49:00.1109387Z SingleProcess AUTOTUNE benchmarking takes 0.2744 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:00.4121017Z Autotune Choices Stats: 2025-09-07T09:49:00.4124055Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.13926400244235992, "best_triton_pos": 1, "best_triton_time": 0.419840008020401, "best_triton_kernel": "triton_convolution2d_111", "best_triton_kernel_desc": "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"} 2025-09-07T09:49:00.4155570Z AUTOTUNE convolution(4x256x88x88, 128x256x3x3) 2025-09-07T09:49:00.4156663Z strides: [1982464, 7744, 88, 1], [2304, 9, 3, 1] 2025-09-07T09:49:00.4157286Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:00.4157851Z convolution 0.1393 ms 100.0% 2025-09-07T09:49:00.4159479Z triton_convolution2d_111 0.4198 ms 33.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:00.4162296Z triton_convolution2d_112 0.4209 ms 33.1% 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 2025-09-07T09:49:00.4165114Z triton_convolution2d_117 0.4219 ms 33.0% 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 2025-09-07T09:49:00.4168002Z triton_convolution2d_114 0.5089 ms 27.4% 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 2025-09-07T09:49:00.4170836Z triton_convolution2d_115 0.5663 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 2025-09-07T09:49:00.4174030Z triton_convolution2d_116 0.5693 ms 24.5% 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 2025-09-07T09:49:00.4176912Z triton_convolution2d_113 1.1018 ms 12.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:49:00.4179541Z SingleProcess AUTOTUNE benchmarking takes 0.2913 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:01.0049701Z Autotune Choices Stats: 2025-09-07T09:49:01.0053286Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.1382399946451187, "best_triton_pos": 1, "best_triton_time": 0.4044800102710724, "best_triton_kernel": "triton_convolution2d_368", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:49:01.0113974Z AUTOTUNE convolution(4x256x44x44, 512x256x3x3) 2025-09-07T09:49:01.0114703Z strides: [507904, 1984, 44, 1], [2304, 9, 3, 1] 2025-09-07T09:49:01.0115340Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:01.0115930Z convolution 0.1382 ms 100.0% 2025-09-07T09:49:01.0117688Z triton_convolution2d_368 0.4045 ms 34.2% 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 2025-09-07T09:49:01.0120623Z triton_convolution2d_373 0.4106 ms 33.7% 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 2025-09-07T09:49:01.0123565Z triton_convolution2d_370 0.5325 ms 26.0% 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 2025-09-07T09:49:01.0126535Z triton_convolution2d_371 0.6113 ms 22.6% 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 2025-09-07T09:49:01.0129463Z triton_convolution2d_367 0.7485 ms 18.5% 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 2025-09-07T09:49:01.0132944Z triton_convolution2d_369 0.7967 ms 17.4% 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 2025-09-07T09:49:01.0135895Z triton_convolution2d_372 0.8233 ms 16.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:01.0138208Z SingleProcess AUTOTUNE benchmarking takes 0.3241 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:01.7753274Z Autotune Choices Stats: 2025-09-07T09:49:01.7756405Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2252800017595291, "best_triton_pos": 1, "best_triton_time": 0.8069120049476624, "best_triton_kernel": "triton_convolution2d_380", "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"} 2025-09-07T09:49:01.7816111Z AUTOTUNE convolution(4x512x44x44, 512x512x3x3) 2025-09-07T09:49:01.7816834Z strides: [991232, 1936, 44, 1], [4608, 9, 3, 1] 2025-09-07T09:49:01.7817471Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:01.7818044Z convolution 0.2253 ms 100.0% 2025-09-07T09:49:01.7819735Z triton_convolution2d_380 0.8069 ms 27.9% 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 2025-09-07T09:49:01.7822619Z triton_convolution2d_375 0.8284 ms 27.2% 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 2025-09-07T09:49:01.7826056Z triton_convolution2d_377 1.0834 ms 20.8% 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 2025-09-07T09:49:01.7828825Z triton_convolution2d_378 1.3025 ms 17.3% 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 2025-09-07T09:49:01.7831693Z triton_convolution2d_376 1.5094 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 2025-09-07T09:49:01.7834312Z triton_convolution2d_374 1.5104 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:01.7837320Z triton_convolution2d_379 1.6589 ms 13.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:01.7839525Z SingleProcess AUTOTUNE benchmarking takes 0.3432 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:49:02.4547300Z Autotune Choices Stats: 2025-09-07T09:49:02.4550426Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.12800000607967377, "best_triton_pos": 1, "best_triton_time": 0.40959998965263367, "best_triton_kernel": "triton_convolution2d_442", "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"} 2025-09-07T09:49:02.4587051Z AUTOTUNE convolution(4x256x44x44, 512x256x3x3) 2025-09-07T09:49:02.4587777Z strides: [495616, 1936, 44, 1], [2304, 9, 3, 1] 2025-09-07T09:49:02.4588414Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:02.4588993Z convolution 0.1280 ms 100.0% 2025-09-07T09:49:02.4591151Z triton_convolution2d_442 0.4096 ms 31.3% 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 2025-09-07T09:49:02.4593941Z triton_convolution2d_437 0.4127 ms 31.0% 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 2025-09-07T09:49:02.4596804Z triton_convolution2d_439 0.5386 ms 23.8% 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 2025-09-07T09:49:02.4599635Z triton_convolution2d_440 0.6205 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 2025-09-07T09:49:02.4602425Z triton_convolution2d_436 0.7537 ms 17.0% 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 2025-09-07T09:49:02.4605243Z triton_convolution2d_438 0.7649 ms 16.7% 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 2025-09-07T09:49:02.4608043Z triton_convolution2d_441 0.8192 ms 15.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:02.4610209Z SingleProcess AUTOTUNE benchmarking takes 0.2982 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:49:02.7117418Z Autotune Choices Stats: 2025-09-07T09:49:02.7118816Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_318", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.130048006772995, "best_triton_pos": 0} 2025-09-07T09:49:02.7153353Z AUTOTUNE convolution(4x32x352x352, 5x32x3x3) 2025-09-07T09:49:02.7153764Z strides: [3964928, 123904, 352, 1], [288, 9, 3, 1] 2025-09-07T09:49:02.7154143Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:02.7155062Z triton_convolution2d_318 0.1300 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:02.7156573Z triton_convolution2d_316 0.1434 ms 90.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:02.7158097Z triton_convolution2d_317 0.1444 ms 90.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:02.7159577Z triton_convolution2d_314 0.1833 ms 70.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:02.7160481Z convolution 0.1905 ms 68.3% 2025-09-07T09:49:02.7161363Z triton_convolution2d_315 0.2161 ms 60.2% 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 2025-09-07T09:49:02.7162852Z triton_convolution2d_313 0.2243 ms 58.0% 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 2025-09-07T09:49:02.7164364Z SingleProcess AUTOTUNE benchmarking takes 0.2177 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T09:49:03.2473643Z Autotune Choices Stats: 2025-09-07T09:49:03.2475320Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.05939200147986412, "best_triton_pos": 1, "best_triton_time": 0.11366400122642517, "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"} 2025-09-07T09:49:03.2508903Z AUTOTUNE convolution(4x128x44x44, 256x128x3x3) 2025-09-07T09:49:03.2509290Z strides: [247808, 1936, 44, 1], [1152, 9, 3, 1] 2025-09-07T09:49:03.2509656Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:03.2509983Z convolution 0.0594 ms 100.0% 2025-09-07T09:49:03.2510888Z triton_convolution2d_42 0.1137 ms 52.3% 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 2025-09-07T09:49:03.2512370Z triton_convolution2d_47 0.1300 ms 45.7% 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 2025-09-07T09:49:03.2513853Z triton_convolution2d_44 0.1772 ms 33.5% 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 2025-09-07T09:49:03.2515322Z triton_convolution2d_45 0.1772 ms 33.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:03.2517090Z triton_convolution2d_41 0.1812 ms 32.8% 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 2025-09-07T09:49:03.2518560Z triton_convolution2d_43 0.2591 ms 22.9% 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 2025-09-07T09:49:03.2520040Z triton_convolution2d_46 0.2703 ms 22.0% 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 2025-09-07T09:49:03.2521210Z SingleProcess AUTOTUNE benchmarking takes 0.2411 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:49:03.8151578Z Autotune Choices Stats: 2025-09-07T09:49:03.8153264Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.09216000139713287, "best_triton_pos": 1, "best_triton_time": 0.2170879989862442, "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"} 2025-09-07T09:49:03.8186592Z AUTOTUNE convolution(4x256x44x44, 256x256x3x3) 2025-09-07T09:49:03.8186956Z strides: [495616, 1936, 44, 1], [2304, 9, 3, 1] 2025-09-07T09:49:03.8187312Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:03.8187629Z convolution 0.0922 ms 100.0% 2025-09-07T09:49:03.8188512Z triton_convolution2d_49 0.2171 ms 42.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:03.8190004Z triton_convolution2d_54 0.2632 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 2025-09-07T09:49:03.8191760Z triton_convolution2d_51 0.3318 ms 27.8% 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 2025-09-07T09:49:03.8193250Z triton_convolution2d_48 0.3553 ms 25.9% 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 2025-09-07T09:49:03.8194719Z triton_convolution2d_52 0.3625 ms 25.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:03.8196202Z triton_convolution2d_50 0.5038 ms 18.3% 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 2025-09-07T09:49:03.8197686Z triton_convolution2d_53 0.5171 ms 17.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:03.8198847Z SingleProcess AUTOTUNE benchmarking takes 0.2843 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:04.1316599Z Autotune Choices Stats: 2025-09-07T09:49:04.1318237Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.15462400019168854, "best_triton_pos": 1, "best_triton_time": 0.4270080029964447, "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"} 2025-09-07T09:49:04.1352388Z AUTOTUNE convolution(4x512x44x44, 256x512x3x3) 2025-09-07T09:49:04.1352813Z strides: [991232, 1936, 44, 1], [4608, 9, 3, 1] 2025-09-07T09:49:04.1353195Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:04.1353511Z convolution 0.1546 ms 100.0% 2025-09-07T09:49:04.1354402Z triton_convolution2d_98 0.4270 ms 36.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:04.1362922Z triton_convolution2d_103 0.5233 ms 29.5% 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 2025-09-07T09:49:04.1364464Z triton_convolution2d_100 0.6892 ms 22.4% 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 2025-09-07T09:49:04.1365991Z triton_convolution2d_97 0.7025 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 2025-09-07T09:49:04.1367465Z triton_convolution2d_101 0.7434 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:04.1368935Z triton_convolution2d_99 0.9974 ms 15.5% 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 2025-09-07T09:49:04.1370420Z triton_convolution2d_102 1.0516 ms 14.7% 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 2025-09-07T09:49:04.1371605Z SingleProcess AUTOTUNE benchmarking takes 0.3009 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:04.5634235Z Autotune Choices Stats: 2025-09-07T09:49:04.5635643Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_158", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.13209599256515503, "best_triton_pos": 0} 2025-09-07T09:49:04.5671727Z AUTOTUNE convolution(4x32x352x352, 4x32x3x3) 2025-09-07T09:49:04.5672113Z strides: [3964928, 123904, 352, 1], [288, 9, 3, 1] 2025-09-07T09:49:04.5672463Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:04.5673388Z triton_convolution2d_158 0.1321 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:04.5674911Z triton_convolution2d_156 0.1423 ms 92.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:04.5676394Z triton_convolution2d_157 0.1423 ms 92.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:04.5677878Z triton_convolution2d_154 0.1823 ms 72.5% 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=2, num_warps=4 2025-09-07T09:49:04.5678789Z convolution 0.1905 ms 69.4% 2025-09-07T09:49:04.5679669Z triton_convolution2d_155 0.2161 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 2025-09-07T09:49:04.5681376Z triton_convolution2d_153 0.2232 ms 59.2% 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 2025-09-07T09:49:04.5682538Z SingleProcess AUTOTUNE benchmarking takes 0.2092 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:49:05.1456932Z Autotune Choices Stats: 2025-09-07T09:49:05.1458608Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.06963200122117996, "best_triton_pos": 1, "best_triton_time": 0.1382399946451187, "best_triton_kernel": "triton_convolution2d_61", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:49:05.1493594Z AUTOTUNE convolution(4x256x22x22, 512x256x3x3) 2025-09-07T09:49:05.1494008Z strides: [123904, 484, 22, 1], [2304, 9, 3, 1] 2025-09-07T09:49:05.1494351Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:05.1494696Z convolution 0.0696 ms 100.0% 2025-09-07T09:49:05.1495562Z triton_convolution2d_61 0.1382 ms 50.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:05.1497047Z triton_convolution2d_58 0.1628 ms 42.8% 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 2025-09-07T09:49:05.1498536Z triton_convolution2d_56 0.1751 ms 39.8% 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 2025-09-07T09:49:05.1500016Z triton_convolution2d_59 0.1782 ms 39.1% 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 2025-09-07T09:49:05.1501786Z triton_convolution2d_60 0.2406 ms 28.9% 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 2025-09-07T09:49:05.1503272Z triton_convolution2d_57 0.2499 ms 27.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:49:05.1504821Z triton_convolution2d_55 0.2632 ms 26.5% 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 2025-09-07T09:49:05.1506004Z SingleProcess AUTOTUNE benchmarking takes 0.2526 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:05.7145904Z Autotune Choices Stats: 2025-09-07T09:49:05.7147613Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.10751999914646149, "best_triton_pos": 1, "best_triton_time": 0.2682879865169525, "best_triton_kernel": "triton_convolution2d_68", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:49:05.7181952Z AUTOTUNE convolution(4x512x22x22, 512x512x3x3) 2025-09-07T09:49:05.7182373Z strides: [247808, 484, 22, 1], [4608, 9, 3, 1] 2025-09-07T09:49:05.7182726Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:05.7183055Z convolution 0.1075 ms 100.0% 2025-09-07T09:49:05.7183922Z triton_convolution2d_68 0.2683 ms 40.1% 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 2025-09-07T09:49:05.7185841Z triton_convolution2d_65 0.3195 ms 33.7% 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 2025-09-07T09:49:05.7187329Z triton_convolution2d_63 0.3410 ms 31.5% 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 2025-09-07T09:49:05.7188803Z triton_convolution2d_66 0.3523 ms 30.5% 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 2025-09-07T09:49:05.7190279Z triton_convolution2d_67 0.4751 ms 22.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:05.7191773Z triton_convolution2d_64 0.4864 ms 22.1% 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 2025-09-07T09:49:05.7193267Z triton_convolution2d_62 0.5325 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 2025-09-07T09:49:05.7194438Z SingleProcess AUTOTUNE benchmarking takes 0.2861 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:06.2410246Z Autotune Choices Stats: 2025-09-07T09:49:06.2411926Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.17510400712490082, "best_triton_pos": 1, "best_triton_time": 0.5232639908790588, "best_triton_kernel": "triton_convolution2d_96", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:49:06.2450269Z AUTOTUNE convolution(4x1024x22x22, 512x1024x3x3) 2025-09-07T09:49:06.2450662Z strides: [495616, 484, 22, 1], [9216, 9, 3, 1] 2025-09-07T09:49:06.2451010Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:06.2451314Z convolution 0.1751 ms 100.0% 2025-09-07T09:49:06.2452200Z triton_convolution2d_96 0.5233 ms 33.5% 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 2025-09-07T09:49:06.2453790Z triton_convolution2d_94 0.6738 ms 26.0% 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 2025-09-07T09:49:06.2455272Z triton_convolution2d_91 0.6779 ms 25.8% 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 2025-09-07T09:49:06.2456756Z triton_convolution2d_93 0.6932 ms 25.3% 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 2025-09-07T09:49:06.2458233Z triton_convolution2d_95 0.9513 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 2025-09-07T09:49:06.2459705Z triton_convolution2d_92 0.9687 ms 18.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:49:06.2461181Z triton_convolution2d_90 1.0742 ms 16.3% 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 2025-09-07T09:49:06.2462527Z SingleProcess AUTOTUNE benchmarking takes 0.2981 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:06.5779143Z Autotune Choices Stats: 2025-09-07T09:49:06.5780778Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.062463998794555664, "best_triton_pos": 1, "best_triton_time": 0.1945600062608719, "best_triton_kernel": "triton_convolution2d_73", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:49:06.5815878Z AUTOTUNE convolution(4x512x11x11, 512x512x3x3) 2025-09-07T09:49:06.5816290Z strides: [61952, 121, 11, 1], [4608, 9, 3, 1] 2025-09-07T09:49:06.5816669Z dtypes: torch.float16, torch.float16 2025-09-07T09:49:06.5816974Z convolution 0.0625 ms 100.0% 2025-09-07T09:49:06.5817856Z triton_convolution2d_73 0.1946 ms 32.1% 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 2025-09-07T09:49:06.5819341Z triton_convolution2d_75 0.2591 ms 24.1% 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 2025-09-07T09:49:06.5820831Z triton_convolution2d_72 0.3062 ms 20.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:49:06.5822308Z triton_convolution2d_71 0.3113 ms 20.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=512, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:49:06.5824060Z triton_convolution2d_70 0.3267 ms 19.1% 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 2025-09-07T09:49:06.5825625Z triton_convolution2d_74 0.4239 ms 14.7% 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 2025-09-07T09:49:06.5827098Z triton_convolution2d_69 0.5048 ms 12.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:49:06.5828254Z SingleProcess AUTOTUNE benchmarking takes 0.2789 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:49:39.6518132Z W0907 09:49:39.650000 36357 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:49:53.3001455Z pass 2025-09-07T09:49:57.7323882Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:49:57.7325294Z import pynvml # type: ignore[import] 2025-09-07T09:50:00.4265490Z 2025-09-07T09:50:02.2382703Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:50:02.2383336Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:50:02.2383899Z cuda train alexnet 2025-09-07T09:50:12.9276867Z Autotune Choices Stats: 2025-09-07T09:50:12.9278642Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_42", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.07782399654388428, "best_triton_pos": 0} 2025-09-07T09:50:12.9319159Z AUTOTUNE mm(4x9216, 9216x4096) 2025-09-07T09:50:12.9319567Z strides: [9216, 1], [1, 9216] 2025-09-07T09:50:12.9319873Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:12.9320669Z triton_mm_42 0.0778 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 2025-09-07T09:50:12.9321861Z triton_mm_38 0.0788 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:12.9322582Z mm 0.0819 ms 95.0% 2025-09-07T09:50:12.9323271Z triton_mm_46 0.0819 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:12.9324456Z triton_mm_50 0.0891 ms 87.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:12.9325636Z triton_mm_35 0.0993 ms 78.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:50:12.9326800Z triton_mm_37 0.1014 ms 76.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:12.9327963Z triton_mm_41 0.1024 ms 76.0% 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 2025-09-07T09:50:12.9329107Z triton_mm_36 0.1044 ms 74.5% 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 2025-09-07T09:50:12.9330282Z triton_mm_45 0.1096 ms 71.0% 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 2025-09-07T09:50:12.9331629Z SingleProcess AUTOTUNE benchmarking takes 0.5064 seconds and 0.3211 seconds precompiling for 18 choices 2025-09-07T09:50:13.5967323Z Autotune Choices Stats: 2025-09-07T09:50:13.5968549Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_59", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.04198399931192398, "best_triton_pos": 0} 2025-09-07T09:50:13.6007071Z AUTOTUNE mm(4x4096, 4096x4096) 2025-09-07T09:50:13.6007424Z strides: [4096, 1], [1, 4096] 2025-09-07T09:50:13.6007720Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:13.6008500Z triton_mm_59 0.0420 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 2025-09-07T09:50:13.6009743Z triton_mm_55 0.0430 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:13.6010923Z triton_mm_63 0.0451 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:13.6011658Z mm 0.0461 ms 91.1% 2025-09-07T09:50:13.6012340Z triton_mm_67 0.0471 ms 89.1% 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 2025-09-07T09:50:13.6013723Z triton_mm_58 0.0512 ms 82.0% 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 2025-09-07T09:50:13.6015208Z triton_mm_52 0.0522 ms 80.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:50:13.6016390Z triton_mm_62 0.0543 ms 77.4% 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 2025-09-07T09:50:13.6017559Z triton_mm_53 0.0553 ms 75.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:13.6018714Z triton_mm_54 0.0553 ms 75.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:13.6019733Z SingleProcess AUTOTUNE benchmarking takes 0.3466 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:50:14.5209617Z Autotune Choices Stats: 2025-09-07T09:50:14.5213216Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.09318400174379349, "best_triton_pos": 1, "best_triton_time": 0.10649599879980087, "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=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:14.5281037Z AUTOTUNE convolution(4x3x224x224, 64x3x11x11) 2025-09-07T09:50:14.5281748Z strides: [150528, 1, 672, 3], [363, 1, 33, 3] 2025-09-07T09:50:14.5282382Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:14.5282962Z convolution 0.0932 ms 100.0% 2025-09-07T09:50:14.5284657Z triton_convolution2d_0 0.1065 ms 87.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:14.5287563Z triton_convolution2d_4 0.1147 ms 81.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.5290932Z triton_convolution2d_3 0.1280 ms 72.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.5294045Z triton_convolution2d_2 0.1659 ms 56.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:14.5296985Z triton_convolution2d_5 0.2007 ms 46.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.5299885Z triton_convolution2d_1 0.3809 ms 24.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:14.5302171Z SingleProcess AUTOTUNE benchmarking takes 0.2488 seconds and 0.0006 seconds precompiling for 7 choices 2025-09-07T09:50:14.6723144Z Autotune Choices Stats: 2025-09-07T09:50:14.6726354Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.048128001391887665, "best_triton_kernel": "triton_convolution2d_10", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:14.6760939Z AUTOTUNE convolution(4x64x27x27, 192x64x5x5) 2025-09-07T09:50:14.6761653Z strides: [46656, 1, 1728, 64], [1600, 1, 320, 64] 2025-09-07T09:50:14.6762303Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:14.6763303Z convolution 0.0225 ms 100.0% 2025-09-07T09:50:14.6765002Z triton_convolution2d_10 0.0481 ms 46.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:14.6767904Z triton_convolution2d_9 0.0717 ms 31.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.6770818Z triton_convolution2d_11 0.0737 ms 30.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.6774085Z triton_convolution2d_12 0.0758 ms 29.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.6777024Z triton_convolution2d_7 0.0891 ms 25.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:14.6779923Z triton_convolution2d_6 0.0922 ms 24.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:14.6782823Z triton_convolution2d_8 0.1485 ms 15.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:14.6785174Z SingleProcess AUTOTUNE benchmarking takes 0.1465 seconds and 0.0007 seconds precompiling for 8 choices 2025-09-07T09:50:14.8486141Z Autotune Choices Stats: 2025-09-07T09:50:14.8500298Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.053247999399900436, "best_triton_kernel": "triton_convolution2d_17", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:14.8525626Z AUTOTUNE convolution(4x192x13x13, 384x192x3x3) 2025-09-07T09:50:14.8526312Z strides: [32448, 1, 2496, 192], [1728, 1, 576, 192] 2025-09-07T09:50:14.8526978Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:14.8527558Z convolution 0.0174 ms 100.0% 2025-09-07T09:50:14.8529235Z triton_convolution2d_17 0.0532 ms 32.7% 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 2025-09-07T09:50:14.8532165Z triton_convolution2d_16 0.0778 ms 22.4% 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 2025-09-07T09:50:14.8535228Z triton_convolution2d_18 0.0799 ms 21.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:14.8538178Z triton_convolution2d_19 0.0799 ms 21.8% 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 2025-09-07T09:50:14.8541044Z triton_convolution2d_14 0.1004 ms 17.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:14.8543898Z triton_convolution2d_13 0.1044 ms 16.7% 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 2025-09-07T09:50:14.8547164Z triton_convolution2d_15 0.1546 ms 11.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:50:14.8549418Z SingleProcess AUTOTUNE benchmarking takes 0.1756 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:15.0898100Z Autotune Choices Stats: 2025-09-07T09:50:15.0901239Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02457600086927414, "best_triton_pos": 1, "best_triton_time": 0.10035199671983719, "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"} 2025-09-07T09:50:15.0968900Z AUTOTUNE convolution(4x384x13x13, 256x384x3x3) 2025-09-07T09:50:15.0969661Z strides: [64896, 1, 4992, 384], [3456, 1, 1152, 384] 2025-09-07T09:50:15.0970350Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:15.0970933Z convolution 0.0246 ms 100.0% 2025-09-07T09:50:15.0972527Z triton_convolution2d_24 0.1004 ms 24.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:15.0975641Z triton_convolution2d_23 0.1454 ms 16.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:15.0978466Z triton_convolution2d_25 0.1526 ms 16.1% 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 2025-09-07T09:50:15.0981634Z triton_convolution2d_26 0.1577 ms 15.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:15.0984351Z triton_convolution2d_21 0.1987 ms 12.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:15.0987282Z triton_convolution2d_20 0.2007 ms 12.2% 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 2025-09-07T09:50:15.0990042Z triton_convolution2d_22 0.3000 ms 8.2% 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 2025-09-07T09:50:15.0992193Z SingleProcess AUTOTUNE benchmarking takes 0.2433 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:50:15.3105063Z Autotune Choices Stats: 2025-09-07T09:50:15.3108334Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.06758400052785873, "best_triton_kernel": "triton_convolution2d_31", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:50:15.3180976Z AUTOTUNE convolution(4x256x13x13, 256x256x3x3) 2025-09-07T09:50:15.3181698Z strides: [43264, 1, 3328, 256], [2304, 1, 768, 256] 2025-09-07T09:50:15.3182289Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:15.3182794Z convolution 0.0195 ms 100.0% 2025-09-07T09:50:15.3184045Z triton_convolution2d_31 0.0676 ms 28.8% 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 2025-09-07T09:50:15.3186025Z triton_convolution2d_30 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 2025-09-07T09:50:15.3187900Z triton_convolution2d_32 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 2025-09-07T09:50:15.3189384Z triton_convolution2d_33 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 2025-09-07T09:50:15.3190868Z triton_convolution2d_28 0.1300 ms 15.0% 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 2025-09-07T09:50:15.3192354Z triton_convolution2d_27 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:15.3193825Z triton_convolution2d_29 0.2017 ms 9.6% 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 2025-09-07T09:50:15.3194994Z SingleProcess AUTOTUNE benchmarking takes 0.2201 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:50:15.8222574Z Autotune Choices Stats: 2025-09-07T09:50:15.8223795Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_76", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.025599999353289604, "best_triton_pos": 0} 2025-09-07T09:50:15.8294455Z AUTOTUNE addmm(4x1000, 4x4096, 4096x1000) 2025-09-07T09:50:15.8295117Z strides: [0, 1], [4096, 1], [1, 4096] 2025-09-07T09:50:15.8295484Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:50:15.8296300Z triton_mm_76 0.0256 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 2025-09-07T09:50:15.8297491Z triton_mm_80 0.0328 ms 78.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:15.8298657Z triton_mm_71 0.0358 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 2025-09-07T09:50:15.8299819Z triton_mm_84 0.0369 ms 69.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:15.8300987Z triton_mm_72 0.0379 ms 67.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:15.8302156Z triton_mm_69 0.0410 ms 62.5% 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 2025-09-07T09:50:15.8303315Z triton_mm_70 0.0410 ms 62.5% 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 2025-09-07T09:50:15.8304460Z triton_mm_75 0.0430 ms 59.5% 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 2025-09-07T09:50:15.8305879Z triton_mm_79 0.0430 ms 59.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:15.8307043Z triton_mm_82 0.0471 ms 54.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:15.8308059Z SingleProcess AUTOTUNE benchmarking takes 0.5100 seconds and 0.0005 seconds precompiling for 19 choices 2025-09-07T09:50:24.3436304Z Autotune Choices Stats: 2025-09-07T09:50:24.3438504Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_168", "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": 0.05632000043988228, "best_triton_pos": 0} 2025-09-07T09:50:24.3480876Z AUTOTUNE mm(4096x4, 4x9216) 2025-09-07T09:50:24.3481428Z strides: [1, 4096], [9216, 1] 2025-09-07T09:50:24.3482013Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:24.3483365Z triton_mm_168 0.0563 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 2025-09-07T09:50:24.3485548Z triton_mm_169 0.0563 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 2025-09-07T09:50:24.3487658Z triton_mm_170 0.0563 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 2025-09-07T09:50:24.3489776Z triton_mm_175 0.0563 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:24.3491885Z triton_mm_177 0.0563 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 2025-09-07T09:50:24.3494991Z triton_mm_172 0.0573 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:24.3497156Z triton_mm_173 0.0573 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:24.3499289Z triton_mm_174 0.0573 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:24.3501611Z triton_mm_176 0.0573 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:24.3503994Z triton_mm_178 0.0573 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:24.3506164Z SingleProcess AUTOTUNE benchmarking takes 0.3076 seconds and 0.0006 seconds precompiling for 17 choices 2025-09-07T09:50:24.8831729Z Autotune Choices Stats: 2025-09-07T09:50:24.8832958Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_135", "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": 0.028672000393271446, "best_triton_pos": 0} 2025-09-07T09:50:24.8877149Z AUTOTUNE mm(4096x4, 4x4096) 2025-09-07T09:50:24.8877477Z strides: [1, 4096], [4096, 1] 2025-09-07T09:50:24.8877790Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:24.8878549Z triton_mm_135 0.0287 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 2025-09-07T09:50:24.8880134Z triton_mm_136 0.0287 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 2025-09-07T09:50:24.8881327Z triton_mm_137 0.0287 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 2025-09-07T09:50:24.8882510Z triton_mm_139 0.0287 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 2025-09-07T09:50:24.8883686Z triton_mm_141 0.0287 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:24.8884867Z triton_mm_140 0.0297 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:24.8886043Z triton_mm_142 0.0297 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:24.8887211Z triton_mm_143 0.0297 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:24.8888391Z triton_mm_144 0.0297 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:24.8889574Z triton_mm_145 0.0297 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:24.8890605Z SingleProcess AUTOTUNE benchmarking takes 0.2530 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:50:25.3477751Z Autotune Choices Stats: 2025-09-07T09:50:25.3479390Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_102", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:50:25.3520249Z AUTOTUNE mm(1000x4, 4x4096) 2025-09-07T09:50:25.3520573Z strides: [1, 1000], [4096, 1] 2025-09-07T09:50:25.3520877Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:25.3521632Z triton_mm_102 0.0123 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 2025-09-07T09:50:25.3522830Z triton_mm_103 0.0123 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 2025-09-07T09:50:25.3524038Z triton_mm_104 0.0123 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 2025-09-07T09:50:25.3525231Z triton_mm_105 0.0123 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 2025-09-07T09:50:25.3526420Z triton_mm_106 0.0123 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 2025-09-07T09:50:25.3527607Z triton_mm_107 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:25.3528797Z triton_mm_108 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:25.3530172Z triton_mm_109 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:25.3531367Z triton_mm_110 0.0123 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 2025-09-07T09:50:25.3532562Z triton_mm_111 0.0123 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 2025-09-07T09:50:25.3533818Z SingleProcess AUTOTUNE benchmarking takes 0.2191 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:50:25.8291180Z Autotune Choices Stats: 2025-09-07T09:50:25.8292394Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_87", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T09:50:25.8333261Z AUTOTUNE mm(4x1000, 1000x4096) 2025-09-07T09:50:25.8333659Z strides: [1000, 1], [4096, 1] 2025-09-07T09:50:25.8333951Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:25.8334709Z triton_mm_87 0.0164 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:25.8335904Z triton_mm_93 0.0164 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 2025-09-07T09:50:25.8337097Z triton_mm_97 0.0164 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:25.8338303Z triton_mm_101 0.0164 ms 100.0% 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=5, num_warps=8 2025-09-07T09:50:25.8339801Z triton_mm_92 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:25.8340974Z triton_mm_96 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:25.8341700Z mm 0.0184 ms 88.9% 2025-09-07T09:50:25.8342382Z triton_mm_95 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:25.8343559Z triton_mm_99 0.0184 ms 88.9% 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=4, num_warps=4 2025-09-07T09:50:25.8344807Z triton_mm_89 0.0195 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:25.8345834Z SingleProcess AUTOTUNE benchmarking takes 0.2560 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:50:26.4025983Z Autotune Choices Stats: 2025-09-07T09:50:26.4027217Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_126", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.04403200000524521, "best_triton_pos": 0} 2025-09-07T09:50:26.4069780Z AUTOTUNE mm(4x4096, 4096x4096) 2025-09-07T09:50:26.4070184Z strides: [4096, 1], [4096, 1] 2025-09-07T09:50:26.4070487Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:26.4071254Z triton_mm_126 0.0440 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 2025-09-07T09:50:26.4072369Z mm 0.0451 ms 97.7% 2025-09-07T09:50:26.4073077Z triton_mm_130 0.0451 ms 97.7% 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 2025-09-07T09:50:26.4074262Z triton_mm_134 0.0461 ms 95.6% 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 2025-09-07T09:50:26.4075426Z triton_mm_120 0.0492 ms 89.6% 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 2025-09-07T09:50:26.4076596Z triton_mm_122 0.0492 ms 89.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:26.4077759Z triton_mm_125 0.0502 ms 87.8% 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 2025-09-07T09:50:26.4078945Z triton_mm_129 0.0522 ms 84.3% 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 2025-09-07T09:50:26.4080119Z triton_mm_132 0.0532 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:26.4081278Z triton_mm_121 0.0543 ms 81.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:26.4082298Z SingleProcess AUTOTUNE benchmarking takes 0.3353 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:50:27.3016184Z Autotune Choices Stats: 2025-09-07T09:50:27.3017856Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_153", "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": 0.07782399654388428, "best_triton_pos": 0} 2025-09-07T09:50:27.3059981Z AUTOTUNE mm(4x4096, 4096x9216) 2025-09-07T09:50:27.3060296Z strides: [4096, 1], [9216, 1] 2025-09-07T09:50:27.3060594Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:27.3061356Z triton_mm_153 0.0778 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 2025-09-07T09:50:27.3062567Z triton_mm_162 0.0778 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 2025-09-07T09:50:27.3063747Z triton_mm_163 0.0778 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 2025-09-07T09:50:27.3065018Z triton_mm_167 0.0778 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 2025-09-07T09:50:27.3065770Z mm 0.0788 ms 98.7% 2025-09-07T09:50:27.3066448Z triton_mm_158 0.0788 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:27.3067621Z triton_mm_159 0.0788 ms 98.7% 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 2025-09-07T09:50:27.3068797Z triton_mm_161 0.0788 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:27.3070195Z triton_mm_165 0.0799 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:27.3071366Z triton_mm_155 0.0840 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:50:27.3072395Z SingleProcess AUTOTUNE benchmarking takes 0.3850 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:50:33.0327098Z pass 2025-09-07T09:50:36.3324606Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:50:36.3326048Z import pynvml # type: ignore[import] 2025-09-07T09:50:39.2238072Z 2025-09-07T09:50:41.9161274Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:50:41.9161662Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:50:41.9161999Z cuda train basic_gnn_edgecnn 2025-09-07T09:50:49.2415273Z Autotune Choices Stats: 2025-09-07T09:50:49.2416499Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_16", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.06758400052785873, "best_triton_pos": 0} 2025-09-07T09:50:49.2462688Z AUTOTUNE mm(200000x128, 128x64) 2025-09-07T09:50:49.2462994Z strides: [128, 1], [1, 128] 2025-09-07T09:50:49.2463296Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:49.2464061Z triton_mm_16 0.0676 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 2025-09-07T09:50:49.2465352Z triton_mm_11 0.0696 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:49.2466861Z triton_mm_13 0.0696 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:49.2468030Z triton_mm_7 0.0707 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:50:49.2469179Z triton_mm_8 0.0707 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:49.2470331Z triton_mm_9 0.0707 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:49.2471495Z triton_mm_10 0.0707 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:49.2472663Z triton_mm_12 0.0707 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:50:49.2473825Z triton_mm_14 0.0717 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:49.2474990Z triton_mm_17 0.0717 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:49.2476003Z SingleProcess AUTOTUNE benchmarking takes 0.3568 seconds and 0.0350 seconds precompiling for 19 choices 2025-09-07T09:50:50.4160917Z Autotune Choices Stats: 2025-09-07T09:50:50.4166632Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_25", "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": 0.04403200000524521, "best_triton_pos": 0} 2025-09-07T09:50:50.4203667Z AUTOTUNE addmm(200000x64, 200000x64, 64x64) 2025-09-07T09:50:50.4204013Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T09:50:50.4204363Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:50:50.4205158Z triton_mm_25 0.0440 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 2025-09-07T09:50:50.4206342Z triton_mm_26 0.0451 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:50.4207503Z triton_mm_29 0.0451 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:50.4208683Z triton_mm_30 0.0451 ms 97.7% 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=4, num_warps=4 2025-09-07T09:50:50.4209851Z triton_mm_35 0.0451 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:50.4211023Z triton_mm_22 0.0471 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:50:50.4212192Z triton_mm_34 0.0471 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:50.4213644Z triton_mm_27 0.0502 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:50.4214392Z bias_addmm 0.0512 ms 86.0% 2025-09-07T09:50:50.4215349Z triton_mm_24 0.0512 ms 86.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:50.4216374Z SingleProcess AUTOTUNE benchmarking takes 0.3645 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:50:51.9227385Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in torch_dynamo_resume_in_scatter_at_93 2025-09-07T09:50:51.9229815Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T09:50:51.9230273Z 2025-09-07T09:50:51.9230280Z 2025-09-07T09:50:55.6996946Z Autotune Choices Stats: 2025-09-07T09:50:55.6998723Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_79", "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": 0.04403200000524521, "best_triton_pos": 0} 2025-09-07T09:50:55.7342762Z AUTOTUNE mm(200000x64, 64x64) 2025-09-07T09:50:55.7343140Z strides: [64, 1], [64, 1] 2025-09-07T09:50:55.7343431Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:55.7344196Z triton_mm_79 0.0440 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 2025-09-07T09:50:55.7345490Z triton_mm_80 0.0440 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 2025-09-07T09:50:55.7346668Z triton_mm_83 0.0440 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 2025-09-07T09:50:55.7348236Z triton_mm_84 0.0440 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 2025-09-07T09:50:55.7349420Z triton_mm_88 0.0440 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 2025-09-07T09:50:55.7350607Z triton_mm_89 0.0440 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:50:55.7351778Z triton_mm_85 0.0471 ms 93.5% 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 2025-09-07T09:50:55.7352945Z triton_mm_73 0.0481 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:50:55.7354113Z triton_mm_81 0.0481 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:50:55.7355274Z triton_mm_86 0.0481 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:50:55.7356297Z SingleProcess AUTOTUNE benchmarking takes 0.3816 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:50:58.5679032Z Autotune Choices Stats: 2025-09-07T09:50:58.5680547Z {"num_choices": 27, "num_triton_choices": 16, "best_kernel": "mm", "best_time": 0.08806400001049042, "best_triton_pos": 11, "best_triton_time": 0.7505919933319092, "best_triton_kernel": "triton_mm_128", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:50:58.5740465Z AUTOTUNE mm(64x200000, 200000x128) 2025-09-07T09:50:58.5741167Z strides: [1, 64], [128, 1] 2025-09-07T09:50:58.5741453Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:58.5741766Z mm 0.0881 ms 100.0% 2025-09-07T09:50:58.5742077Z decompose_k_mm_25_split_13 0.0881 ms 100.0% k_split=25 2025-09-07T09:50:58.5742496Z decompose_k_mm_50_split_14 0.0891 ms 98.9% k_split=50 2025-09-07T09:50:58.5742916Z decompose_k_mm_125_split_15 0.0891 ms 98.9% k_split=125 2025-09-07T09:50:58.5743333Z decompose_k_mm_250_split_16 0.0922 ms 95.6% k_split=250 2025-09-07T09:50:58.5743824Z decompose_k_mm_625_split_17 0.1034 ms 85.1% k_split=625 2025-09-07T09:50:58.5744238Z decompose_k_mm_10_split_12 0.1106 ms 79.6% k_split=10 2025-09-07T09:50:58.5744739Z decompose_k_mm_1250_split_18 0.1341 ms 65.6% k_split=1250 2025-09-07T09:50:58.5745187Z decompose_k_mm_5_split_11 0.1649 ms 53.4% k_split=5 2025-09-07T09:50:58.5745590Z decompose_k_mm_4_split_19 0.1956 ms 45.0% k_split=4 2025-09-07T09:50:58.5746216Z SingleProcess AUTOTUNE benchmarking takes 2.5327 seconds and 0.0003 seconds precompiling for 27 choices 2025-09-07T09:51:01.1467122Z Autotune Choices Stats: 2025-09-07T09:51:01.1470278Z {"num_choices": 26, "num_triton_choices": 15, "best_kernel": "decompose_k_mm_50_split_4", "best_kernel_desc": "k_split=50", "best_time": 0.06451199948787689, "best_triton_pos": 11, "best_triton_time": 1.0956799983978271, "best_triton_kernel": "triton_mm_98", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:51:01.1528469Z AUTOTUNE mm(64x200000, 200000x64) 2025-09-07T09:51:01.1528835Z strides: [1, 64], [64, 1] 2025-09-07T09:51:01.1529126Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:01.1529877Z decompose_k_mm_50_split_4 0.0645 ms 100.0% k_split=50 2025-09-07T09:51:01.1530322Z decompose_k_mm_125_split_5 0.0655 ms 98.4% k_split=125 2025-09-07T09:51:01.1530748Z decompose_k_mm_25_split_3 0.0696 ms 92.6% k_split=25 2025-09-07T09:51:01.1531174Z decompose_k_mm_250_split_6 0.0707 ms 91.3% k_split=250 2025-09-07T09:51:01.1531536Z mm 0.0717 ms 90.0% 2025-09-07T09:51:01.1531829Z decompose_k_mm_625_split_7 0.0748 ms 86.3% k_split=625 2025-09-07T09:51:01.1532257Z decompose_k_mm_1250_split_8 0.0881 ms 73.3% k_split=1250 2025-09-07T09:51:01.1532679Z decompose_k_mm_10_split_2 0.0993 ms 64.9% k_split=10 2025-09-07T09:51:01.1533314Z decompose_k_mm_5_split_1 0.1628 ms 39.6% k_split=5 2025-09-07T09:51:01.1533701Z decompose_k_mm_4_split_9 0.1966 ms 32.8% k_split=4 2025-09-07T09:51:01.1534333Z SingleProcess AUTOTUNE benchmarking takes 2.3810 seconds and 0.0002 seconds precompiling for 26 choices 2025-09-07T09:51:01.7411061Z Autotune Choices Stats: 2025-09-07T09:51:01.7412298Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_111", "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": 0.0655359998345375, "best_triton_pos": 0} 2025-09-07T09:51:01.7459742Z AUTOTUNE mm(200000x64, 64x128) 2025-09-07T09:51:01.7460244Z strides: [64, 1], [128, 1] 2025-09-07T09:51:01.7460679Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:01.7461945Z triton_mm_111 0.0655 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 2025-09-07T09:51:01.7463755Z triton_mm_113 0.0655 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 2025-09-07T09:51:01.7465524Z triton_mm_116 0.0655 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 2025-09-07T09:51:01.7467850Z triton_mm_117 0.0655 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 2025-09-07T09:51:01.7469845Z triton_mm_112 0.0666 ms 98.5% 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 2025-09-07T09:51:01.7471710Z triton_mm_114 0.0666 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:51:01.7473803Z triton_mm_115 0.0666 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:51:01.7476031Z triton_mm_118 0.0666 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:51:01.7478177Z triton_mm_119 0.0666 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:51:01.7480292Z triton_mm_120 0.0666 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=2, num_warps=8 2025-09-07T09:51:01.7482112Z SingleProcess AUTOTUNE benchmarking takes 0.3635 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:51:02.1664711Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpqpyym4nx.py", line 190, in propagate 2025-09-07T09:51:02.1665696Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T09:51:02.1666171Z File "/tmp/jenkins_pyg/tmpqpyym4nx.py", line 141, in _collect 2025-09-07T09:51:02.1666959Z x_i = self._lift(x_i, edge_def, i) 2025-09-07T09:51:02.1667349Z File "/tmp/jenkins_pyg/tmpqpyym4nx.py", line 88, in _lift 2025-09-07T09:51:02.1667776Z return src.index_select(self.node_dim, index) 2025-09-07T09:51:02.1668038Z 2025-09-07T09:51:02.1668050Z 2025-09-07T09:51:02.4300065Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpqpyym4nx.py", line 190, in propagate 2025-09-07T09:51:02.4301017Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T09:51:02.4301479Z File "/tmp/jenkins_pyg/tmpqpyym4nx.py", line 141, in _collect 2025-09-07T09:51:02.4301895Z x_i = self._lift(x_i, edge_def, i) 2025-09-07T09:51:02.4302284Z File "/tmp/jenkins_pyg/tmpqpyym4nx.py", line 88, in _lift 2025-09-07T09:51:02.4302709Z return src.index_select(self.node_dim, index) 2025-09-07T09:51:02.4302958Z 2025-09-07T09:51:02.4302963Z 2025-09-07T09:51:03.0741054Z W0907 09:51:03.073000 43170 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T09:51:05.2454426Z pass 2025-09-07T09:51:08.4171893Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:51:08.4173582Z import pynvml # type: ignore[import] 2025-09-07T09:51:11.1626507Z 2025-09-07T09:51:13.6429801Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:13.6430181Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:51:13.6430504Z cuda train basic_gnn_gcn 2025-09-07T09:51:17.7503331Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T09:51:17.7504842Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T09:51:17.7505935Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:51:17.7506637Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:51:17.7506938Z 2025-09-07T09:51:17.7506950Z 2025-09-07T09:51:21.4169499Z Autotune Choices Stats: 2025-09-07T09:51:21.4170714Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:51:21.4217050Z AUTOTUNE mm(10000x64, 64x64) 2025-09-07T09:51:21.4217382Z strides: [64, 1], [1, 64] 2025-09-07T09:51:21.4217675Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:21.4218446Z triton_mm_4 0.0092 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 2025-09-07T09:51:21.4219637Z triton_mm_6 0.0092 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 2025-09-07T09:51:21.4220804Z triton_mm_7 0.0092 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 2025-09-07T09:51:21.4221964Z triton_mm_8 0.0092 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 2025-09-07T09:51:21.4223131Z triton_mm_11 0.0092 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 2025-09-07T09:51:21.4224739Z triton_mm_12 0.0092 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 2025-09-07T09:51:21.4225937Z triton_mm_13 0.0092 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 2025-09-07T09:51:21.4227105Z triton_mm_14 0.0092 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 2025-09-07T09:51:21.4228285Z triton_mm_17 0.0092 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 2025-09-07T09:51:21.4229458Z triton_mm_0 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:51:21.4230470Z SingleProcess AUTOTUNE benchmarking takes 0.1957 seconds and 2.4839 seconds precompiling for 19 choices 2025-09-07T09:51:22.0362477Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp4t3m646e.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:51:22.0363585Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:51:22.0364091Z File "/tmp/jenkins_pyg/tmp4t3m646e.py", line 188, in propagate 2025-09-07T09:51:22.0364679Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T09:51:22.0365567Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:51:22.0366364Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:51:22.0367144Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:51:22.0367847Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:51:22.0368902Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:51:22.0369630Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:51:22.0370352Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:51:22.0371020Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:51:22.0371674Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:51:22.0372374Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:51:22.0372680Z 2025-09-07T09:51:22.0372685Z 2025-09-07T09:51:23.0668501Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp8l80bjhh.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:51:23.0669653Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:51:23.0670164Z File "/tmp/jenkins_pyg/tmp8l80bjhh.py", line 188, in propagate 2025-09-07T09:51:23.0670774Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T09:51:23.0671658Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:51:23.0672457Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:51:23.0673200Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:51:23.0673920Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:51:23.0674976Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:51:23.0675680Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:51:23.0676397Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:51:23.0677057Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:51:23.0677716Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:51:23.0678396Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:51:23.0678693Z 2025-09-07T09:51:23.0678698Z 2025-09-07T09:51:23.3628123Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp8l80bjhh.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T09:51:23.3629205Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T09:51:23.3629731Z File "/tmp/jenkins_pyg/tmp8l80bjhh.py", line 188, in propagate 2025-09-07T09:51:23.3630324Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T09:51:23.3631228Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:51:23.3632030Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:51:23.3632756Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:51:23.3633471Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:51:23.3634182Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:51:23.3634896Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:51:23.3635592Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:51:23.3636263Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:51:23.3637288Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:51:23.3637992Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:51:23.3638282Z 2025-09-07T09:51:23.3638287Z 2025-09-07T09:51:24.9656598Z Autotune Choices Stats: 2025-09-07T09:51:24.9657816Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_57", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:51:24.9722356Z AUTOTUNE mm(10000x64, 64x64) 2025-09-07T09:51:24.9722674Z strides: [64, 1], [64, 1] 2025-09-07T09:51:24.9722965Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:24.9723764Z triton_mm_57 0.0092 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 2025-09-07T09:51:24.9724938Z triton_mm_58 0.0092 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 2025-09-07T09:51:24.9726111Z triton_mm_59 0.0092 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 2025-09-07T09:51:24.9727274Z triton_mm_62 0.0092 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 2025-09-07T09:51:24.9728436Z triton_mm_63 0.0092 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 2025-09-07T09:51:24.9729959Z triton_mm_64 0.0092 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 2025-09-07T09:51:24.9731137Z triton_mm_65 0.0092 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 2025-09-07T09:51:24.9732318Z triton_mm_68 0.0092 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 2025-09-07T09:51:24.9733739Z triton_mm_51 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:51:24.9734912Z triton_mm_52 0.0102 ms 90.0% 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 2025-09-07T09:51:24.9735931Z SingleProcess AUTOTUNE benchmarking takes 0.2784 seconds and 0.5194 seconds precompiling for 19 choices 2025-09-07T09:51:26.6164590Z Autotune Choices Stats: 2025-09-07T09:51:26.6166097Z {"num_choices": 26, "num_triton_choices": 15, "best_kernel": "mm", "best_time": 0.016383999958634377, "best_triton_pos": 11, "best_triton_time": 0.062463998794555664, "best_triton_kernel": "triton_mm_44", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:51:26.6281981Z AUTOTUNE mm(64x10000, 10000x64) 2025-09-07T09:51:26.6282294Z strides: [1, 64], [64, 1] 2025-09-07T09:51:26.6282568Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:26.6282876Z mm 0.0164 ms 100.0% 2025-09-07T09:51:26.6283180Z decompose_k_mm_40_split_8 0.0174 ms 94.1% k_split=40 2025-09-07T09:51:26.6283614Z decompose_k_mm_50_split_9 0.0174 ms 94.1% k_split=50 2025-09-07T09:51:26.6284007Z decompose_k_mm_10_split_4 0.0195 ms 84.2% k_split=10 2025-09-07T09:51:26.6284413Z decompose_k_mm_16_split_5 0.0195 ms 84.2% k_split=16 2025-09-07T09:51:26.6285151Z decompose_k_mm_20_split_6 0.0195 ms 84.2% k_split=20 2025-09-07T09:51:26.6285563Z decompose_k_mm_25_split_7 0.0195 ms 84.2% k_split=25 2025-09-07T09:51:26.6285949Z decompose_k_mm_5_split_2 0.0205 ms 80.0% k_split=5 2025-09-07T09:51:26.6286348Z decompose_k_mm_8_split_3 0.0205 ms 80.0% k_split=8 2025-09-07T09:51:26.6286746Z decompose_k_mm_4_split_1 0.0225 ms 72.7% k_split=4 2025-09-07T09:51:26.6287379Z SingleProcess AUTOTUNE benchmarking takes 1.4313 seconds and 0.0006 seconds precompiling for 26 choices 2025-09-07T09:51:27.4316595Z W0907 09:51:27.430000 45117 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T09:51:28.5749337Z pass 2025-09-07T09:51:31.8255645Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:51:31.8257069Z import pynvml # type: ignore[import] 2025-09-07T09:51:34.5875955Z 2025-09-07T09:51:37.0625615Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:37.0626019Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:51:37.0626346Z cuda train basic_gnn_gin 2025-09-07T09:51:45.7887524Z Autotune Choices Stats: 2025-09-07T09:51:45.7889644Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_94", "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": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T09:51:45.7939458Z AUTOTUNE addmm(10000x64, 10000x64, 64x64) 2025-09-07T09:51:45.7940613Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T09:51:45.7941247Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:51:45.7942763Z triton_mm_94 0.0092 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 2025-09-07T09:51:45.7945062Z triton_mm_97 0.0092 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 2025-09-07T09:51:45.7947285Z triton_mm_91 0.0102 ms 90.0% 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 2025-09-07T09:51:45.7949494Z triton_mm_93 0.0102 ms 90.0% 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 2025-09-07T09:51:45.7951702Z triton_mm_96 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:51:45.7953890Z triton_mm_98 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:51:45.7956084Z triton_mm_99 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:51:45.7958275Z triton_mm_100 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:51:45.7960487Z triton_mm_101 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:51:45.7962714Z triton_mm_102 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:51:45.7964951Z SingleProcess AUTOTUNE benchmarking takes 0.2341 seconds and 0.0007 seconds precompiling for 20 choices 2025-09-07T09:51:46.4568662Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:51:46.4571017Z pred = mod(*cloned_inputs) 2025-09-07T09:51:46.4572191Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T09:51:46.4573824Z x = self.convs[i](x, edge_index) 2025-09-07T09:51:46.4574523Z File "/tmp/jenkins_pyg/tmpio5oh16l.py", line 225, in forward 2025-09-07T09:51:46.4575359Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T09:51:46.4576170Z File "/tmp/jenkins_pyg/tmpio5oh16l.py", line 182, in propagate 2025-09-07T09:51:46.4577250Z out = self.aggregate(out, dim_size=kwargs.dim_size, ptr=kwargs.ptr, index=kwargs.index) 2025-09-07T09:51:46.4578879Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:51:46.4580395Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:51:46.4581773Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:51:46.4583114Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:51:46.4584421Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T09:51:46.4585822Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T09:51:46.4587558Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:51:46.4588783Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:51:46.4590009Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T09:51:46.4591291Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T09:51:46.4591831Z 2025-09-07T09:51:46.4591838Z 2025-09-07T09:51:49.2751821Z W0907 09:51:49.274000 46157 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:51:51.1077803Z pass 2025-09-07T09:51:54.1856524Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:51:56.9035374Z import pynvml # type: ignore[import] 2025-09-07T09:51:56.9035850Z 2025-09-07T09:51:59.3198004Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:59.3198686Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:51:59.3199269Z cuda train basic_gnn_sage 2025-09-07T09:52:08.4691587Z Autotune Choices Stats: 2025-09-07T09:52:08.4693082Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_91", "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} 2025-09-07T09:52:08.4745711Z AUTOTUNE addmm(10000x64, 10000x64, 64x64) 2025-09-07T09:52:08.4746056Z strides: [64, 1], [64, 1], [1, 64] 2025-09-07T09:52:08.4746410Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:52:08.4747209Z triton_mm_91 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 2025-09-07T09:52:08.4752006Z triton_mm_92 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:52:08.4753381Z triton_mm_93 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:52:08.4754565Z triton_mm_94 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 2025-09-07T09:52:08.4755736Z triton_mm_96 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 2025-09-07T09:52:08.4756902Z triton_mm_97 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 2025-09-07T09:52:08.4758089Z triton_mm_98 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 2025-09-07T09:52:08.4759243Z triton_mm_99 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 2025-09-07T09:52:08.4760417Z triton_mm_100 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 2025-09-07T09:52:08.4761589Z triton_mm_101 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 2025-09-07T09:52:08.4762814Z SingleProcess AUTOTUNE benchmarking takes 0.2050 seconds and 0.0007 seconds precompiling for 19 choices 2025-09-07T09:52:09.2322741Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:52:09.2325122Z pred = mod(*cloned_inputs) 2025-09-07T09:52:09.2326307Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T09:52:09.2327587Z x = self.convs[i](x, edge_index) 2025-09-07T09:52:09.2328280Z File "/tmp/jenkins_pyg/tmpy_29xv2a.py", line 228, in forward 2025-09-07T09:52:09.2329068Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T09:52:09.2329869Z File "/tmp/jenkins_pyg/tmpy_29xv2a.py", line 182, in propagate 2025-09-07T09:52:09.2330951Z out = self.aggregate(out, dim_size=kwargs.dim_size, ptr=kwargs.ptr, index=kwargs.index) 2025-09-07T09:52:09.2332626Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T09:52:09.2334519Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T09:52:09.2335891Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T09:52:09.2337233Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T09:52:09.2338553Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T09:52:09.2339908Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T09:52:09.2341226Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T09:52:09.2342443Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T09:52:09.2343690Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter 2025-09-07T09:52:09.2345083Z count.scatter_add_(0, index, src.new_ones(src.size(dim))) 2025-09-07T09:52:09.2345657Z 2025-09-07T09:52:09.2346069Z 2025-09-07T09:52:12.0722608Z W0907 09:52:12.071000 46905 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:52:13.5337134Z pass 2025-09-07T09:52:16.7153120Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:52:16.7154555Z import pynvml # type: ignore[import] 2025-09-07T09:52:19.3962557Z 2025-09-07T09:52:20.1660064Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:20.1660461Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:20.1660822Z cuda train dcgan 2025-09-07T09:52:28.6098520Z Autotune Choices Stats: 2025-09-07T09:52:28.6099903Z {"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=4, KERNEL_W=4, 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} 2025-09-07T09:52:28.6154840Z AUTOTUNE convolution(4x3x64x64, 64x3x4x4) 2025-09-07T09:52:28.6155659Z strides: [12288, 4096, 64, 1], [48, 16, 4, 1] 2025-09-07T09:52:28.6156418Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:28.6157408Z triton_convolution2d_0 0.0123 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, 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 2025-09-07T09:52:28.6158893Z triton_convolution2d_4 0.0123 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, 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=8 2025-09-07T09:52:28.6160221Z convolution 0.0143 ms 85.7% 2025-09-07T09:52:28.6161097Z triton_convolution2d_3 0.0143 ms 85.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, 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 2025-09-07T09:52:28.6162578Z triton_convolution2d_5 0.0164 ms 75.0% 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=8 2025-09-07T09:52:28.6164047Z triton_convolution2d_1 0.0174 ms 70.6% 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 2025-09-07T09:52:28.6165539Z triton_convolution2d_2 0.0256 ms 48.0% 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 2025-09-07T09:52:28.6166713Z SingleProcess AUTOTUNE benchmarking takes 0.0852 seconds and 0.0010 seconds precompiling for 7 choices 2025-09-07T09:52:29.1901888Z Autotune Choices Stats: 2025-09-07T09:52:29.1903594Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.05427199974656105, "best_triton_kernel": "triton_convolution2d_10", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:52:29.1956357Z AUTOTUNE convolution(4x64x32x32, 128x64x4x4) 2025-09-07T09:52:29.1956796Z strides: [65536, 1024, 32, 1], [1024, 16, 4, 1] 2025-09-07T09:52:29.1957190Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:29.1957499Z convolution 0.0266 ms 100.0% 2025-09-07T09:52:29.1958737Z triton_convolution2d_10 0.0543 ms 49.1% 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 2025-09-07T09:52:29.1960229Z triton_convolution2d_12 0.0758 ms 35.1% 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 2025-09-07T09:52:29.1961706Z triton_convolution2d_7 0.0860 ms 31.0% 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 2025-09-07T09:52:29.1963179Z triton_convolution2d_6 0.0901 ms 29.5% 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 2025-09-07T09:52:29.1964659Z triton_convolution2d_11 0.0901 ms 29.5% 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 2025-09-07T09:52:29.1966134Z triton_convolution2d_9 0.0973 ms 27.4% 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 2025-09-07T09:52:29.1967603Z triton_convolution2d_8 0.4342 ms 6.1% 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 2025-09-07T09:52:29.1968765Z SingleProcess AUTOTUNE benchmarking takes 0.1627 seconds and 0.0056 seconds precompiling for 8 choices 2025-09-07T09:52:29.7043538Z Autotune Choices Stats: 2025-09-07T09:52:29.7045564Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03174399957060814, "best_triton_pos": 1, "best_triton_time": 0.09932799637317657, "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"} 2025-09-07T09:52:29.7093120Z AUTOTUNE convolution(4x128x16x16, 256x128x4x4) 2025-09-07T09:52:29.7093535Z strides: [32768, 256, 16, 1], [2048, 16, 4, 1] 2025-09-07T09:52:29.7093866Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:29.7094186Z convolution 0.0317 ms 100.0% 2025-09-07T09:52:29.7095062Z triton_convolution2d_17 0.0993 ms 32.0% 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 2025-09-07T09:52:29.7096550Z triton_convolution2d_19 0.1536 ms 20.7% 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 2025-09-07T09:52:29.7098028Z triton_convolution2d_14 0.1731 ms 18.3% 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 2025-09-07T09:52:29.7099501Z triton_convolution2d_16 0.1812 ms 17.5% 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 2025-09-07T09:52:29.7100977Z triton_convolution2d_18 0.2755 ms 11.5% 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 2025-09-07T09:52:29.7102430Z triton_convolution2d_13 0.2898 ms 11.0% 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 2025-09-07T09:52:29.7104121Z triton_convolution2d_15 0.3482 ms 9.1% 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 2025-09-07T09:52:29.7105376Z SingleProcess AUTOTUNE benchmarking takes 0.2470 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:30.2284814Z Autotune Choices Stats: 2025-09-07T09:52:30.2286503Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.043007999658584595, "best_triton_pos": 1, "best_triton_time": 0.19046400487422943, "best_triton_kernel": "triton_convolution2d_22", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, 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"} 2025-09-07T09:52:30.2334092Z AUTOTUNE convolution(4x256x8x8, 512x256x4x4) 2025-09-07T09:52:30.2334464Z strides: [16384, 64, 8, 1], [4096, 16, 4, 1] 2025-09-07T09:52:30.2334826Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:30.2335134Z convolution 0.0430 ms 100.0% 2025-09-07T09:52:30.2336012Z triton_convolution2d_22 0.1905 ms 22.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, 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 2025-09-07T09:52:30.2337489Z triton_convolution2d_24 0.1925 ms 22.3% 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 2025-09-07T09:52:30.2338960Z triton_convolution2d_26 0.2775 ms 15.5% 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 2025-09-07T09:52:30.2340711Z triton_convolution2d_21 0.2888 ms 14.9% 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 2025-09-07T09:52:30.2342190Z triton_convolution2d_23 0.3533 ms 12.2% 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 2025-09-07T09:52:30.2343674Z triton_convolution2d_25 0.5652 ms 7.6% 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 2025-09-07T09:52:30.2345202Z triton_convolution2d_20 0.6062 ms 7.1% 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 2025-09-07T09:52:30.2346368Z SingleProcess AUTOTUNE benchmarking takes 0.2745 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:30.5733697Z Autotune Choices Stats: 2025-09-07T09:52:30.5735408Z {"num_choices": 4, "num_triton_choices": 3, "best_kernel": "convolution", "best_time": 0.055296000093221664, "best_triton_pos": 1, "best_triton_time": 0.1013759970664978, "best_triton_kernel": "triton_convolution2d_29", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:52:30.5781657Z AUTOTUNE convolution(4x512x4x4, 1x512x4x4) 2025-09-07T09:52:30.5782034Z strides: [8192, 16, 4, 1], [8192, 16, 4, 1] 2025-09-07T09:52:30.5782363Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:30.5782683Z convolution 0.0553 ms 100.0% 2025-09-07T09:52:30.5790867Z triton_convolution2d_29 0.1014 ms 54.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:52:30.5792651Z triton_convolution2d_27 0.1157 ms 47.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:52:30.5794132Z triton_convolution2d_28 0.1157 ms 47.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=4 2025-09-07T09:52:30.5795299Z SingleProcess AUTOTUNE benchmarking takes 0.0949 seconds and 0.0002 seconds precompiling for 4 choices 2025-09-07T09:52:33.1398137Z pass 2025-09-07T09:52:36.0392867Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:52:36.0394306Z import pynvml # type: ignore[import] 2025-09-07T09:52:38.8257292Z 2025-09-07T09:52:42.2790016Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:52:42.2790400Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:52:42.2790728Z cuda train demucs 2025-09-07T09:53:02.3334689Z E0907 09:53:02.332000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Runtime error during autotuning: 2025-09-07T09:53:02.3336249Z E0907 09:53:02.332000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4. 2025-09-07T09:53:02.3337734Z E0907 09:53:02.332000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Ignoring this choice. 2025-09-07T09:53:02.3338879Z Autotune Choices Stats: 2025-09-07T09:53:02.3339349Z {"num_choices": 2, "num_triton_choices": 0, "best_kernel": "convolution", "best_time": 0.13209599256515503} 2025-09-07T09:53:02.3384578Z AUTOTUNE convolution(4x64x95696, 128x64x1) 2025-09-07T09:53:02.3384996Z strides: [6124544, 95696, 1], [64, 1, 1] 2025-09-07T09:53:02.3385326Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:02.3385641Z convolution 0.1321 ms 100.0% 2025-09-07T09:53:02.3385918Z conv1x1_via_mm inf ms 0.0% 2025-09-07T09:53:02.3386480Z SingleProcess AUTOTUNE benchmarking takes 0.0338 seconds and 0.0002 seconds precompiling for 2 choices 2025-09-07T09:53:02.7053518Z E0907 09:53:02.704000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Runtime error during autotuning: 2025-09-07T09:53:02.7055083Z E0907 09:53:02.704000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4. 2025-09-07T09:53:02.7056587Z E0907 09:53:02.704000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Ignoring this choice. 2025-09-07T09:53:02.7057205Z Autotune Choices Stats: 2025-09-07T09:53:02.7057669Z {"num_choices": 2, "num_triton_choices": 0, "best_kernel": "convolution", "best_time": 0.2017280012369156} 2025-09-07T09:53:02.7146540Z AUTOTUNE convolution(4x128x23923, 256x128x1) 2025-09-07T09:53:02.7146904Z strides: [3062144, 23923, 1], [128, 1, 1] 2025-09-07T09:53:02.7147234Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:02.7147536Z convolution 0.2017 ms 100.0% 2025-09-07T09:53:02.7147827Z conv1x1_via_mm inf ms 0.0% 2025-09-07T09:53:02.7148376Z SingleProcess AUTOTUNE benchmarking takes 0.0430 seconds and 0.0002 seconds precompiling for 2 choices 2025-09-07T09:53:03.0426839Z E0907 09:53:03.042000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Runtime error during autotuning: 2025-09-07T09:53:03.0428771Z E0907 09:53:03.042000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4. 2025-09-07T09:53:03.0430372Z E0907 09:53:03.042000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Ignoring this choice. 2025-09-07T09:53:03.0430968Z Autotune Choices Stats: 2025-09-07T09:53:03.0431455Z {"num_choices": 2, "num_triton_choices": 0, "best_kernel": "convolution", "best_time": 0.11673600226640701} 2025-09-07T09:53:03.0474458Z AUTOTUNE convolution(4x256x5979, 512x256x1) 2025-09-07T09:53:03.0474797Z strides: [1530624, 5979, 1], [256, 1, 1] 2025-09-07T09:53:03.0475126Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:03.0475447Z convolution 0.1167 ms 100.0% 2025-09-07T09:53:03.0475739Z conv1x1_via_mm inf ms 0.0% 2025-09-07T09:53:03.0476282Z SingleProcess AUTOTUNE benchmarking takes 0.0292 seconds and 0.0002 seconds precompiling for 2 choices 2025-09-07T09:53:03.3515673Z E0907 09:53:03.350000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Runtime error during autotuning: 2025-09-07T09:53:03.3518704Z E0907 09:53:03.350000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4. 2025-09-07T09:53:03.3521564Z E0907 09:53:03.350000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Ignoring this choice. 2025-09-07T09:53:03.3522703Z Autotune Choices Stats: 2025-09-07T09:53:03.3523576Z {"num_choices": 2, "num_triton_choices": 0, "best_kernel": "convolution", "best_time": 0.07372800260782242} 2025-09-07T09:53:03.3563038Z AUTOTUNE convolution(4x512x1493, 1024x512x1) 2025-09-07T09:53:03.3563442Z strides: [764416, 1493, 1], [512, 1, 1] 2025-09-07T09:53:03.3564167Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:03.3564491Z convolution 0.0737 ms 100.0% 2025-09-07T09:53:03.3564773Z conv1x1_via_mm inf ms 0.0% 2025-09-07T09:53:03.3565346Z SingleProcess AUTOTUNE benchmarking takes 0.0275 seconds and 0.0002 seconds precompiling for 2 choices 2025-09-07T09:53:03.6570596Z E0907 09:53:03.656000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Runtime error during autotuning: 2025-09-07T09:53:03.6572123Z E0907 09:53:03.656000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4. 2025-09-07T09:53:03.6573828Z E0907 09:53:03.656000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Ignoring this choice. 2025-09-07T09:53:03.6574434Z Autotune Choices Stats: 2025-09-07T09:53:03.6574923Z {"num_choices": 2, "num_triton_choices": 0, "best_kernel": "convolution", "best_time": 0.055296000093221664} 2025-09-07T09:53:03.6620277Z AUTOTUNE convolution(4x1024x372, 2048x1024x1) 2025-09-07T09:53:03.6620675Z strides: [380928, 372, 1], [1024, 1, 1] 2025-09-07T09:53:03.6621020Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:03.6621341Z convolution 0.0553 ms 100.0% 2025-09-07T09:53:03.6621638Z conv1x1_via_mm inf ms 0.0% 2025-09-07T09:53:03.6622198Z SingleProcess AUTOTUNE benchmarking takes 0.0276 seconds and 0.0002 seconds precompiling for 2 choices 2025-09-07T09:53:03.9621127Z E0907 09:53:03.961000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Runtime error during autotuning: 2025-09-07T09:53:03.9622699Z E0907 09:53:03.961000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4. 2025-09-07T09:53:03.9624209Z E0907 09:53:03.961000 48551 site-packages/torch/_inductor/select_algorithm.py:2967] [4/0_1] Ignoring this choice. 2025-09-07T09:53:03.9624898Z Autotune Choices Stats: 2025-09-07T09:53:03.9625735Z {"num_choices": 2, "num_triton_choices": 0, "best_kernel": "convolution", "best_time": 0.05222399905323982} 2025-09-07T09:53:03.9670037Z AUTOTUNE convolution(4x2048x92, 4096x2048x1) 2025-09-07T09:53:03.9670402Z strides: [188416, 92, 1], [2048, 1, 1] 2025-09-07T09:53:03.9670733Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:03.9671039Z convolution 0.0522 ms 100.0% 2025-09-07T09:53:03.9671333Z conv1x1_via_mm inf ms 0.0% 2025-09-07T09:53:03.9671889Z SingleProcess AUTOTUNE benchmarking takes 0.0276 seconds and 0.0002 seconds precompiling for 2 choices 2025-09-07T09:53:16.5342689Z pass 2025-09-07T09:53:19.8980404Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:53:19.8981851Z import pynvml # type: ignore[import] 2025-09-07T09:53:22.7845730Z 2025-09-07T09:53:25.3748529Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:25.3748907Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:53:25.3749239Z cuda train densenet121 2025-09-07T09:54:11.3818263Z Autotune Choices Stats: 2025-09-07T09:54:11.3819631Z {"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": 0.04915200173854828, "best_triton_pos": 0} 2025-09-07T09:54:11.3870674Z AUTOTUNE convolution(4x3x224x224, 64x3x7x7) 2025-09-07T09:54:11.3871083Z strides: [150528, 50176, 224, 1], [147, 49, 7, 1] 2025-09-07T09:54:11.3871429Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:11.3872798Z triton_convolution2d_5 0.0492 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 2025-09-07T09:54:11.3874290Z triton_convolution2d_1 0.0512 ms 96.0% 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 2025-09-07T09:54:11.3875194Z convolution 0.0655 ms 75.0% 2025-09-07T09:54:11.3876060Z triton_convolution2d_0 0.0717 ms 68.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:11.3877523Z triton_convolution2d_3 0.0727 ms 67.6% 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 2025-09-07T09:54:11.3878998Z triton_convolution2d_4 0.0809 ms 60.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:54:11.3880465Z triton_convolution2d_2 0.1167 ms 42.1% 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 2025-09-07T09:54:11.3881623Z SingleProcess AUTOTUNE benchmarking takes 0.1471 seconds and 0.0004 seconds precompiling for 7 choices 2025-09-07T09:54:11.8758096Z Autotune Choices Stats: 2025-09-07T09:54:11.8759456Z {"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} 2025-09-07T09:54:11.8811680Z AUTOTUNE convolution(4x64x56x56, 128x64x1x1) 2025-09-07T09:54:11.8812060Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:54:11.8812739Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:11.8813902Z 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 2025-09-07T09:54:11.8815392Z 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 2025-09-07T09:54:11.8816870Z 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 2025-09-07T09:54:11.8818361Z 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 2025-09-07T09:54:11.8819839Z 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 2025-09-07T09:54:11.8821307Z 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 2025-09-07T09:54:11.8822769Z 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 2025-09-07T09:54:11.8823855Z conv1x1_via_mm 0.0522 ms 21.6% 2025-09-07T09:54:11.8824162Z convolution 0.0543 ms 20.8% 2025-09-07T09:54:11.8824801Z SingleProcess AUTOTUNE benchmarking takes 0.1514 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:12.3325954Z Autotune Choices Stats: 2025-09-07T09:54:12.3327302Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_24", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:54:12.3376349Z AUTOTUNE convolution(4x96x56x56, 128x96x1x1) 2025-09-07T09:54:12.3376730Z strides: [301056, 3136, 56, 1], [96, 1, 1, 1] 2025-09-07T09:54:12.3377079Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.3377974Z triton_convolution2d_24 0.0123 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:12.3379495Z triton_convolution2d_23 0.0133 ms 92.3% 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 2025-09-07T09:54:12.3380981Z triton_convolution2d_25 0.0133 ms 92.3% 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 2025-09-07T09:54:12.3382447Z triton_convolution2d_20 0.0143 ms 85.7% 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 2025-09-07T09:54:12.3383918Z triton_convolution2d_26 0.0143 ms 85.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:12.3385732Z triton_convolution2d_21 0.0154 ms 80.0% 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 2025-09-07T09:54:12.3387220Z triton_convolution2d_22 0.0174 ms 70.6% 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 2025-09-07T09:54:12.3388127Z convolution 0.0205 ms 60.0% 2025-09-07T09:54:12.3388410Z conv1x1_via_mm 0.0584 ms 21.1% 2025-09-07T09:54:12.3388985Z SingleProcess AUTOTUNE benchmarking takes 0.1477 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:12.5174951Z Autotune Choices Stats: 2025-09-07T09:54:12.5176326Z {"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=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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T09:54:12.5225482Z AUTOTUNE convolution(4x128x56x56, 128x128x1x1) 2025-09-07T09:54:12.5225858Z strides: [401408, 3136, 56, 1], [128, 1, 1, 1] 2025-09-07T09:54:12.5226192Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.5227117Z triton_convolution2d_39 0.0133 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 2025-09-07T09:54:12.5228604Z triton_convolution2d_38 0.0143 ms 92.9% 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 2025-09-07T09:54:12.5230085Z triton_convolution2d_37 0.0154 ms 86.7% 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 2025-09-07T09:54:12.5238660Z triton_convolution2d_40 0.0154 ms 86.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:12.5240138Z triton_convolution2d_34 0.0174 ms 76.5% 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 2025-09-07T09:54:12.5241621Z triton_convolution2d_35 0.0174 ms 76.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:12.5243091Z triton_convolution2d_36 0.0195 ms 68.4% 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 2025-09-07T09:54:12.5244003Z convolution 0.0215 ms 61.9% 2025-09-07T09:54:12.5244311Z conv1x1_via_mm 0.0635 ms 21.0% 2025-09-07T09:54:12.5244878Z SingleProcess AUTOTUNE benchmarking takes 0.1508 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:12.7056502Z Autotune Choices Stats: 2025-09-07T09:54:12.7057872Z {"num_choices": 9, "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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.015359999611973763, "best_triton_pos": 0} 2025-09-07T09:54:12.7107905Z AUTOTUNE convolution(4x160x56x56, 128x160x1x1) 2025-09-07T09:54:12.7108309Z strides: [501760, 3136, 56, 1], [160, 1, 1, 1] 2025-09-07T09:54:12.7108640Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.7109970Z triton_convolution2d_52 0.0154 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 2025-09-07T09:54:12.7111477Z triton_convolution2d_53 0.0154 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 2025-09-07T09:54:12.7112960Z triton_convolution2d_51 0.0164 ms 93.7% 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 2025-09-07T09:54:12.7114621Z triton_convolution2d_54 0.0164 ms 93.7% 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 2025-09-07T09:54:12.7116121Z triton_convolution2d_48 0.0184 ms 83.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:12.7117599Z triton_convolution2d_49 0.0184 ms 83.3% 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 2025-09-07T09:54:12.7119078Z triton_convolution2d_50 0.0215 ms 71.4% 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 2025-09-07T09:54:12.7119990Z convolution 0.0256 ms 60.0% 2025-09-07T09:54:12.7120286Z conv1x1_via_mm 0.0696 ms 22.1% 2025-09-07T09:54:12.7120846Z SingleProcess AUTOTUNE benchmarking takes 0.1536 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:12.8970111Z Autotune Choices Stats: 2025-09-07T09:54:12.8971512Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_66", "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": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T09:54:12.9021989Z AUTOTUNE convolution(4x192x56x56, 128x192x1x1) 2025-09-07T09:54:12.9022424Z strides: [602112, 3136, 56, 1], [192, 1, 1, 1] 2025-09-07T09:54:12.9022773Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.9023670Z triton_convolution2d_66 0.0164 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 2025-09-07T09:54:12.9025219Z triton_convolution2d_67 0.0164 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 2025-09-07T09:54:12.9026737Z triton_convolution2d_65 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 2025-09-07T09:54:12.9028226Z triton_convolution2d_68 0.0184 ms 88.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:12.9029703Z triton_convolution2d_62 0.0195 ms 84.2% 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 2025-09-07T09:54:12.9031171Z triton_convolution2d_63 0.0205 ms 80.0% 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 2025-09-07T09:54:12.9033011Z triton_convolution2d_64 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 2025-09-07T09:54:12.9033917Z convolution 0.0328 ms 50.0% 2025-09-07T09:54:12.9034200Z conv1x1_via_mm 0.0727 ms 22.5% 2025-09-07T09:54:12.9034767Z SingleProcess AUTOTUNE benchmarking takes 0.1568 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:13.0890754Z Autotune Choices Stats: 2025-09-07T09:54:13.0892083Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_79", "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": 0.018432000651955605, "best_triton_pos": 0} 2025-09-07T09:54:13.0942368Z AUTOTUNE convolution(4x224x56x56, 128x224x1x1) 2025-09-07T09:54:13.0942744Z strides: [702464, 3136, 56, 1], [224, 1, 1, 1] 2025-09-07T09:54:13.0943088Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:13.0944001Z triton_convolution2d_79 0.0184 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 2025-09-07T09:54:13.0945545Z triton_convolution2d_80 0.0184 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 2025-09-07T09:54:13.0947026Z triton_convolution2d_81 0.0184 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 2025-09-07T09:54:13.0948502Z triton_convolution2d_82 0.0195 ms 94.7% 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 2025-09-07T09:54:13.0950262Z triton_convolution2d_77 0.0225 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:13.0951732Z triton_convolution2d_76 0.0256 ms 72.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:13.0953199Z triton_convolution2d_78 0.0297 ms 62.1% 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 2025-09-07T09:54:13.0954103Z convolution 0.0358 ms 51.4% 2025-09-07T09:54:13.0954382Z conv1x1_via_mm 0.0809 ms 22.8% 2025-09-07T09:54:13.0954949Z SingleProcess AUTOTUNE benchmarking takes 0.1572 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:13.2745731Z Autotune Choices Stats: 2025-09-07T09:54:13.2747102Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_101", "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} 2025-09-07T09:54:13.2797777Z AUTOTUNE convolution(4x128x28x28, 128x128x1x1) 2025-09-07T09:54:13.2798235Z strides: [100352, 784, 28, 1], [128, 1, 1, 1] 2025-09-07T09:54:13.2798566Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:13.2799477Z triton_convolution2d_101 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 2025-09-07T09:54:13.2800407Z convolution 0.0123 ms 91.7% 2025-09-07T09:54:13.2801596Z triton_convolution2d_102 0.0123 ms 91.7% 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 2025-09-07T09:54:13.2803084Z triton_convolution2d_97 0.0143 ms 78.6% 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 2025-09-07T09:54:13.2804569Z triton_convolution2d_100 0.0143 ms 78.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:13.2806042Z triton_convolution2d_103 0.0143 ms 78.6% 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 2025-09-07T09:54:13.2807529Z triton_convolution2d_98 0.0164 ms 68.8% 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 2025-09-07T09:54:13.2809003Z triton_convolution2d_99 0.0195 ms 57.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:13.2809904Z conv1x1_via_mm 0.0297 ms 37.9% 2025-09-07T09:54:13.2810472Z SingleProcess AUTOTUNE benchmarking takes 0.1512 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:13.7318510Z Autotune Choices Stats: 2025-09-07T09:54:13.7319870Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_115", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T09:54:13.7370565Z AUTOTUNE convolution(4x160x28x28, 128x160x1x1) 2025-09-07T09:54:13.7371027Z strides: [125440, 784, 28, 1], [160, 1, 1, 1] 2025-09-07T09:54:13.7371360Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:13.7372271Z triton_convolution2d_115 0.0123 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:13.7373386Z convolution 0.0133 ms 92.3% 2025-09-07T09:54:13.7374266Z triton_convolution2d_116 0.0133 ms 92.3% 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 2025-09-07T09:54:13.7375750Z triton_convolution2d_111 0.0164 ms 75.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:13.7377235Z triton_convolution2d_114 0.0164 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:13.7378726Z triton_convolution2d_117 0.0164 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:13.7380213Z triton_convolution2d_112 0.0184 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:13.7381694Z triton_convolution2d_113 0.0225 ms 54.5% 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 2025-09-07T09:54:13.7382606Z conv1x1_via_mm 0.0317 ms 38.7% 2025-09-07T09:54:13.7383419Z SingleProcess AUTOTUNE benchmarking takes 0.1489 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:13.9176354Z Autotune Choices Stats: 2025-09-07T09:54:13.9178080Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.013311999849975109, "best_triton_kernel": "triton_convolution2d_129", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:54:13.9229395Z AUTOTUNE convolution(4x192x28x28, 128x192x1x1) 2025-09-07T09:54:13.9229780Z strides: [150528, 784, 28, 1], [192, 1, 1, 1] 2025-09-07T09:54:13.9230158Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:13.9230478Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:13.9231360Z triton_convolution2d_129 0.0133 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 2025-09-07T09:54:13.9232844Z triton_convolution2d_130 0.0154 ms 86.7% 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 2025-09-07T09:54:13.9234327Z triton_convolution2d_125 0.0174 ms 76.5% 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 2025-09-07T09:54:13.9235817Z triton_convolution2d_128 0.0174 ms 76.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:13.9237718Z triton_convolution2d_131 0.0174 ms 76.5% 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 2025-09-07T09:54:13.9239198Z triton_convolution2d_126 0.0205 ms 65.0% 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 2025-09-07T09:54:13.9240682Z triton_convolution2d_127 0.0246 ms 54.2% 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 2025-09-07T09:54:13.9241577Z conv1x1_via_mm 0.0328 ms 40.6% 2025-09-07T09:54:13.9242145Z SingleProcess AUTOTUNE benchmarking takes 0.1518 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:14.1059782Z Autotune Choices Stats: 2025-09-07T09:54:14.1061490Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "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"} 2025-09-07T09:54:14.1113619Z AUTOTUNE convolution(4x224x28x28, 128x224x1x1) 2025-09-07T09:54:14.1114024Z strides: [175616, 784, 28, 1], [224, 1, 1, 1] 2025-09-07T09:54:14.1114356Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:14.1114678Z convolution 0.0143 ms 100.0% 2025-09-07T09:54:14.1115567Z triton_convolution2d_143 0.0143 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 2025-09-07T09:54:14.1117426Z triton_convolution2d_144 0.0154 ms 93.3% 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 2025-09-07T09:54:14.1118931Z triton_convolution2d_142 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.1120425Z triton_convolution2d_145 0.0184 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.1121891Z triton_convolution2d_139 0.0195 ms 73.7% 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 2025-09-07T09:54:14.1123377Z triton_convolution2d_140 0.0215 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:14.1124865Z triton_convolution2d_141 0.0276 ms 51.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:14.1125772Z conv1x1_via_mm 0.0369 ms 38.9% 2025-09-07T09:54:14.1126337Z SingleProcess AUTOTUNE benchmarking takes 0.1540 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:14.2949632Z Autotune Choices Stats: 2025-09-07T09:54:14.2951325Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014336000196635723, "best_triton_pos": 1, "best_triton_time": 0.015359999611973763, "best_triton_kernel": "triton_convolution2d_157", "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"} 2025-09-07T09:54:14.3002696Z AUTOTUNE convolution(4x256x28x28, 128x256x1x1) 2025-09-07T09:54:14.3003126Z strides: [200704, 784, 28, 1], [256, 1, 1, 1] 2025-09-07T09:54:14.3003469Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:14.3003789Z convolution 0.0143 ms 100.0% 2025-09-07T09:54:14.3004681Z triton_convolution2d_157 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 2025-09-07T09:54:14.3006147Z triton_convolution2d_158 0.0164 ms 87.5% 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 2025-09-07T09:54:14.3007636Z triton_convolution2d_156 0.0205 ms 70.0% 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 2025-09-07T09:54:14.3009126Z triton_convolution2d_159 0.0205 ms 70.0% 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 2025-09-07T09:54:14.3010613Z triton_convolution2d_153 0.0215 ms 66.7% 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 2025-09-07T09:54:14.3012094Z triton_convolution2d_154 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:14.3013837Z triton_convolution2d_155 0.0307 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=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:14.3014748Z conv1x1_via_mm 0.0379 ms 37.8% 2025-09-07T09:54:14.3015544Z SingleProcess AUTOTUNE benchmarking takes 0.1542 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:14.4849640Z Autotune Choices Stats: 2025-09-07T09:54:14.4851328Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.016383999958634377, "best_triton_kernel": "triton_convolution2d_171", "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"} 2025-09-07T09:54:14.4903659Z AUTOTUNE convolution(4x288x28x28, 128x288x1x1) 2025-09-07T09:54:14.4904062Z strides: [225792, 784, 28, 1], [288, 1, 1, 1] 2025-09-07T09:54:14.4904443Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:14.4904797Z convolution 0.0164 ms 100.0% 2025-09-07T09:54:14.4905694Z triton_convolution2d_171 0.0164 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 2025-09-07T09:54:14.4907182Z triton_convolution2d_172 0.0184 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.4908673Z triton_convolution2d_170 0.0215 ms 76.2% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.4910166Z triton_convolution2d_173 0.0215 ms 76.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.4911972Z triton_convolution2d_167 0.0236 ms 69.6% 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 2025-09-07T09:54:14.4913457Z triton_convolution2d_168 0.0256 ms 64.0% 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 2025-09-07T09:54:14.4914944Z triton_convolution2d_169 0.0338 ms 48.5% 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 2025-09-07T09:54:14.4915840Z conv1x1_via_mm 0.0410 ms 40.0% 2025-09-07T09:54:14.4916411Z SingleProcess AUTOTUNE benchmarking takes 0.1553 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:14.6775783Z Autotune Choices Stats: 2025-09-07T09:54:14.6777513Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.01740800030529499, "best_triton_kernel": "triton_convolution2d_185", "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"} 2025-09-07T09:54:14.6829969Z AUTOTUNE convolution(4x320x28x28, 128x320x1x1) 2025-09-07T09:54:14.6830359Z strides: [250880, 784, 28, 1], [320, 1, 1, 1] 2025-09-07T09:54:14.6830707Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:14.6831015Z convolution 0.0164 ms 100.0% 2025-09-07T09:54:14.6831894Z triton_convolution2d_185 0.0174 ms 94.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:14.6837987Z triton_convolution2d_186 0.0195 ms 84.2% 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 2025-09-07T09:54:14.6839665Z triton_convolution2d_184 0.0236 ms 69.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.6841161Z triton_convolution2d_187 0.0236 ms 69.6% 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 2025-09-07T09:54:14.6842647Z triton_convolution2d_181 0.0246 ms 66.7% 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 2025-09-07T09:54:14.6844143Z triton_convolution2d_182 0.0287 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:14.6845643Z triton_convolution2d_183 0.0358 ms 45.7% 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 2025-09-07T09:54:14.6846540Z conv1x1_via_mm 0.0420 ms 39.0% 2025-09-07T09:54:14.6847113Z SingleProcess AUTOTUNE benchmarking takes 0.1579 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:14.8702636Z Autotune Choices Stats: 2025-09-07T09:54:14.8704345Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.01740800030529499, "best_triton_kernel": "triton_convolution2d_199", "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"} 2025-09-07T09:54:14.8759195Z AUTOTUNE convolution(4x352x28x28, 128x352x1x1) 2025-09-07T09:54:14.8759586Z strides: [275968, 784, 28, 1], [352, 1, 1, 1] 2025-09-07T09:54:14.8759923Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:14.8760243Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:14.8761121Z triton_convolution2d_199 0.0174 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 2025-09-07T09:54:14.8762611Z triton_convolution2d_200 0.0205 ms 65.0% 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 2025-09-07T09:54:14.8764098Z triton_convolution2d_198 0.0246 ms 54.2% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.8765596Z triton_convolution2d_201 0.0246 ms 54.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:14.8767056Z triton_convolution2d_195 0.0256 ms 52.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:14.8768538Z triton_convolution2d_196 0.0297 ms 44.8% 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 2025-09-07T09:54:14.8770018Z triton_convolution2d_197 0.0389 ms 34.2% 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 2025-09-07T09:54:14.8770947Z conv1x1_via_mm 0.0492 ms 27.1% 2025-09-07T09:54:14.8771765Z SingleProcess AUTOTUNE benchmarking takes 0.1582 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:15.0639053Z Autotune Choices Stats: 2025-09-07T09:54:15.0640757Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "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"} 2025-09-07T09:54:15.0692688Z AUTOTUNE convolution(4x384x28x28, 128x384x1x1) 2025-09-07T09:54:15.0693179Z strides: [301056, 784, 28, 1], [384, 1, 1, 1] 2025-09-07T09:54:15.0693555Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:15.0693887Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:15.0694791Z triton_convolution2d_213 0.0195 ms 68.4% 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 2025-09-07T09:54:15.0696287Z triton_convolution2d_214 0.0215 ms 61.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:15.0697784Z triton_convolution2d_212 0.0256 ms 52.0% 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 2025-09-07T09:54:15.0699268Z triton_convolution2d_215 0.0256 ms 52.0% 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 2025-09-07T09:54:15.0701095Z triton_convolution2d_209 0.0276 ms 48.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:15.0702581Z triton_convolution2d_210 0.0317 ms 41.9% 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 2025-09-07T09:54:15.0704063Z triton_convolution2d_211 0.0420 ms 31.7% 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 2025-09-07T09:54:15.0705064Z conv1x1_via_mm 0.0502 ms 26.5% 2025-09-07T09:54:15.0705636Z SingleProcess AUTOTUNE benchmarking takes 0.1577 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:15.2577544Z Autotune Choices Stats: 2025-09-07T09:54:15.2579284Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:54:15.2631920Z AUTOTUNE convolution(4x416x28x28, 128x416x1x1) 2025-09-07T09:54:15.2632299Z strides: [326144, 784, 28, 1], [416, 1, 1, 1] 2025-09-07T09:54:15.2632643Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:15.2632950Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:15.2633837Z triton_convolution2d_227 0.0195 ms 68.4% 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 2025-09-07T09:54:15.2635679Z triton_convolution2d_228 0.0225 ms 59.1% 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 2025-09-07T09:54:15.2637164Z triton_convolution2d_229 0.0266 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:15.2638653Z triton_convolution2d_226 0.0276 ms 48.1% 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 2025-09-07T09:54:15.2640141Z triton_convolution2d_223 0.0297 ms 44.8% 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 2025-09-07T09:54:15.2641634Z triton_convolution2d_224 0.0328 ms 40.6% 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 2025-09-07T09:54:15.2643117Z triton_convolution2d_225 0.0440 ms 30.2% 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 2025-09-07T09:54:15.2644027Z conv1x1_via_mm 0.0502 ms 26.5% 2025-09-07T09:54:15.2644595Z SingleProcess AUTOTUNE benchmarking takes 0.1588 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:15.4541683Z Autotune Choices Stats: 2025-09-07T09:54:15.4543389Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.020479999482631683, "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"} 2025-09-07T09:54:15.4596965Z AUTOTUNE convolution(4x448x28x28, 128x448x1x1) 2025-09-07T09:54:15.4597340Z strides: [351232, 784, 28, 1], [448, 1, 1, 1] 2025-09-07T09:54:15.4597678Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:15.4597996Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:15.4598873Z triton_convolution2d_241 0.0205 ms 65.0% 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 2025-09-07T09:54:15.4600348Z triton_convolution2d_242 0.0236 ms 56.5% 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 2025-09-07T09:54:15.4601838Z triton_convolution2d_240 0.0287 ms 46.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:15.4603338Z triton_convolution2d_243 0.0287 ms 46.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:15.4604807Z triton_convolution2d_237 0.0307 ms 43.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:15.4606288Z triton_convolution2d_238 0.0348 ms 38.2% 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 2025-09-07T09:54:15.4607782Z triton_convolution2d_239 0.0471 ms 28.3% 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 2025-09-07T09:54:15.4608700Z conv1x1_via_mm 0.0502 ms 26.5% 2025-09-07T09:54:15.4609520Z SingleProcess AUTOTUNE benchmarking takes 0.1614 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:15.6515281Z Autotune Choices Stats: 2025-09-07T09:54:15.6516979Z {"num_choices": 9, "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_255", "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"} 2025-09-07T09:54:15.6569792Z AUTOTUNE convolution(4x480x28x28, 128x480x1x1) 2025-09-07T09:54:15.6570193Z strides: [376320, 784, 28, 1], [480, 1, 1, 1] 2025-09-07T09:54:15.6570558Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:15.6570877Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:15.6571771Z triton_convolution2d_255 0.0215 ms 61.9% 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 2025-09-07T09:54:15.6573471Z triton_convolution2d_256 0.0246 ms 54.2% 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 2025-09-07T09:54:15.6574973Z triton_convolution2d_254 0.0297 ms 44.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:15.6576465Z triton_convolution2d_257 0.0297 ms 44.8% 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 2025-09-07T09:54:15.6578281Z triton_convolution2d_251 0.0328 ms 40.6% 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 2025-09-07T09:54:15.6579769Z triton_convolution2d_252 0.0369 ms 36.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:15.6581267Z triton_convolution2d_253 0.0492 ms 27.1% 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 2025-09-07T09:54:15.6582180Z conv1x1_via_mm 0.0522 ms 25.5% 2025-09-07T09:54:15.6582747Z SingleProcess AUTOTUNE benchmarking takes 0.1621 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:15.8200563Z Autotune Choices Stats: 2025-09-07T09:54:15.8202308Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013311999849975109, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_convolution2d_276", "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"} 2025-09-07T09:54:15.8256115Z AUTOTUNE convolution(4x256x14x14, 128x256x1x1) 2025-09-07T09:54:15.8256543Z strides: [50176, 196, 14, 1], [256, 1, 1, 1] 2025-09-07T09:54:15.8256891Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:15.8257214Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:15.8258106Z triton_convolution2d_276 0.0143 ms 92.9% 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 2025-09-07T09:54:15.8259973Z triton_convolution2d_277 0.0164 ms 81.2% 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 2025-09-07T09:54:15.8261464Z triton_convolution2d_275 0.0205 ms 65.0% 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 2025-09-07T09:54:15.8262958Z triton_convolution2d_278 0.0205 ms 65.0% 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 2025-09-07T09:54:15.8264441Z triton_convolution2d_272 0.0215 ms 61.9% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:15.8266037Z triton_convolution2d_273 0.0246 ms 54.2% 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 2025-09-07T09:54:15.8266949Z conv1x1_via_mm 0.0256 ms 52.0% 2025-09-07T09:54:15.8267844Z triton_convolution2d_274 0.0287 ms 46.4% 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 2025-09-07T09:54:15.8269025Z SingleProcess AUTOTUNE benchmarking takes 0.1551 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:16.2953255Z Autotune Choices Stats: 2025-09-07T09:54:16.2954949Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.015359999611973763, "best_triton_kernel": "triton_convolution2d_290", "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"} 2025-09-07T09:54:16.3009394Z AUTOTUNE convolution(4x288x14x14, 128x288x1x1) 2025-09-07T09:54:16.3009775Z strides: [56448, 196, 14, 1], [288, 1, 1, 1] 2025-09-07T09:54:16.3010108Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:16.3010429Z convolution 0.0154 ms 100.0% 2025-09-07T09:54:16.3011318Z triton_convolution2d_290 0.0154 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 2025-09-07T09:54:16.3013037Z triton_convolution2d_291 0.0174 ms 88.2% 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 2025-09-07T09:54:16.3014536Z triton_convolution2d_286 0.0215 ms 71.4% 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 2025-09-07T09:54:16.3016043Z triton_convolution2d_289 0.0215 ms 71.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:16.3017517Z triton_convolution2d_292 0.0215 ms 71.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:16.3018417Z conv1x1_via_mm 0.0246 ms 62.5% 2025-09-07T09:54:16.3019289Z triton_convolution2d_287 0.0246 ms 62.5% 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 2025-09-07T09:54:16.3021004Z triton_convolution2d_288 0.0317 ms 48.4% 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 2025-09-07T09:54:16.3022185Z SingleProcess AUTOTUNE benchmarking takes 0.1561 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:16.4870312Z Autotune Choices Stats: 2025-09-07T09:54:16.4871969Z {"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_304", "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"} 2025-09-07T09:54:16.4925906Z AUTOTUNE convolution(4x320x14x14, 128x320x1x1) 2025-09-07T09:54:16.4926297Z strides: [62720, 196, 14, 1], [320, 1, 1, 1] 2025-09-07T09:54:16.4926666Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:16.4926989Z convolution 0.0154 ms 100.0% 2025-09-07T09:54:16.4927885Z triton_convolution2d_304 0.0164 ms 93.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:16.4929356Z triton_convolution2d_305 0.0184 ms 83.3% 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 2025-09-07T09:54:16.4930847Z triton_convolution2d_303 0.0225 ms 68.2% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:16.4932331Z triton_convolution2d_300 0.0236 ms 65.2% 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 2025-09-07T09:54:16.4934411Z triton_convolution2d_306 0.0236 ms 65.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:16.4935318Z conv1x1_via_mm 0.0256 ms 60.0% 2025-09-07T09:54:16.4936202Z triton_convolution2d_301 0.0287 ms 53.6% 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 2025-09-07T09:54:16.4937689Z triton_convolution2d_302 0.0348 ms 44.1% 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 2025-09-07T09:54:16.4938861Z SingleProcess AUTOTUNE benchmarking takes 0.1570 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:16.6806310Z Autotune Choices Stats: 2025-09-07T09:54:16.6807680Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_318", "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": 0.016383999958634377, "best_triton_pos": 0} 2025-09-07T09:54:16.6862712Z AUTOTUNE convolution(4x352x14x14, 128x352x1x1) 2025-09-07T09:54:16.6863075Z strides: [68992, 196, 14, 1], [352, 1, 1, 1] 2025-09-07T09:54:16.6863425Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:16.6864334Z triton_convolution2d_318 0.0164 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 2025-09-07T09:54:16.6865307Z convolution 0.0195 ms 84.2% 2025-09-07T09:54:16.6866193Z triton_convolution2d_319 0.0195 ms 84.2% 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 2025-09-07T09:54:16.6867999Z triton_convolution2d_314 0.0246 ms 66.7% 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 2025-09-07T09:54:16.6869471Z triton_convolution2d_317 0.0246 ms 66.7% 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 2025-09-07T09:54:16.6870962Z triton_convolution2d_320 0.0246 ms 66.7% 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 2025-09-07T09:54:16.6871864Z conv1x1_via_mm 0.0287 ms 57.1% 2025-09-07T09:54:16.6872755Z triton_convolution2d_315 0.0287 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:16.6874244Z triton_convolution2d_316 0.0369 ms 44.4% 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 2025-09-07T09:54:16.6875411Z SingleProcess AUTOTUNE benchmarking takes 0.1586 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:16.8762252Z Autotune Choices Stats: 2025-09-07T09:54:16.8763943Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 1, "best_triton_time": 0.018432000651955605, "best_triton_kernel": "triton_convolution2d_332", "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"} 2025-09-07T09:54:16.8819257Z AUTOTUNE convolution(4x384x14x14, 128x384x1x1) 2025-09-07T09:54:16.8819704Z strides: [75264, 196, 14, 1], [384, 1, 1, 1] 2025-09-07T09:54:16.8820051Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:16.8820376Z convolution 0.0164 ms 100.0% 2025-09-07T09:54:16.8821264Z triton_convolution2d_332 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 2025-09-07T09:54:16.8822747Z triton_convolution2d_333 0.0215 ms 76.2% 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 2025-09-07T09:54:16.8824245Z triton_convolution2d_331 0.0256 ms 64.0% 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 2025-09-07T09:54:16.8825832Z triton_convolution2d_328 0.0266 ms 61.5% 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 2025-09-07T09:54:16.8827319Z triton_convolution2d_334 0.0266 ms 61.5% 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 2025-09-07T09:54:16.8828229Z conv1x1_via_mm 0.0276 ms 59.3% 2025-09-07T09:54:16.8829116Z triton_convolution2d_329 0.0328 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:16.8830595Z triton_convolution2d_330 0.0399 ms 41.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:16.8832127Z SingleProcess AUTOTUNE benchmarking takes 0.1607 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:17.0743694Z Autotune Choices Stats: 2025-09-07T09:54:17.0745504Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.018432000651955605, "best_triton_kernel": "triton_convolution2d_346", "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"} 2025-09-07T09:54:17.0802309Z AUTOTUNE convolution(4x416x14x14, 128x416x1x1) 2025-09-07T09:54:17.0802725Z strides: [81536, 196, 14, 1], [416, 1, 1, 1] 2025-09-07T09:54:17.0803074Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:17.0803420Z convolution 0.0174 ms 100.0% 2025-09-07T09:54:17.0804325Z triton_convolution2d_346 0.0184 ms 94.4% 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 2025-09-07T09:54:17.0805809Z triton_convolution2d_347 0.0215 ms 81.0% 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 2025-09-07T09:54:17.0807290Z triton_convolution2d_345 0.0266 ms 65.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:17.0808771Z triton_convolution2d_342 0.0276 ms 63.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.0810535Z triton_convolution2d_348 0.0276 ms 63.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:17.0811421Z conv1x1_via_mm 0.0287 ms 60.7% 2025-09-07T09:54:17.0812306Z triton_convolution2d_343 0.0328 ms 53.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.0814064Z triton_convolution2d_344 0.0420 ms 41.5% 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 2025-09-07T09:54:17.0815243Z SingleProcess AUTOTUNE benchmarking takes 0.1629 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:17.2768913Z Autotune Choices Stats: 2025-09-07T09:54:17.2770654Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 1, "best_triton_time": 0.01945599913597107, "best_triton_kernel": "triton_convolution2d_360", "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"} 2025-09-07T09:54:17.2828203Z AUTOTUNE convolution(4x448x14x14, 128x448x1x1) 2025-09-07T09:54:17.2828625Z strides: [87808, 196, 14, 1], [448, 1, 1, 1] 2025-09-07T09:54:17.2828960Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:17.2829288Z convolution 0.0195 ms 100.0% 2025-09-07T09:54:17.2830185Z triton_convolution2d_360 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 2025-09-07T09:54:17.2831702Z triton_convolution2d_361 0.0225 ms 86.4% 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 2025-09-07T09:54:17.2832937Z conv1x1_via_mm 0.0287 ms 67.9% 2025-09-07T09:54:17.2833824Z triton_convolution2d_356 0.0287 ms 67.9% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.2835326Z triton_convolution2d_359 0.0287 ms 67.9% 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 2025-09-07T09:54:17.2836818Z triton_convolution2d_362 0.0287 ms 67.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:17.2838311Z triton_convolution2d_357 0.0369 ms 52.8% 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 2025-09-07T09:54:17.2839814Z triton_convolution2d_358 0.0451 ms 43.2% 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 2025-09-07T09:54:17.2841002Z SingleProcess AUTOTUNE benchmarking takes 0.1664 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:17.4796917Z Autotune Choices Stats: 2025-09-07T09:54:17.4798626Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.020479999482631683, "best_triton_kernel": "triton_convolution2d_374", "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"} 2025-09-07T09:54:17.4854942Z AUTOTUNE convolution(4x480x14x14, 128x480x1x1) 2025-09-07T09:54:17.4855346Z strides: [94080, 196, 14, 1], [480, 1, 1, 1] 2025-09-07T09:54:17.4855691Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:17.4856019Z convolution 0.0205 ms 100.0% 2025-09-07T09:54:17.4856907Z triton_convolution2d_374 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.4858390Z triton_convolution2d_375 0.0236 ms 87.0% 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 2025-09-07T09:54:17.4859286Z conv1x1_via_mm 0.0297 ms 69.0% 2025-09-07T09:54:17.4860182Z triton_convolution2d_373 0.0297 ms 69.0% 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 2025-09-07T09:54:17.4861674Z triton_convolution2d_376 0.0297 ms 69.0% 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 2025-09-07T09:54:17.4863152Z triton_convolution2d_370 0.0307 ms 66.7% 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 2025-09-07T09:54:17.4864637Z triton_convolution2d_371 0.0358 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.4866176Z triton_convolution2d_372 0.0471 ms 43.5% 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 2025-09-07T09:54:17.4867618Z SingleProcess AUTOTUNE benchmarking takes 0.1665 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:17.6827786Z Autotune Choices Stats: 2025-09-07T09:54:17.6829491Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_convolution2d_388", "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"} 2025-09-07T09:54:17.6889743Z AUTOTUNE convolution(4x512x14x14, 128x512x1x1) 2025-09-07T09:54:17.6890133Z strides: [100352, 196, 14, 1], [512, 1, 1, 1] 2025-09-07T09:54:17.6890514Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:17.6890832Z convolution 0.0205 ms 100.0% 2025-09-07T09:54:17.6891728Z triton_convolution2d_388 0.0215 ms 95.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.6893474Z triton_convolution2d_389 0.0246 ms 83.3% 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 2025-09-07T09:54:17.6894384Z conv1x1_via_mm 0.0297 ms 69.0% 2025-09-07T09:54:17.6895273Z triton_convolution2d_387 0.0307 ms 66.7% 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 2025-09-07T09:54:17.6896764Z triton_convolution2d_390 0.0317 ms 64.5% 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 2025-09-07T09:54:17.6898579Z triton_convolution2d_384 0.0338 ms 60.6% 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 2025-09-07T09:54:17.6900057Z triton_convolution2d_385 0.0410 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:17.6901555Z triton_convolution2d_386 0.0502 ms 40.8% 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 2025-09-07T09:54:17.6902732Z SingleProcess AUTOTUNE benchmarking takes 0.1667 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:17.8862334Z Autotune Choices Stats: 2025-09-07T09:54:17.8864043Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_convolution2d_402", "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"} 2025-09-07T09:54:17.8922506Z AUTOTUNE convolution(4x544x14x14, 128x544x1x1) 2025-09-07T09:54:17.8922900Z strides: [106624, 196, 14, 1], [544, 1, 1, 1] 2025-09-07T09:54:17.8923254Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:17.8923560Z convolution 0.0205 ms 100.0% 2025-09-07T09:54:17.8924439Z triton_convolution2d_402 0.0225 ms 90.9% 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 2025-09-07T09:54:17.8926286Z triton_convolution2d_403 0.0266 ms 76.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:17.8927204Z conv1x1_via_mm 0.0307 ms 66.7% 2025-09-07T09:54:17.8928100Z triton_convolution2d_401 0.0328 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:17.8929590Z triton_convolution2d_404 0.0328 ms 62.5% 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 2025-09-07T09:54:17.8931054Z triton_convolution2d_398 0.0338 ms 60.6% 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 2025-09-07T09:54:17.8932544Z triton_convolution2d_399 0.0399 ms 51.3% 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 2025-09-07T09:54:17.8934304Z triton_convolution2d_400 0.0522 ms 39.2% 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 2025-09-07T09:54:17.8935487Z SingleProcess AUTOTUNE benchmarking takes 0.1670 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:18.0908175Z Autotune Choices Stats: 2025-09-07T09:54:18.0909846Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_convolution2d_416", "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"} 2025-09-07T09:54:18.0967207Z AUTOTUNE convolution(4x576x14x14, 128x576x1x1) 2025-09-07T09:54:18.0967604Z strides: [112896, 196, 14, 1], [576, 1, 1, 1] 2025-09-07T09:54:18.0967935Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:18.0968256Z convolution 0.0205 ms 100.0% 2025-09-07T09:54:18.0969131Z triton_convolution2d_416 0.0225 ms 90.9% 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 2025-09-07T09:54:18.0970611Z triton_convolution2d_417 0.0276 ms 74.1% 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 2025-09-07T09:54:18.0971518Z conv1x1_via_mm 0.0307 ms 66.7% 2025-09-07T09:54:18.0972402Z triton_convolution2d_415 0.0338 ms 60.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.0974131Z triton_convolution2d_418 0.0348 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.0975609Z triton_convolution2d_412 0.0358 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:18.0977086Z triton_convolution2d_413 0.0451 ms 45.5% 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 2025-09-07T09:54:18.0978570Z triton_convolution2d_414 0.0553 ms 37.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:18.0979990Z SingleProcess AUTOTUNE benchmarking takes 0.1681 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:18.2975382Z Autotune Choices Stats: 2025-09-07T09:54:18.3035999Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.023552000522613525, "best_triton_kernel": "triton_convolution2d_430", "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"} 2025-09-07T09:54:18.3037697Z AUTOTUNE convolution(4x608x14x14, 128x608x1x1) 2025-09-07T09:54:18.3038066Z strides: [119168, 196, 14, 1], [608, 1, 1, 1] 2025-09-07T09:54:18.3038441Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:18.3038760Z convolution 0.0215 ms 100.0% 2025-09-07T09:54:18.3039650Z triton_convolution2d_430 0.0236 ms 91.3% 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 2025-09-07T09:54:18.3041108Z triton_convolution2d_431 0.0287 ms 75.0% 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 2025-09-07T09:54:18.3042014Z conv1x1_via_mm 0.0317 ms 67.7% 2025-09-07T09:54:18.3042921Z triton_convolution2d_429 0.0348 ms 61.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.3044411Z triton_convolution2d_432 0.0358 ms 60.0% 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 2025-09-07T09:54:18.3046269Z triton_convolution2d_426 0.0369 ms 58.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:18.3047755Z triton_convolution2d_427 0.0440 ms 48.8% 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 2025-09-07T09:54:18.3049239Z triton_convolution2d_428 0.0584 ms 36.8% 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 2025-09-07T09:54:18.3050415Z SingleProcess AUTOTUNE benchmarking takes 0.1710 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:18.5060154Z Autotune Choices Stats: 2025-09-07T09:54:18.5061888Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.02457600086927414, "best_triton_kernel": "triton_convolution2d_444", "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"} 2025-09-07T09:54:18.5119487Z AUTOTUNE convolution(4x640x14x14, 128x640x1x1) 2025-09-07T09:54:18.5119956Z strides: [125440, 196, 14, 1], [640, 1, 1, 1] 2025-09-07T09:54:18.5120306Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:18.5120635Z convolution 0.0215 ms 100.0% 2025-09-07T09:54:18.5121507Z triton_convolution2d_444 0.0246 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:18.5123334Z triton_convolution2d_445 0.0297 ms 72.4% 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 2025-09-07T09:54:18.5124251Z conv1x1_via_mm 0.0317 ms 67.7% 2025-09-07T09:54:18.5125143Z triton_convolution2d_443 0.0369 ms 58.3% 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 2025-09-07T09:54:18.5126633Z triton_convolution2d_446 0.0379 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.5128120Z triton_convolution2d_440 0.0389 ms 55.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:18.5129615Z triton_convolution2d_441 0.0492 ms 43.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:18.5131089Z triton_convolution2d_442 0.0614 ms 35.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:18.5132261Z SingleProcess AUTOTUNE benchmarking takes 0.1726 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:18.7133317Z Autotune Choices Stats: 2025-09-07T09:54:18.7135033Z {"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_458", "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"} 2025-09-07T09:54:18.7201380Z AUTOTUNE convolution(4x672x14x14, 128x672x1x1) 2025-09-07T09:54:18.7201793Z strides: [131712, 196, 14, 1], [672, 1, 1, 1] 2025-09-07T09:54:18.7202144Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:18.7202454Z convolution 0.0215 ms 100.0% 2025-09-07T09:54:18.7203353Z triton_convolution2d_458 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 2025-09-07T09:54:18.7204837Z triton_convolution2d_459 0.0307 ms 70.0% 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 2025-09-07T09:54:18.7205744Z conv1x1_via_mm 0.0338 ms 63.6% 2025-09-07T09:54:18.7206646Z triton_convolution2d_457 0.0379 ms 56.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.7208134Z triton_convolution2d_460 0.0389 ms 55.3% 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 2025-09-07T09:54:18.7209614Z triton_convolution2d_454 0.0399 ms 53.8% 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 2025-09-07T09:54:18.7211081Z triton_convolution2d_455 0.0471 ms 45.7% 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 2025-09-07T09:54:18.7212568Z triton_convolution2d_456 0.0635 ms 33.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:18.7214181Z SingleProcess AUTOTUNE benchmarking takes 0.1721 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:18.9239775Z Autotune Choices Stats: 2025-09-07T09:54:18.9241478Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021503999829292297, "best_triton_pos": 1, "best_triton_time": 0.026623999699950218, "best_triton_kernel": "triton_convolution2d_472", "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"} 2025-09-07T09:54:18.9305460Z AUTOTUNE convolution(4x704x14x14, 128x704x1x1) 2025-09-07T09:54:18.9305834Z strides: [137984, 196, 14, 1], [704, 1, 1, 1] 2025-09-07T09:54:18.9306203Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:18.9306524Z convolution 0.0215 ms 100.0% 2025-09-07T09:54:18.9307419Z triton_convolution2d_472 0.0266 ms 80.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:18.9308905Z triton_convolution2d_473 0.0317 ms 67.7% 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 2025-09-07T09:54:18.9309814Z conv1x1_via_mm 0.0338 ms 63.6% 2025-09-07T09:54:18.9310688Z triton_convolution2d_471 0.0399 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.9312181Z triton_convolution2d_474 0.0410 ms 52.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:18.9314012Z triton_convolution2d_468 0.0420 ms 51.2% 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 2025-09-07T09:54:18.9315494Z triton_convolution2d_469 0.0532 ms 40.4% 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 2025-09-07T09:54:18.9316981Z triton_convolution2d_470 0.0666 ms 32.3% 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 2025-09-07T09:54:18.9318164Z SingleProcess AUTOTUNE benchmarking takes 0.1748 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:19.1345522Z Autotune Choices Stats: 2025-09-07T09:54:19.1347238Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.027648000046610832, "best_triton_kernel": "triton_convolution2d_486", "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"} 2025-09-07T09:54:19.1408785Z AUTOTUNE convolution(4x736x14x14, 128x736x1x1) 2025-09-07T09:54:19.1409214Z strides: [144256, 196, 14, 1], [736, 1, 1, 1] 2025-09-07T09:54:19.1409576Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:19.1409889Z convolution 0.0225 ms 100.0% 2025-09-07T09:54:19.1410783Z triton_convolution2d_486 0.0276 ms 81.5% 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 2025-09-07T09:54:19.1412619Z triton_convolution2d_487 0.0328 ms 68.8% 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 2025-09-07T09:54:19.1413771Z conv1x1_via_mm 0.0348 ms 64.7% 2025-09-07T09:54:19.1414674Z triton_convolution2d_485 0.0410 ms 55.0% 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 2025-09-07T09:54:19.1416169Z triton_convolution2d_488 0.0420 ms 53.7% 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 2025-09-07T09:54:19.1417659Z triton_convolution2d_482 0.0430 ms 52.4% 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 2025-09-07T09:54:19.1419162Z triton_convolution2d_483 0.0512 ms 44.0% 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 2025-09-07T09:54:19.1420632Z triton_convolution2d_484 0.0686 ms 32.8% 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 2025-09-07T09:54:19.1421806Z SingleProcess AUTOTUNE benchmarking takes 0.1744 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:19.3464076Z Autotune Choices Stats: 2025-09-07T09:54:19.3465836Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.027648000046610832, "best_triton_kernel": "triton_convolution2d_500", "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"} 2025-09-07T09:54:19.3528307Z AUTOTUNE convolution(4x768x14x14, 128x768x1x1) 2025-09-07T09:54:19.3528717Z strides: [150528, 196, 14, 1], [768, 1, 1, 1] 2025-09-07T09:54:19.3529054Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:19.3529383Z convolution 0.0225 ms 100.0% 2025-09-07T09:54:19.3530281Z triton_convolution2d_500 0.0276 ms 81.5% 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 2025-09-07T09:54:19.3531762Z triton_convolution2d_501 0.0338 ms 66.7% 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 2025-09-07T09:54:19.3532670Z conv1x1_via_mm 0.0348 ms 64.7% 2025-09-07T09:54:19.3533818Z triton_convolution2d_499 0.0420 ms 53.7% 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 2025-09-07T09:54:19.3535294Z triton_convolution2d_502 0.0440 ms 51.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.3536773Z triton_convolution2d_496 0.0451 ms 50.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.3538246Z triton_convolution2d_497 0.0584 ms 38.6% 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 2025-09-07T09:54:19.3539732Z triton_convolution2d_498 0.0717 ms 31.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:19.3541194Z SingleProcess AUTOTUNE benchmarking takes 0.1764 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:19.5583981Z Autotune Choices Stats: 2025-09-07T09:54:19.5585742Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.028672000393271446, "best_triton_kernel": "triton_convolution2d_514", "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"} 2025-09-07T09:54:19.5649963Z AUTOTUNE convolution(4x800x14x14, 128x800x1x1) 2025-09-07T09:54:19.5650353Z strides: [156800, 196, 14, 1], [800, 1, 1, 1] 2025-09-07T09:54:19.5650752Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:19.5651082Z convolution 0.0225 ms 100.0% 2025-09-07T09:54:19.5651985Z triton_convolution2d_514 0.0287 ms 78.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.5653713Z triton_convolution2d_515 0.0348 ms 64.7% 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 2025-09-07T09:54:19.5654631Z conv1x1_via_mm 0.0358 ms 62.9% 2025-09-07T09:54:19.5655513Z triton_convolution2d_513 0.0430 ms 52.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.5657008Z triton_convolution2d_516 0.0451 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.5658823Z triton_convolution2d_510 0.0461 ms 48.9% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.5660332Z triton_convolution2d_511 0.0543 ms 41.5% 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 2025-09-07T09:54:19.5661821Z triton_convolution2d_512 0.0737 ms 30.6% 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 2025-09-07T09:54:19.5662983Z SingleProcess AUTOTUNE benchmarking takes 0.1771 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:19.7751430Z Autotune Choices Stats: 2025-09-07T09:54:19.7753165Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.02969600073993206, "best_triton_kernel": "triton_convolution2d_528", "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"} 2025-09-07T09:54:19.7819231Z AUTOTUNE convolution(4x832x14x14, 128x832x1x1) 2025-09-07T09:54:19.7819670Z strides: [163072, 196, 14, 1], [832, 1, 1, 1] 2025-09-07T09:54:19.7820017Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:19.7820361Z convolution 0.0225 ms 100.0% 2025-09-07T09:54:19.7821253Z triton_convolution2d_528 0.0297 ms 75.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.7822184Z conv1x1_via_mm 0.0358 ms 62.9% 2025-09-07T09:54:19.7823428Z triton_convolution2d_529 0.0358 ms 62.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.7825013Z triton_convolution2d_527 0.0451 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 2025-09-07T09:54:19.7826504Z triton_convolution2d_530 0.0461 ms 48.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.7827989Z triton_convolution2d_524 0.0481 ms 46.8% 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 2025-09-07T09:54:19.7829492Z triton_convolution2d_525 0.0625 ms 36.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.7830971Z triton_convolution2d_526 0.0768 ms 29.3% 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 2025-09-07T09:54:19.7832149Z SingleProcess AUTOTUNE benchmarking takes 0.1810 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:19.9710027Z Autotune Choices Stats: 2025-09-07T09:54:19.9711717Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023552000522613525, "best_triton_pos": 1, "best_triton_time": 0.030719999223947525, "best_triton_kernel": "triton_convolution2d_542", "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"} 2025-09-07T09:54:19.9778130Z AUTOTUNE convolution(4x864x14x14, 128x864x1x1) 2025-09-07T09:54:19.9778507Z strides: [169344, 196, 14, 1], [864, 1, 1, 1] 2025-09-07T09:54:19.9778853Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:19.9779174Z convolution 0.0236 ms 100.0% 2025-09-07T09:54:19.9780052Z triton_convolution2d_542 0.0307 ms 76.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.9780948Z conv1x1_via_mm 0.0369 ms 63.9% 2025-09-07T09:54:19.9781835Z triton_convolution2d_543 0.0369 ms 63.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.9783335Z triton_convolution2d_541 0.0461 ms 51.1% 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 2025-09-07T09:54:19.9784875Z triton_convolution2d_544 0.0471 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:19.9786360Z triton_convolution2d_538 0.0492 ms 47.9% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:19.9787830Z triton_convolution2d_539 0.0584 ms 40.4% 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 2025-09-07T09:54:19.9789530Z triton_convolution2d_540 0.0788 ms 29.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:19.9790693Z SingleProcess AUTOTUNE benchmarking takes 0.1813 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:20.1912349Z Autotune Choices Stats: 2025-09-07T09:54:20.1914038Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.03174399957060814, "best_triton_kernel": "triton_convolution2d_556", "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"} 2025-09-07T09:54:20.1977668Z AUTOTUNE convolution(4x896x14x14, 128x896x1x1) 2025-09-07T09:54:20.1978051Z strides: [175616, 196, 14, 1], [896, 1, 1, 1] 2025-09-07T09:54:20.1978417Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:20.1978733Z convolution 0.0225 ms 100.0% 2025-09-07T09:54:20.1979634Z triton_convolution2d_556 0.0317 ms 71.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.1980538Z conv1x1_via_mm 0.0379 ms 59.5% 2025-09-07T09:54:20.1981429Z triton_convolution2d_557 0.0379 ms 59.5% 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 2025-09-07T09:54:20.1982910Z triton_convolution2d_555 0.0471 ms 47.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:20.1984394Z triton_convolution2d_558 0.0492 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 2025-09-07T09:54:20.1986250Z triton_convolution2d_552 0.0512 ms 44.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.1987724Z triton_convolution2d_553 0.0655 ms 34.4% 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 2025-09-07T09:54:20.1989207Z triton_convolution2d_554 0.0819 ms 27.5% 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 2025-09-07T09:54:20.1990380Z SingleProcess AUTOTUNE benchmarking takes 0.1839 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:20.3889121Z Autotune Choices Stats: 2025-09-07T09:54:20.3890738Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02252800017595291, "best_triton_pos": 1, "best_triton_time": 0.03276799991726875, "best_triton_kernel": "triton_convolution2d_570", "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"} 2025-09-07T09:54:20.3959921Z AUTOTUNE convolution(4x928x14x14, 128x928x1x1) 2025-09-07T09:54:20.3960296Z strides: [181888, 196, 14, 1], [928, 1, 1, 1] 2025-09-07T09:54:20.3960645Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:20.3960971Z convolution 0.0225 ms 100.0% 2025-09-07T09:54:20.3961851Z triton_convolution2d_570 0.0328 ms 68.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.3962755Z conv1x1_via_mm 0.0389 ms 57.9% 2025-09-07T09:54:20.3963887Z triton_convolution2d_571 0.0389 ms 57.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:20.3965392Z triton_convolution2d_569 0.0492 ms 45.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:20.3966882Z triton_convolution2d_572 0.0502 ms 44.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:20.3968363Z triton_convolution2d_566 0.0522 ms 43.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.3969853Z triton_convolution2d_567 0.0614 ms 36.7% 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 2025-09-07T09:54:20.3971342Z triton_convolution2d_568 0.0840 ms 26.8% 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 2025-09-07T09:54:20.3972518Z SingleProcess AUTOTUNE benchmarking takes 0.1840 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:20.5870578Z Autotune Choices Stats: 2025-09-07T09:54:20.5872235Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023552000522613525, "best_triton_pos": 1, "best_triton_time": 0.03379200026392937, "best_triton_kernel": "triton_convolution2d_584", "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"} 2025-09-07T09:54:20.5936727Z AUTOTUNE convolution(4x960x14x14, 128x960x1x1) 2025-09-07T09:54:20.5937138Z strides: [188160, 196, 14, 1], [960, 1, 1, 1] 2025-09-07T09:54:20.5937469Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:20.5937790Z convolution 0.0236 ms 100.0% 2025-09-07T09:54:20.5938657Z triton_convolution2d_584 0.0338 ms 69.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.5939553Z conv1x1_via_mm 0.0379 ms 62.2% 2025-09-07T09:54:20.5940431Z triton_convolution2d_585 0.0410 ms 57.5% 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 2025-09-07T09:54:20.5941925Z triton_convolution2d_583 0.0502 ms 46.9% 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 2025-09-07T09:54:20.5943407Z triton_convolution2d_586 0.0522 ms 45.1% 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 2025-09-07T09:54:20.5944946Z triton_convolution2d_580 0.0543 ms 43.4% 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 2025-09-07T09:54:20.5946428Z triton_convolution2d_581 0.0707 ms 33.3% 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 2025-09-07T09:54:20.5948124Z triton_convolution2d_582 0.0870 ms 27.1% 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 2025-09-07T09:54:20.5956535Z SingleProcess AUTOTUNE benchmarking takes 0.1832 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:20.7826237Z Autotune Choices Stats: 2025-09-07T09:54:20.7827902Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023552000522613525, "best_triton_pos": 1, "best_triton_time": 0.03379200026392937, "best_triton_kernel": "triton_convolution2d_598", "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"} 2025-09-07T09:54:20.7889897Z AUTOTUNE convolution(4x992x14x14, 128x992x1x1) 2025-09-07T09:54:20.7890271Z strides: [194432, 196, 14, 1], [992, 1, 1, 1] 2025-09-07T09:54:20.7890653Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:20.7890973Z convolution 0.0236 ms 100.0% 2025-09-07T09:54:20.7891867Z triton_convolution2d_598 0.0338 ms 69.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.7892774Z conv1x1_via_mm 0.0389 ms 60.5% 2025-09-07T09:54:20.7893861Z triton_convolution2d_599 0.0410 ms 57.5% 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 2025-09-07T09:54:20.7895361Z triton_convolution2d_597 0.0512 ms 46.0% 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 2025-09-07T09:54:20.7896848Z triton_convolution2d_600 0.0532 ms 44.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:20.7898699Z triton_convolution2d_594 0.0553 ms 42.6% 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 2025-09-07T09:54:20.7900181Z triton_convolution2d_595 0.0655 ms 35.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.7901660Z triton_convolution2d_596 0.0891 ms 26.4% 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 2025-09-07T09:54:20.7902832Z SingleProcess AUTOTUNE benchmarking takes 0.1804 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:20.9636098Z Autotune Choices Stats: 2025-09-07T09:54:20.9637768Z {"num_choices": 9, "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_619", "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"} 2025-09-07T09:54:20.9700756Z AUTOTUNE convolution(4x512x7x7, 128x512x1x1) 2025-09-07T09:54:20.9701103Z strides: [25088, 49, 7, 1], [512, 1, 1, 1] 2025-09-07T09:54:20.9701452Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:20.9701771Z convolution 0.0133 ms 100.0% 2025-09-07T09:54:20.9702650Z triton_convolution2d_619 0.0215 ms 61.9% 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 2025-09-07T09:54:20.9704419Z triton_convolution2d_620 0.0246 ms 54.2% 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 2025-09-07T09:54:20.9705405Z conv1x1_via_mm 0.0256 ms 52.0% 2025-09-07T09:54:20.9706293Z triton_convolution2d_618 0.0307 ms 43.3% 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 2025-09-07T09:54:20.9707785Z triton_convolution2d_615 0.0328 ms 40.6% 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 2025-09-07T09:54:20.9709262Z triton_convolution2d_617 0.0369 ms 36.1% 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 2025-09-07T09:54:20.9710744Z triton_convolution2d_621 0.0369 ms 36.1% 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 2025-09-07T09:54:20.9712216Z triton_convolution2d_616 0.0451 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:20.9713376Z SingleProcess AUTOTUNE benchmarking takes 0.1630 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:54:21.3914747Z Autotune Choices Stats: 2025-09-07T09:54:21.3916451Z {"num_choices": 9, "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_633", "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"} 2025-09-07T09:54:21.3976932Z AUTOTUNE convolution(4x544x7x7, 128x544x1x1) 2025-09-07T09:54:21.3977302Z strides: [26656, 49, 7, 1], [544, 1, 1, 1] 2025-09-07T09:54:21.3977634Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:21.3977951Z convolution 0.0154 ms 100.0% 2025-09-07T09:54:21.3978813Z triton_convolution2d_633 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:21.3979721Z conv1x1_via_mm 0.0246 ms 62.5% 2025-09-07T09:54:21.3980601Z triton_convolution2d_634 0.0256 ms 60.0% 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 2025-09-07T09:54:21.3982093Z triton_convolution2d_632 0.0328 ms 46.9% 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 2025-09-07T09:54:21.3983579Z triton_convolution2d_629 0.0358 ms 42.9% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:21.3985109Z triton_convolution2d_631 0.0379 ms 40.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:21.3986599Z triton_convolution2d_635 0.0389 ms 39.5% 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 2025-09-07T09:54:21.3988270Z triton_convolution2d_630 0.0471 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:21.3989452Z SingleProcess AUTOTUNE benchmarking takes 0.1629 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:21.6001815Z Autotune Choices Stats: 2025-09-07T09:54:21.6003463Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.02252800017595291, "best_triton_kernel": "triton_convolution2d_647", "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"} 2025-09-07T09:54:21.6065560Z AUTOTUNE convolution(4x576x7x7, 128x576x1x1) 2025-09-07T09:54:21.6065917Z strides: [28224, 49, 7, 1], [576, 1, 1, 1] 2025-09-07T09:54:21.6066290Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:21.6066610Z convolution 0.0154 ms 100.0% 2025-09-07T09:54:21.6067499Z triton_convolution2d_647 0.0225 ms 68.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:21.6068403Z conv1x1_via_mm 0.0236 ms 65.2% 2025-09-07T09:54:21.6069273Z triton_convolution2d_648 0.0266 ms 57.7% 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 2025-09-07T09:54:21.6070755Z triton_convolution2d_646 0.0338 ms 45.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:21.6072233Z triton_convolution2d_643 0.0379 ms 40.5% 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 2025-09-07T09:54:21.6074002Z triton_convolution2d_645 0.0399 ms 38.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:21.6075488Z triton_convolution2d_649 0.0399 ms 38.5% 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 2025-09-07T09:54:21.6076975Z triton_convolution2d_644 0.0492 ms 31.2% 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 2025-09-07T09:54:21.6078150Z SingleProcess AUTOTUNE benchmarking takes 0.1657 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:21.7830835Z Autotune Choices Stats: 2025-09-07T09:54:21.7832510Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 1, "best_triton_time": 0.023552000522613525, "best_triton_kernel": "triton_convolution2d_661", "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"} 2025-09-07T09:54:21.7895287Z AUTOTUNE convolution(4x608x7x7, 128x608x1x1) 2025-09-07T09:54:21.7895679Z strides: [29792, 49, 7, 1], [608, 1, 1, 1] 2025-09-07T09:54:21.7896032Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:21.7896350Z convolution 0.0154 ms 100.0% 2025-09-07T09:54:21.7897221Z triton_convolution2d_661 0.0236 ms 65.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:21.7898138Z conv1x1_via_mm 0.0246 ms 62.5% 2025-09-07T09:54:21.7899332Z triton_convolution2d_662 0.0276 ms 55.6% 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 2025-09-07T09:54:21.7900833Z triton_convolution2d_660 0.0358 ms 42.9% 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 2025-09-07T09:54:21.7902317Z triton_convolution2d_657 0.0389 ms 39.5% 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 2025-09-07T09:54:21.7903801Z triton_convolution2d_663 0.0420 ms 36.6% 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 2025-09-07T09:54:21.7905377Z triton_convolution2d_659 0.0430 ms 35.7% 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 2025-09-07T09:54:21.7906863Z triton_convolution2d_658 0.0512 ms 30.0% 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 2025-09-07T09:54:21.7908018Z SingleProcess AUTOTUNE benchmarking takes 0.1689 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:21.9662330Z Autotune Choices Stats: 2025-09-07T09:54:21.9663990Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015359999611973763, "best_triton_pos": 2, "best_triton_time": 0.02457600086927414, "best_triton_kernel": "triton_convolution2d_675", "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"} 2025-09-07T09:54:21.9727118Z AUTOTUNE convolution(4x640x7x7, 128x640x1x1) 2025-09-07T09:54:21.9727492Z strides: [31360, 49, 7, 1], [640, 1, 1, 1] 2025-09-07T09:54:21.9727830Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:21.9728157Z convolution 0.0154 ms 100.0% 2025-09-07T09:54:21.9728453Z conv1x1_via_mm 0.0236 ms 65.2% 2025-09-07T09:54:21.9729334Z triton_convolution2d_675 0.0246 ms 62.5% 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 2025-09-07T09:54:21.9730817Z triton_convolution2d_676 0.0287 ms 53.6% 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 2025-09-07T09:54:21.9732313Z triton_convolution2d_674 0.0369 ms 41.7% 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 2025-09-07T09:54:21.9734040Z triton_convolution2d_671 0.0399 ms 38.5% 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 2025-09-07T09:54:21.9735506Z triton_convolution2d_677 0.0440 ms 34.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:21.9736983Z triton_convolution2d_673 0.0451 ms 34.1% 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 2025-09-07T09:54:21.9738681Z triton_convolution2d_672 0.0543 ms 28.3% 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 2025-09-07T09:54:21.9739856Z SingleProcess AUTOTUNE benchmarking takes 0.1690 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:22.1494243Z Autotune Choices Stats: 2025-09-07T09:54:22.1495919Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 2, "best_triton_time": 0.025599999353289604, "best_triton_kernel": "triton_convolution2d_689", "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"} 2025-09-07T09:54:22.1559137Z AUTOTUNE convolution(4x672x7x7, 128x672x1x1) 2025-09-07T09:54:22.1559539Z strides: [32928, 49, 7, 1], [672, 1, 1, 1] 2025-09-07T09:54:22.1559905Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:22.1560213Z convolution 0.0174 ms 100.0% 2025-09-07T09:54:22.1560503Z conv1x1_via_mm 0.0246 ms 70.8% 2025-09-07T09:54:22.1561399Z triton_convolution2d_689 0.0256 ms 68.0% 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 2025-09-07T09:54:22.1562880Z triton_convolution2d_690 0.0297 ms 58.6% 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 2025-09-07T09:54:22.1564372Z triton_convolution2d_688 0.0379 ms 45.9% 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 2025-09-07T09:54:22.1565860Z triton_convolution2d_685 0.0420 ms 41.5% 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 2025-09-07T09:54:22.1567613Z triton_convolution2d_691 0.0461 ms 37.8% 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 2025-09-07T09:54:22.1569098Z triton_convolution2d_687 0.0471 ms 37.0% 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 2025-09-07T09:54:22.1570580Z triton_convolution2d_686 0.0563 ms 30.9% 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 2025-09-07T09:54:22.1571752Z SingleProcess AUTOTUNE benchmarking takes 0.1691 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:22.3331927Z Autotune Choices Stats: 2025-09-07T09:54:22.3333814Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 2, "best_triton_time": 0.026623999699950218, "best_triton_kernel": "triton_convolution2d_703", "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"} 2025-09-07T09:54:22.3396403Z AUTOTUNE convolution(4x704x7x7, 128x704x1x1) 2025-09-07T09:54:22.3396762Z strides: [34496, 49, 7, 1], [704, 1, 1, 1] 2025-09-07T09:54:22.3397087Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:22.3397410Z convolution 0.0174 ms 100.0% 2025-09-07T09:54:22.3397703Z conv1x1_via_mm 0.0246 ms 70.8% 2025-09-07T09:54:22.3398583Z triton_convolution2d_703 0.0266 ms 65.4% 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 2025-09-07T09:54:22.3400341Z triton_convolution2d_704 0.0297 ms 58.6% 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 2025-09-07T09:54:22.3401838Z triton_convolution2d_702 0.0389 ms 44.7% 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 2025-09-07T09:54:22.3403320Z triton_convolution2d_699 0.0440 ms 39.5% 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 2025-09-07T09:54:22.3404799Z triton_convolution2d_705 0.0471 ms 37.0% 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 2025-09-07T09:54:22.3406291Z triton_convolution2d_701 0.0481 ms 36.2% 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 2025-09-07T09:54:22.3407777Z triton_convolution2d_700 0.0584 ms 29.8% 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 2025-09-07T09:54:22.3408942Z SingleProcess AUTOTUNE benchmarking takes 0.1694 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:22.5169576Z Autotune Choices Stats: 2025-09-07T09:54:22.5171246Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 2, "best_triton_time": 0.026623999699950218, "best_triton_kernel": "triton_convolution2d_717", "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"} 2025-09-07T09:54:22.5233727Z AUTOTUNE convolution(4x736x7x7, 128x736x1x1) 2025-09-07T09:54:22.5234117Z strides: [36064, 49, 7, 1], [736, 1, 1, 1] 2025-09-07T09:54:22.5234456Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:22.5234777Z convolution 0.0174 ms 100.0% 2025-09-07T09:54:22.5235070Z conv1x1_via_mm 0.0246 ms 70.8% 2025-09-07T09:54:22.5235943Z triton_convolution2d_717 0.0266 ms 65.4% 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 2025-09-07T09:54:22.5237434Z triton_convolution2d_718 0.0317 ms 54.8% 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 2025-09-07T09:54:22.5238940Z triton_convolution2d_716 0.0410 ms 42.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:22.5240428Z triton_convolution2d_713 0.0451 ms 38.6% 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 2025-09-07T09:54:22.5241910Z triton_convolution2d_715 0.0502 ms 34.7% 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 2025-09-07T09:54:22.5243397Z triton_convolution2d_719 0.0502 ms 34.7% 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 2025-09-07T09:54:22.5245177Z triton_convolution2d_714 0.0604 ms 28.8% 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 2025-09-07T09:54:22.5246358Z SingleProcess AUTOTUNE benchmarking takes 0.1697 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:22.7015493Z Autotune Choices Stats: 2025-09-07T09:54:22.7017148Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016383999958634377, "best_triton_pos": 2, "best_triton_time": 0.027648000046610832, "best_triton_kernel": "triton_convolution2d_731", "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"} 2025-09-07T09:54:22.7081986Z AUTOTUNE convolution(4x768x7x7, 128x768x1x1) 2025-09-07T09:54:22.7082357Z strides: [37632, 49, 7, 1], [768, 1, 1, 1] 2025-09-07T09:54:22.7082725Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:22.7083035Z convolution 0.0164 ms 100.0% 2025-09-07T09:54:22.7083333Z conv1x1_via_mm 0.0246 ms 66.7% 2025-09-07T09:54:22.7084236Z triton_convolution2d_731 0.0276 ms 59.3% 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 2025-09-07T09:54:22.7085718Z triton_convolution2d_732 0.0328 ms 50.0% 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 2025-09-07T09:54:22.7087202Z triton_convolution2d_730 0.0420 ms 39.0% 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 2025-09-07T09:54:22.7088673Z triton_convolution2d_727 0.0471 ms 34.8% 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 2025-09-07T09:54:22.7090416Z triton_convolution2d_733 0.0512 ms 32.0% 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 2025-09-07T09:54:22.7091898Z triton_convolution2d_729 0.0522 ms 31.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:22.7093638Z triton_convolution2d_728 0.0625 ms 26.2% 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 2025-09-07T09:54:22.7094817Z SingleProcess AUTOTUNE benchmarking takes 0.1709 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:22.8882362Z Autotune Choices Stats: 2025-09-07T09:54:22.8884039Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 2, "best_triton_time": 0.028672000393271446, "best_triton_kernel": "triton_convolution2d_745", "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"} 2025-09-07T09:54:22.8952247Z AUTOTUNE convolution(4x800x7x7, 128x800x1x1) 2025-09-07T09:54:22.8952630Z strides: [39200, 49, 7, 1], [800, 1, 1, 1] 2025-09-07T09:54:22.8952956Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:22.8953273Z convolution 0.0184 ms 100.0% 2025-09-07T09:54:22.8953562Z conv1x1_via_mm 0.0246 ms 75.0% 2025-09-07T09:54:22.8954443Z triton_convolution2d_745 0.0287 ms 64.3% 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 2025-09-07T09:54:22.8956187Z triton_convolution2d_746 0.0338 ms 54.5% 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 2025-09-07T09:54:22.8957689Z triton_convolution2d_744 0.0430 ms 42.9% 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 2025-09-07T09:54:22.8959187Z triton_convolution2d_741 0.0481 ms 38.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:22.8960660Z triton_convolution2d_747 0.0522 ms 35.3% 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 2025-09-07T09:54:22.8962141Z triton_convolution2d_743 0.0543 ms 34.0% 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 2025-09-07T09:54:22.8963615Z triton_convolution2d_742 0.0645 ms 28.6% 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 2025-09-07T09:54:22.8964777Z SingleProcess AUTOTUNE benchmarking takes 0.1727 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:23.0761528Z Autotune Choices Stats: 2025-09-07T09:54:23.0763162Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 2, "best_triton_time": 0.02969600073993206, "best_triton_kernel": "triton_convolution2d_759", "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"} 2025-09-07T09:54:23.0829165Z AUTOTUNE convolution(4x832x7x7, 128x832x1x1) 2025-09-07T09:54:23.0829552Z strides: [40768, 49, 7, 1], [832, 1, 1, 1] 2025-09-07T09:54:23.0829875Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:23.0830198Z convolution 0.0184 ms 100.0% 2025-09-07T09:54:23.0830493Z conv1x1_via_mm 0.0256 ms 72.0% 2025-09-07T09:54:23.0831378Z triton_convolution2d_759 0.0297 ms 62.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:23.0832860Z triton_convolution2d_760 0.0338 ms 54.5% 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 2025-09-07T09:54:23.0834366Z triton_convolution2d_758 0.0440 ms 41.9% 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 2025-09-07T09:54:23.0835854Z triton_convolution2d_755 0.0492 ms 37.5% 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 2025-09-07T09:54:23.0837327Z triton_convolution2d_761 0.0543 ms 34.0% 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 2025-09-07T09:54:23.0838809Z triton_convolution2d_757 0.0563 ms 32.7% 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 2025-09-07T09:54:23.0840545Z triton_convolution2d_756 0.0666 ms 27.7% 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 2025-09-07T09:54:23.0841710Z SingleProcess AUTOTUNE benchmarking takes 0.1735 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:23.2659328Z Autotune Choices Stats: 2025-09-07T09:54:23.2660978Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01945599913597107, "best_triton_pos": 2, "best_triton_time": 0.030719999223947525, "best_triton_kernel": "triton_convolution2d_773", "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"} 2025-09-07T09:54:23.2725326Z AUTOTUNE convolution(4x864x7x7, 128x864x1x1) 2025-09-07T09:54:23.2725745Z strides: [42336, 49, 7, 1], [864, 1, 1, 1] 2025-09-07T09:54:23.2726107Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:23.2726414Z convolution 0.0195 ms 100.0% 2025-09-07T09:54:23.2726706Z conv1x1_via_mm 0.0256 ms 76.0% 2025-09-07T09:54:23.2727596Z triton_convolution2d_773 0.0307 ms 63.3% 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 2025-09-07T09:54:23.2729073Z triton_convolution2d_774 0.0348 ms 55.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:23.2730561Z triton_convolution2d_772 0.0461 ms 42.2% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:23.2732048Z triton_convolution2d_769 0.0512 ms 38.0% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:23.2733994Z triton_convolution2d_775 0.0563 ms 34.5% 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 2025-09-07T09:54:23.2735474Z triton_convolution2d_771 0.0584 ms 33.3% 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 2025-09-07T09:54:23.2736943Z triton_convolution2d_770 0.0696 ms 27.9% 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 2025-09-07T09:54:23.2738118Z SingleProcess AUTOTUNE benchmarking takes 0.1753 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:23.4555552Z Autotune Choices Stats: 2025-09-07T09:54:23.4557233Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018432000651955605, "best_triton_pos": 2, "best_triton_time": 0.030719999223947525, "best_triton_kernel": "triton_convolution2d_787", "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"} 2025-09-07T09:54:23.4622158Z AUTOTUNE convolution(4x896x7x7, 128x896x1x1) 2025-09-07T09:54:23.4622536Z strides: [43904, 49, 7, 1], [896, 1, 1, 1] 2025-09-07T09:54:23.4622858Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:23.4623175Z convolution 0.0184 ms 100.0% 2025-09-07T09:54:23.4623467Z conv1x1_via_mm 0.0256 ms 72.0% 2025-09-07T09:54:23.4624362Z triton_convolution2d_787 0.0307 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 2025-09-07T09:54:23.4626172Z triton_convolution2d_788 0.0358 ms 51.4% 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 2025-09-07T09:54:23.4627658Z triton_convolution2d_786 0.0471 ms 39.1% 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 2025-09-07T09:54:23.4629152Z triton_convolution2d_783 0.0522 ms 35.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:23.4630629Z triton_convolution2d_789 0.0573 ms 32.1% 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 2025-09-07T09:54:23.4632116Z triton_convolution2d_785 0.0594 ms 31.0% 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 2025-09-07T09:54:23.4633600Z triton_convolution2d_784 0.0707 ms 26.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:23.4634773Z SingleProcess AUTOTUNE benchmarking takes 0.1752 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:23.6470881Z Autotune Choices Stats: 2025-09-07T09:54:23.6472534Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021503999829292297, "best_triton_pos": 2, "best_triton_time": 0.03276799991726875, "best_triton_kernel": "triton_convolution2d_801", "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"} 2025-09-07T09:54:23.6537354Z AUTOTUNE convolution(4x928x7x7, 128x928x1x1) 2025-09-07T09:54:23.6537716Z strides: [45472, 49, 7, 1], [928, 1, 1, 1] 2025-09-07T09:54:23.6538057Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:23.6538367Z convolution 0.0215 ms 100.0% 2025-09-07T09:54:23.6538657Z conv1x1_via_mm 0.0266 ms 80.8% 2025-09-07T09:54:23.6539544Z triton_convolution2d_801 0.0328 ms 65.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:23.6541034Z triton_convolution2d_802 0.0369 ms 58.3% 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 2025-09-07T09:54:23.6542542Z triton_convolution2d_800 0.0481 ms 44.7% 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 2025-09-07T09:54:23.6544034Z triton_convolution2d_797 0.0543 ms 39.6% 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 2025-09-07T09:54:23.6545588Z triton_convolution2d_803 0.0604 ms 35.6% 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 2025-09-07T09:54:23.6547077Z triton_convolution2d_799 0.0625 ms 34.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:54:23.6548760Z triton_convolution2d_798 0.0737 ms 29.2% 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 2025-09-07T09:54:23.6549939Z SingleProcess AUTOTUNE benchmarking takes 0.1772 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:23.8405297Z Autotune Choices Stats: 2025-09-07T09:54:23.8406947Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 2, "best_triton_time": 0.03276799991726875, "best_triton_kernel": "triton_convolution2d_815", "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"} 2025-09-07T09:54:23.8474839Z AUTOTUNE convolution(4x960x7x7, 128x960x1x1) 2025-09-07T09:54:23.8475218Z strides: [47040, 49, 7, 1], [960, 1, 1, 1] 2025-09-07T09:54:23.8475570Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:23.8475893Z convolution 0.0205 ms 100.0% 2025-09-07T09:54:23.8476184Z conv1x1_via_mm 0.0256 ms 80.0% 2025-09-07T09:54:23.8477079Z triton_convolution2d_815 0.0328 ms 62.5% 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 2025-09-07T09:54:23.8478549Z triton_convolution2d_816 0.0379 ms 54.1% 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 2025-09-07T09:54:23.8480032Z triton_convolution2d_814 0.0492 ms 41.7% 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 2025-09-07T09:54:23.8481512Z triton_convolution2d_811 0.0563 ms 36.4% 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 2025-09-07T09:54:23.8483263Z triton_convolution2d_817 0.0614 ms 33.3% 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 2025-09-07T09:54:23.8484748Z triton_convolution2d_813 0.0635 ms 32.3% 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 2025-09-07T09:54:23.8486321Z triton_convolution2d_812 0.0758 ms 27.0% 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 2025-09-07T09:54:23.8487488Z SingleProcess AUTOTUNE benchmarking takes 0.1794 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:24.0344974Z Autotune Choices Stats: 2025-09-07T09:54:24.0346664Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020479999482631683, "best_triton_pos": 2, "best_triton_time": 0.03379200026392937, "best_triton_kernel": "triton_convolution2d_829", "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"} 2025-09-07T09:54:24.0414751Z AUTOTUNE convolution(4x992x7x7, 128x992x1x1) 2025-09-07T09:54:24.0415131Z strides: [48608, 49, 7, 1], [992, 1, 1, 1] 2025-09-07T09:54:24.0415469Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:24.0415789Z convolution 0.0205 ms 100.0% 2025-09-07T09:54:24.0416082Z conv1x1_via_mm 0.0256 ms 80.0% 2025-09-07T09:54:24.0416966Z triton_convolution2d_829 0.0338 ms 60.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:24.0418815Z triton_convolution2d_830 0.0389 ms 52.6% 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 2025-09-07T09:54:24.0420316Z triton_convolution2d_828 0.0502 ms 40.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:24.0421802Z triton_convolution2d_825 0.0573 ms 35.7% 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 2025-09-07T09:54:24.0423278Z triton_convolution2d_831 0.0635 ms 32.3% 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 2025-09-07T09:54:24.0424844Z triton_convolution2d_827 0.0666 ms 30.8% 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=1, num_warps=8 2025-09-07T09:54:24.0426322Z triton_convolution2d_826 0.0778 ms 26.3% 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 2025-09-07T09:54:24.0427496Z SingleProcess AUTOTUNE benchmarking takes 0.1796 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:25.6154152Z Autotune Choices Stats: 2025-09-07T09:54:25.6155838Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03993599861860275, "best_triton_pos": 1, "best_triton_time": 0.04608000069856644, "best_triton_kernel": "triton_convolution2d_18", "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=8"} 2025-09-07T09:54:25.6224250Z AUTOTUNE convolution(4x128x56x56, 32x128x3x3) 2025-09-07T09:54:25.6224653Z strides: [401408, 3136, 56, 1], [1152, 9, 3, 1] 2025-09-07T09:54:25.6225038Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:25.6225359Z convolution 0.0399 ms 100.0% 2025-09-07T09:54:25.6226246Z triton_convolution2d_18 0.0461 ms 86.7% 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=8 2025-09-07T09:54:25.6227729Z triton_convolution2d_16 0.0522 ms 76.5% 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 2025-09-07T09:54:25.6229198Z triton_convolution2d_17 0.0543 ms 73.6% 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 2025-09-07T09:54:25.6230677Z triton_convolution2d_13 0.0573 ms 69.6% 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 2025-09-07T09:54:25.6232125Z triton_convolution2d_14 0.0707 ms 56.5% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:25.6233598Z triton_convolution2d_19 0.0717 ms 55.7% 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 2025-09-07T09:54:25.6235076Z triton_convolution2d_15 0.1792 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=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:54:25.6236554Z SingleProcess AUTOTUNE benchmarking takes 0.1639 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:54:25.7865210Z Autotune Choices Stats: 2025-09-07T09:54:25.7866518Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_94", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.018432000651955605, "best_triton_pos": 0} 2025-09-07T09:54:25.7933689Z AUTOTUNE convolution(4x256x56x56, 128x256x1x1) 2025-09-07T09:54:25.7934072Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:54:25.7934419Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:25.7935324Z triton_convolution2d_94 0.0184 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 2025-09-07T09:54:25.7936854Z triton_convolution2d_95 0.0184 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 2025-09-07T09:54:25.7938348Z triton_convolution2d_93 0.0205 ms 90.0% 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 2025-09-07T09:54:25.7939826Z triton_convolution2d_96 0.0205 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:25.7941291Z triton_convolution2d_90 0.0236 ms 78.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:25.7943000Z triton_convolution2d_91 0.0256 ms 72.0% 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 2025-09-07T09:54:25.7944482Z triton_convolution2d_92 0.0328 ms 56.3% 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 2025-09-07T09:54:25.7945488Z convolution 0.0369 ms 50.0% 2025-09-07T09:54:25.7945796Z conv1x1_via_mm 0.0840 ms 22.0% 2025-09-07T09:54:25.7946370Z SingleProcess AUTOTUNE benchmarking takes 0.1566 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:25.9356954Z Autotune Choices Stats: 2025-09-07T09:54:25.9358604Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.027648000046610832, "best_triton_pos": 1, "best_triton_time": 0.030719999223947525, "best_triton_kernel": "triton_convolution2d_109", "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=8"} 2025-09-07T09:54:25.9426338Z AUTOTUNE convolution(4x128x28x28, 32x128x3x3) 2025-09-07T09:54:25.9426751Z strides: [100352, 784, 28, 1], [1152, 9, 3, 1] 2025-09-07T09:54:25.9427103Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:25.9427422Z convolution 0.0276 ms 100.0% 2025-09-07T09:54:25.9428295Z triton_convolution2d_109 0.0307 ms 90.0% 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 2025-09-07T09:54:25.9429774Z triton_convolution2d_108 0.0379 ms 73.0% 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=4 2025-09-07T09:54:25.9431547Z triton_convolution2d_107 0.0389 ms 71.1% 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 2025-09-07T09:54:25.9433039Z triton_convolution2d_104 0.0471 ms 58.7% 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 2025-09-07T09:54:25.9434511Z triton_convolution2d_110 0.0584 ms 47.4% 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 2025-09-07T09:54:25.9435996Z triton_convolution2d_105 0.0676 ms 40.9% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:25.9437499Z triton_convolution2d_106 0.1331 ms 20.8% 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 2025-09-07T09:54:25.9438679Z SingleProcess AUTOTUNE benchmarking takes 0.1487 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:54:26.1338597Z Autotune Choices Stats: 2025-09-07T09:54:26.1340247Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01740800030529499, "best_triton_pos": 1, "best_triton_time": 0.023552000522613525, "best_triton_kernel": "triton_convolution2d_269", "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"} 2025-09-07T09:54:26.1408127Z AUTOTUNE convolution(4x512x28x28, 256x512x1x1) 2025-09-07T09:54:26.1408526Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:54:26.1408878Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:26.1409203Z convolution 0.0174 ms 100.0% 2025-09-07T09:54:26.1410085Z triton_convolution2d_269 0.0236 ms 73.9% 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 2025-09-07T09:54:26.1411573Z triton_convolution2d_268 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 2025-09-07T09:54:26.1413279Z triton_convolution2d_271 0.0317 ms 54.8% 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 2025-09-07T09:54:26.1414780Z triton_convolution2d_270 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 2025-09-07T09:54:26.1416270Z triton_convolution2d_266 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 2025-09-07T09:54:26.1417749Z triton_convolution2d_265 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 2025-09-07T09:54:26.1419226Z triton_convolution2d_267 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 2025-09-07T09:54:26.1420125Z conv1x1_via_mm 0.0655 ms 26.6% 2025-09-07T09:54:26.1420695Z SingleProcess AUTOTUNE benchmarking takes 0.1648 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:26.2809628Z Autotune Choices Stats: 2025-09-07T09:54:26.2811689Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026623999699950218, "best_triton_pos": 1, "best_triton_time": 0.026623999699950218, "best_triton_kernel": "triton_convolution2d_283", "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"} 2025-09-07T09:54:26.2878147Z AUTOTUNE convolution(4x128x14x14, 32x128x3x3) 2025-09-07T09:54:26.2878524Z strides: [25088, 196, 14, 1], [1152, 9, 3, 1] 2025-09-07T09:54:26.2878855Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:26.2879181Z convolution 0.0266 ms 100.0% 2025-09-07T09:54:26.2880066Z triton_convolution2d_283 0.0266 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=4 2025-09-07T09:54:26.2881575Z triton_convolution2d_284 0.0297 ms 89.7% 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=8 2025-09-07T09:54:26.2883050Z triton_convolution2d_282 0.0420 ms 63.4% 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 2025-09-07T09:54:26.2884537Z triton_convolution2d_279 0.0440 ms 60.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:26.2886001Z triton_convolution2d_285 0.0543 ms 49.1% 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 2025-09-07T09:54:26.2887698Z triton_convolution2d_280 0.0655 ms 40.6% 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 2025-09-07T09:54:26.2889186Z triton_convolution2d_281 0.1249 ms 21.3% 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 2025-09-07T09:54:26.2890365Z SingleProcess AUTOTUNE benchmarking takes 0.1455 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:54:26.5417814Z Autotune Choices Stats: 2025-09-07T09:54:26.5419492Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.025599999353289604, "best_triton_pos": 1, "best_triton_time": 0.035840000957250595, "best_triton_kernel": "triton_convolution2d_612", "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"} 2025-09-07T09:54:26.5496353Z AUTOTUNE convolution(4x1024x14x14, 512x1024x1x1) 2025-09-07T09:54:26.5496738Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:54:26.5497092Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:26.5497418Z convolution 0.0256 ms 100.0% 2025-09-07T09:54:26.5498314Z triton_convolution2d_612 0.0358 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:54:26.5499808Z triton_convolution2d_613 0.0481 ms 53.2% 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 2025-09-07T09:54:26.5501573Z triton_convolution2d_611 0.0532 ms 48.1% 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 2025-09-07T09:54:26.5503053Z triton_convolution2d_614 0.0543 ms 47.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:54:26.5503964Z conv1x1_via_mm 0.0573 ms 44.6% 2025-09-07T09:54:26.5504934Z triton_convolution2d_608 0.0717 ms 35.7% 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 2025-09-07T09:54:26.5506423Z triton_convolution2d_609 0.0768 ms 33.3% 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 2025-09-07T09:54:26.5507921Z triton_convolution2d_610 0.0932 ms 27.5% 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 2025-09-07T09:54:26.5509101Z SingleProcess AUTOTUNE benchmarking takes 0.1855 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:54:26.6812506Z Autotune Choices Stats: 2025-09-07T09:54:26.6814292Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.025599999353289604, "best_triton_pos": 1, "best_triton_time": 0.027648000046610832, "best_triton_kernel": "triton_convolution2d_627", "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=8"} 2025-09-07T09:54:26.6884476Z AUTOTUNE convolution(4x128x7x7, 32x128x3x3) 2025-09-07T09:54:26.6884863Z strides: [6272, 49, 7, 1], [1152, 9, 3, 1] 2025-09-07T09:54:26.6885201Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:26.6885510Z convolution 0.0256 ms 100.0% 2025-09-07T09:54:26.6886396Z triton_convolution2d_627 0.0276 ms 92.6% 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 2025-09-07T09:54:26.6887881Z triton_convolution2d_626 0.0307 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 2025-09-07T09:54:26.6889357Z triton_convolution2d_622 0.0379 ms 67.6% 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 2025-09-07T09:54:26.6890849Z triton_convolution2d_625 0.0399 ms 64.1% 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 2025-09-07T09:54:26.6892344Z triton_convolution2d_624 0.0440 ms 58.1% 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 2025-09-07T09:54:26.6893924Z triton_convolution2d_628 0.0502 ms 51.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:54:26.6895416Z triton_convolution2d_623 0.0553 ms 46.3% 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:26.6896574Z SingleProcess AUTOTUNE benchmarking takes 0.1360 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:54:27.0285226Z Autotune Choices Stats: 2025-09-07T09:54:27.0286714Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_843", "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} 2025-09-07T09:54:27.0359122Z AUTOTUNE addmm(4x1000, 4x1024, 1024x1000) 2025-09-07T09:54:27.0359474Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T09:54:27.0359837Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:54:27.0360637Z triton_mm_843 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 2025-09-07T09:54:27.0361833Z triton_mm_847 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 2025-09-07T09:54:27.0363039Z triton_mm_851 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:27.0364215Z triton_mm_855 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 2025-09-07T09:54:27.0364962Z bias_addmm 0.0143 ms 78.6% 2025-09-07T09:54:27.0365659Z triton_mm_841 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 2025-09-07T09:54:27.0366827Z triton_mm_842 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 2025-09-07T09:54:27.0368176Z triton_mm_840 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 2025-09-07T09:54:27.0369354Z triton_mm_846 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:27.0370525Z triton_mm_850 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 2025-09-07T09:54:27.0371548Z SingleProcess AUTOTUNE benchmarking takes 0.2835 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T09:55:02.1064362Z Autotune Choices Stats: 2025-09-07T09:55:02.1065634Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_873", "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} 2025-09-07T09:55:02.1137095Z AUTOTUNE mm(1000x4, 4x1024) 2025-09-07T09:55:02.1137390Z strides: [1, 1000], [1024, 1] 2025-09-07T09:55:02.1137700Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:02.1138474Z triton_mm_873 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 2025-09-07T09:55:02.1139670Z triton_mm_874 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 2025-09-07T09:55:02.1140858Z triton_mm_875 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 2025-09-07T09:55:02.1142044Z triton_mm_876 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 2025-09-07T09:55:02.1143569Z triton_mm_877 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 2025-09-07T09:55:02.1144833Z triton_mm_878 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 2025-09-07T09:55:02.1146030Z triton_mm_879 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 2025-09-07T09:55:02.1147217Z triton_mm_880 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 2025-09-07T09:55:02.1148409Z triton_mm_881 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 2025-09-07T09:55:02.1149614Z triton_mm_882 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 2025-09-07T09:55:02.1150649Z SingleProcess AUTOTUNE benchmarking takes 0.2155 seconds and 0.0004 seconds precompiling for 17 choices 2025-09-07T09:55:02.9355653Z Autotune Choices Stats: 2025-09-07T09:55:02.9356873Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_860", "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} 2025-09-07T09:55:02.9423858Z AUTOTUNE mm(4x1000, 1000x1024) 2025-09-07T09:55:02.9424159Z strides: [1000, 1], [1024, 1] 2025-09-07T09:55:02.9424887Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:02.9425700Z triton_mm_860 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 2025-09-07T09:55:02.9426911Z triton_mm_864 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 2025-09-07T09:55:02.9428120Z triton_mm_868 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 2025-09-07T09:55:02.9428865Z mm 0.0133 ms 84.6% 2025-09-07T09:55:02.9429550Z triton_mm_858 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 2025-09-07T09:55:02.9430730Z triton_mm_872 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 2025-09-07T09:55:02.9431896Z triton_mm_859 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 2025-09-07T09:55:02.9433070Z triton_mm_863 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 2025-09-07T09:55:02.9434249Z triton_mm_867 0.0143 ms 78.6% 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=3, num_warps=4 2025-09-07T09:55:02.9435437Z triton_mm_857 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 2025-09-07T09:55:02.9436465Z SingleProcess AUTOTUNE benchmarking takes 0.2446 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:55:26.3353783Z pass 2025-09-07T09:55:32.1425409Z accuracy pass_rate=92.31% 2025-09-07T09:55:32.1431480Z calls_captured gmean=0.00x mean=225.615x 2025-09-07T09:55:32.1435155Z unique_graphs gmean=0.00x mean=3.538x 2025-09-07T09:55:32.1439434Z graph_breaks gmean=0.00x mean=7.692x 2025-09-07T09:55:32.1443563Z unique_graph_breaks gmean=0.00x mean=4.846x 2025-09-07T09:55:32.1447746Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:55:32.1451836Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:55:32.1456423Z cudagraph_skips gmean=0.00x mean=0.769x 2025-09-07T09:55:32.1457636Z compilation_latency mean=36.654 seconds 2025-09-07T09:55:33.1090181Z + [[ 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* ]] 2025-09-07T09:55:33.1091737Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:55:33.1092048Z + for target in "${targets[@]}" 2025-09-07T09:55:33.1092352Z + target_flag=('--performance') 2025-09-07T09:55:33.1092642Z + local target_flag 2025-09-07T09:55:33.1093126Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T09:55:33.1093467Z + target_flag+=(--cold-start-latency) 2025-09-07T09:55:33.1094851Z + [[ 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* ]] 2025-09-07T09:55:33.1097283Z + [[ 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* ]] 2025-09-07T09:55:33.1099854Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.csv 2025-09-07T09:55:33.7312535Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:55:33.7313932Z import pynvml # type: ignore[import] 2025-09-07T09:55:37.8178497Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:55:37.8181139Z import pynvml # type: ignore[import] 2025-09-07T09:55:40.5680613Z 2025-09-07T09:55:40.7659552Z loading model: 0it [00:00, ?it/s][rank0]:W0907 09:55:40.765000 61643 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T09:55:41.7728091Z 2025-09-07T09:55:41.7728453Z loading model: 0it [00:01, ?it/s] 2025-09-07T09:55:41.7728847Z cuda train torchrec_dlrm 2025-09-07T09:55:54.4720391Z [rank0]:W0907 09:55:54.471000 61643 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:56:02.8141628Z 2025-09-07T09:56:02.9233028Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:58:25.9043973Z 2025-09-07T09:58:26.2562273Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:00:19.0284434Z 2025-09-07T10:00:19.2574825Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:01:13.1415064Z 2025-09-07T10:01:13.2482464Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:01:31.9670423Z 2025-09-07T10:01:32.0729939Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:01:50.4591033Z 2025-09-07T10:01:50.5606662Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:02:08.9188435Z 2025-09-07T10:02:09.0189959Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:05:30.2411141Z 2025-09-07T10:05:30.3600404Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:07:55.2265140Z 2025-09-07T10:07:55.7529956Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:09:49.2826856Z 2025-09-07T10:09:49.6198301Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:10:44.6382405Z 2025-09-07T10:10:44.7441906Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:11:04.1293690Z 2025-09-07T10:11:04.2322649Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:11:23.7737342Z 2025-09-07T10:11:23.8784438Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:11:42.7049655Z 2025-09-07T10:11:42.8102023Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:15:15.6795353Z 2025-09-07T10:15:15.6934918Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:15:15.6978654Z [rank0]: torchbench_main() 2025-09-07T10:15:15.6979249Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T10:15:15.6979925Z [rank0]: main(TorchBenchmarkRunner(), original_dir) 2025-09-07T10:15:15.6980514Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T10:15:15.6981115Z [rank0]: process_entry(0, runner, original_dir, args) 2025-09-07T10:15:15.6981756Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T10:15:15.6982369Z [rank0]: result = run(runner, args, original_dir) 2025-09-07T10:15:15.6982942Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4279, in run 2025-09-07T10:15:15.6983488Z [rank0]: runner.run_one_model( 2025-09-07T10:15:15.6984060Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2886, in run_one_model 2025-09-07T10:15:15.6984661Z [rank0]: status = self.run_performance_test( 2025-09-07T10:15:15.6988704Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2796, in run_performance_test 2025-09-07T10:15:15.6989580Z [rank0]: results.append(experiment(model, example_inputs, **experiment_kwargs)) 2025-09-07T10:15:15.6990362Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1124, in speedup_experiment 2025-09-07T10:15:15.6991025Z [rank0]: timings[rep, 0], expected_output = timed( 2025-09-07T10:15:15.6991590Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 751, in timed 2025-09-07T10:15:15.6992303Z [rank0]: result = model_iter_fn(model, example_inputs, collect_outputs=collect_outputs) 2025-09-07T10:15:15.6993152Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T10:15:15.6993841Z [rank0]: pred = mod(*cloned_inputs) 2025-09-07T10:15:15.6994562Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:15:15.6995293Z [rank0]: return self._call_impl(*args, **kwargs) 2025-09-07T10:15:15.6995990Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:15:15.6996678Z [rank0]: return forward_call(*args, **kwargs) 2025-09-07T10:15:15.6997326Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T10:15:15.6998066Z [rank0]: logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T10:15:15.6998877Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:15:15.6999610Z [rank0]: return self._call_impl(*args, **kwargs) 2025-09-07T10:15:15.7000503Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:15:15.7001197Z [rank0]: return forward_call(*args, **kwargs) 2025-09-07T10:15:15.7001843Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T10:15:15.7002481Z [rank0]: concatenated_dense = self.inter_arch( 2025-09-07T10:15:15.7003207Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:15:15.7003939Z [rank0]: return self._call_impl(*args, **kwargs) 2025-09-07T10:15:15.7004625Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:15:15.7005296Z [rank0]: return forward_call(*args, **kwargs) 2025-09-07T10:15:15.7005937Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 279, in forward 2025-09-07T10:15:15.7006577Z [rank0]: combined_values = torch.cat( 2025-09-07T10:15:15.7007297Z [rank0]: RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 1072 but got size 1024 for tensor number 1 in the list. 2025-09-07T10:15:17.9264290Z [rank0]:[W907 10:15:17.212724245 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T10:15:18.6371866Z Run failed with return code: 1 2025-09-07T10:15:18.6372245Z Output: None 2025-09-07T10:15:18.6372473Z Error: None 2025-09-07T10:15:19.2398976Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:15:19.2401761Z import pynvml # type: ignore[import] 2025-09-07T10:15:22.0319152Z 2025-09-07T10:15:24.7671275Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:15:24.7672195Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:15:24.7672558Z cuda train BERT_pytorch 2025-09-07T10:16:11.2617855Z 2025-09-07T10:16:11.3726877Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:17:49.6231088Z 2025-09-07T10:17:49.8966250Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:17:49.8969571Z torchbench_main() 2025-09-07T10:17:49.8970109Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T10:17:49.8970724Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T10:17:49.8971278Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T10:17:49.8974523Z process_entry(0, runner, original_dir, args) 2025-09-07T10:17:49.8975122Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T10:17:49.8978403Z result = run(runner, args, original_dir) 2025-09-07T10:17:49.8978920Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4279, in run 2025-09-07T10:17:49.8983114Z runner.run_one_model( 2025-09-07T10:17:49.8983632Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2886, in run_one_model 2025-09-07T10:17:49.8986510Z status = self.run_performance_test( 2025-09-07T10:17:49.8987123Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2796, in run_performance_test 2025-09-07T10:17:49.8989774Z results.append(experiment(model, example_inputs, **experiment_kwargs)) 2025-09-07T10:17:49.8990983Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1124, in speedup_experiment 2025-09-07T10:17:49.8991608Z timings[rep, 0], expected_output = timed( 2025-09-07T10:17:49.8992139Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 751, in timed 2025-09-07T10:17:49.8992809Z result = model_iter_fn(model, example_inputs, collect_outputs=collect_outputs) 2025-09-07T10:17:49.8993593Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T10:17:49.8994248Z pred = mod(*cloned_inputs) 2025-09-07T10:17:49.8994901Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:17:49.8995592Z return self._call_impl(*args, **kwargs) 2025-09-07T10:17:49.8996236Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:17:49.8997583Z return forward_call(*args, **kwargs) 2025-09-07T10:17:49.8998164Z File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 241, in forward 2025-09-07T10:17:49.8998765Z multi_feat = self.model_enc_multi(multi) 2025-09-07T10:17:49.8999457Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:17:49.9000331Z return self._call_impl(*args, **kwargs) 2025-09-07T10:17:49.9000949Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:17:49.9002611Z return forward_call(*args, **kwargs) 2025-09-07T10:17:49.9003239Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py", line 250, in forward 2025-09-07T10:17:49.9004077Z input = module(input) 2025-09-07T10:17:49.9004703Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:17:49.9005397Z return self._call_impl(*args, **kwargs) 2025-09-07T10:17:49.9006032Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:17:49.9009035Z return forward_call(*args, **kwargs) 2025-09-07T10:17:49.9009647Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 548, in forward 2025-09-07T10:17:49.9010331Z return self._conv_forward(input, self.weight, self.bias) 2025-09-07T10:17:49.9011021Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 543, in _conv_forward 2025-09-07T10:17:49.9011662Z return F.conv2d( 2025-09-07T10:17:49.9012243Z RuntimeError: Given groups=1, weight of size [64, 4, 7, 7], expected input[3, 3, 518, 518] to have 4 channels, but got 3 channels instead 2025-09-07T10:17:54.6101835Z Run failed with return code: 1 2025-09-07T10:17:54.6102405Z Output: None 2025-09-07T10:17:54.6102784Z Error: None 2025-09-07T10:17:55.2312830Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:17:55.2314241Z import pynvml # type: ignore[import] 2025-09-07T10:17:58.1240366Z 2025-09-07T10:18:02.0551706Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:18:02.0552109Z loading model: 0it [00:03, ?it/s] 2025-09-07T10:18:02.0552450Z cuda train LearningToPaint 2025-09-07T10:18:27.1040674Z 2025-09-07T10:18:27.3469258Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:19:47.1544004Z 2025-09-07T10:19:47.4891018Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:20:46.1691266Z 2025-09-07T10:20:46.2768926Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:21:05.1445889Z 2025-09-07T10:21:05.2527580Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:21:24.4106437Z 2025-09-07T10:21:24.5129857Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:21:43.5235274Z 2025-09-07T10:21:43.6249862Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:25:46.8329198Z 2025-09-07T10:25:46.9360063Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:29:50.1103426Z 2025-09-07T10:29:50.4662425Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:32:37.4716779Z 2025-09-07T10:32:37.7017391Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:33:54.2109052Z 2025-09-07T10:33:54.3130167Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:34:26.3491141Z 2025-09-07T10:34:26.4564648Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:34:54.3825301Z 2025-09-07T10:34:54.4887047Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:35:22.6344992Z 2025-09-07T10:35:22.7365862Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:41:41.5412780Z 2025-09-07T10:41:41.6708943Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:45:04.9746006Z 2025-09-07T10:45:05.4953072Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:48:26.1520383Z 2025-09-07T10:48:26.4862921Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:49:54.9267486Z 2025-09-07T10:49:55.0338579Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:50:20.0127939Z 2025-09-07T10:50:20.1214453Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:50:44.2438802Z 2025-09-07T10:50:44.3442786Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:51:08.9426272Z 2025-09-07T10:51:09.0437642Z running benchmark: 0% 0/30 [00:00 0:`). Dynamo does not support tracing dynamic control flow. 2025-09-07T11:35:26.0661336Z Hint: This graph break is fundamental - it is unlikely that Dynamo will ever be able to trace through your code. Consider finding a workaround. 2025-09-07T11:35:26.0662125Z Hint: Use `torch.cond` to express dynamic control flow. 2025-09-07T11:35:26.0662405Z 2025-09-07T11:35:26.0662717Z Developer debug context: attempted to jump with TensorVariable() 2025-09-07T11:35:26.0663059Z 2025-09-07T11:35:26.0663531Z For more details about this graph break, please visit: https://meta-pytorch.github.io/compile-graph-break-site/gb/gb0170.html 2025-09-07T11:35:26.0664112Z 2025-09-07T11:35:26.0664200Z from user code: 2025-09-07T11:35:26.0664668Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1130, in forward 2025-09-07T11:35:26.0665293Z model_out = self.model( 2025-09-07T11:35:26.0665873Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:35:26.0666513Z return forward_call(*args, **kwargs) 2025-09-07T11:35:26.0667051Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 983, in forward 2025-09-07T11:35:26.0667599Z x = self.extract_features( 2025-09-07T11:35:26.0668136Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1008, in extract_features 2025-09-07T11:35:26.0668733Z self_attn_padding_mask is None 2025-09-07T11:35:26.0668944Z 2025-09-07T11:35:26.0669563Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T11:35:26.0670306Z 2025-09-07T11:35:26.0670533Z TorchDynamo optimized model failed to run because of following error 2025-09-07T11:35:26.0838157Z fail_to_run 2025-09-07T11:35:27.9599045Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:35:27.9600466Z import pynvml # type: ignore[import] 2025-09-07T11:35:30.6078231Z 2025-09-07T11:35:31.1904105Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:31.1904501Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:31.1910094Z cuda eval dcgan 2025-09-07T11:35:35.6771520Z pass 2025-09-07T11:35:37.3619843Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:35:37.3621260Z import pynvml # type: ignore[import] 2025-09-07T11:35:39.9819493Z 2025-09-07T11:35:43.4184986Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:35:43.4185428Z loading model: 0it [00:03, ?it/s] 2025-09-07T11:35:43.4205905Z cuda eval demucs 2025-09-07T11:36:17.1556504Z pass 2025-09-07T11:36:19.0413877Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:19.0415321Z import pynvml # type: ignore[import] 2025-09-07T11:36:21.7736033Z 2025-09-07T11:36:23.3123722Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:36:23.3124108Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:36:23.3272668Z cuda eval densenet121 2025-09-07T11:36:32.5587986Z pass 2025-09-07T11:36:34.4795932Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:34.4797380Z import pynvml # type: ignore[import] 2025-09-07T11:36:37.1360825Z 2025-09-07T11:36:37.4021261Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:36:37.4021827Z what(): std::bad_alloc 2025-09-07T11:36:37.6238881Z Run failed with return code: -6 2025-09-07T11:36:37.6239758Z Output: None 2025-09-07T11:36:37.6240007Z Error: None 2025-09-07T11:36:38.1878879Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:38.1880314Z import pynvml # type: ignore[import] 2025-09-07T11:36:40.9967899Z 2025-09-07T11:36:41.2785657Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:36:41.2786245Z what(): std::bad_alloc 2025-09-07T11:36:41.4931400Z Run failed with return code: -6 2025-09-07T11:36:41.4931751Z Output: None 2025-09-07T11:36:41.4931995Z Error: None 2025-09-07T11:36:42.0727647Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:42.0729066Z import pynvml # type: ignore[import] 2025-09-07T11:36:44.8708097Z 2025-09-07T11:36:45.1422632Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:36:45.1423190Z what(): std::bad_alloc 2025-09-07T11:36:45.3623422Z Run failed with return code: -6 2025-09-07T11:36:45.3623767Z Output: None 2025-09-07T11:36:45.3623998Z Error: None 2025-09-07T11:36:45.3667165Z accuracy pass_rate=71.43% 2025-09-07T11:36:45.3674065Z calls_captured gmean=0.00x mean=89.857x 2025-09-07T11:36:45.3678354Z unique_graphs gmean=0.00x mean=0.714x 2025-09-07T11:36:45.3682616Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:36:45.3686755Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:36:45.3690864Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:36:45.3695548Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:36:45.3699558Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:36:45.3700762Z compilation_latency mean=3.335 seconds 2025-09-07T11:36:46.3203209Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:36:46.8809359Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:46.8810786Z import pynvml # type: ignore[import] 2025-09-07T11:36:50.6712973Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:50.6714379Z import pynvml # type: ignore[import] 2025-09-07T11:36:53.3228808Z 2025-09-07T11:36:53.5172002Z loading model: 0it [00:00, ?it/s][rank0]:W0907 11:36:53.516000 278610 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T11:36:54.3519612Z 2025-09-07T11:36:54.3520051Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:36:54.3520432Z cuda eval torchrec_dlrm 2025-09-07T11:36:54.3533800Z Traceback (most recent call last): 2025-09-07T11:36:54.3534387Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T11:36:54.3535360Z self.model_iter_fn(model, example_inputs) 2025-09-07T11:36:54.3535946Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:36:54.3536517Z return mod(*inputs) 2025-09-07T11:36:54.3537162Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:36:54.3537857Z return self._call_impl(*args, **kwargs) 2025-09-07T11:36:54.3538497Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:36:54.3539142Z return forward_call(*args, **kwargs) 2025-09-07T11:36:54.3539723Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T11:36:54.3540429Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T11:36:54.3541206Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:36:54.3541889Z return self._call_impl(*args, **kwargs) 2025-09-07T11:36:54.3542508Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:36:54.3543142Z return forward_call(*args, **kwargs) 2025-09-07T11:36:54.3543732Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T11:36:54.3544338Z concatenated_dense = self.inter_arch( 2025-09-07T11:36:54.3545079Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:36:54.3545769Z return self._call_impl(*args, **kwargs) 2025-09-07T11:36:54.3546533Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:36:54.3547170Z return forward_call(*args, **kwargs) 2025-09-07T11:36:54.3547768Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T11:36:54.3548444Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T11:36:54.3549170Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:36:54.3549854Z return self._call_impl(*args, **kwargs) 2025-09-07T11:36:54.3550583Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:36:54.3551222Z return forward_call(*args, **kwargs) 2025-09-07T11:36:54.3551828Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T11:36:54.3552539Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T11:36:54.3553187Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T11:36:54.3553602Z 2025-09-07T11:36:54.3553834Z The above exception was the direct cause of the following exception: 2025-09-07T11:36:54.3554163Z 2025-09-07T11:36:54.3554284Z Traceback (most recent call last): 2025-09-07T11:36:54.3554765Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:36:54.3555282Z ) = runner.load_model( 2025-09-07T11:36:54.3555794Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T11:36:54.3556384Z self.validate_model(model, example_inputs) 2025-09-07T11:36:54.3556964Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T11:36:54.3557552Z raise RuntimeError("Eager run failed") from e 2025-09-07T11:36:54.3557914Z RuntimeError: Eager run failed 2025-09-07T11:36:54.3558105Z 2025-09-07T11:36:54.3558208Z eager_fail_to_run 2025-09-07T11:36:54.9948227Z [rank0]:[W907 11:36:54.281122855 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T11:36:56.0572652Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:36:56.0574215Z import pynvml # type: ignore[import] 2025-09-07T11:36:58.7791722Z 2025-09-07T11:37:01.2968506Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:37:01.2968890Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:37:01.3030251Z cuda eval BERT_pytorch 2025-09-07T11:37:34.2952120Z pass 2025-09-07T11:37:37.5192983Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:37:37.5194399Z import pynvml # type: ignore[import] 2025-09-07T11:37:40.2577766Z 2025-09-07T11:37:43.0226472Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:37:43.0226854Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:37:43.0280893Z cuda eval Background_Matting 2025-09-07T11:37:43.0516085Z pass_due_to_skip 2025-09-07T11:37:44.7895374Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:37:44.7897214Z import pynvml # type: ignore[import] 2025-09-07T11:37:47.4590224Z 2025-09-07T11:37:50.7617393Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:37:50.7617770Z loading model: 0it [00:03, ?it/s] 2025-09-07T11:37:50.7644366Z cuda eval LearningToPaint 2025-09-07T11:38:07.0023310Z pass 2025-09-07T11:38:10.3942792Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:38:10.3944618Z import pynvml # type: ignore[import] 2025-09-07T11:38:13.0677176Z 2025-09-07T11:38:15.2442449Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T11:38:15.6737876Z 2025-09-07T11:38:15.6738230Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:38:15.6740121Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T11:38:15.6740711Z cuda eval Super_SloMo 2025-09-07T11:38:16.2204744Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T11:38:57.6606253Z pass 2025-09-07T11:39:01.4135927Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:39:01.4137341Z import pynvml # type: ignore[import] 2025-09-07T11:39:04.0638543Z 2025-09-07T11:39:05.6319312Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:39:05.6319709Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:39:05.6324481Z cuda eval alexnet 2025-09-07T11:39:21.4533518Z pass 2025-09-07T11:39:24.7307865Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:39:24.7309705Z import pynvml # type: ignore[import] 2025-09-07T11:39:27.5074971Z 2025-09-07T11:39:29.7632708Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:39:29.7633084Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:39:29.7638268Z cuda eval basic_gnn_edgecnn 2025-09-07T11:39:41.4586732Z pass 2025-09-07T11:39:44.2602779Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:39:44.2604230Z import pynvml # type: ignore[import] 2025-09-07T11:39:46.9717739Z 2025-09-07T11:39:49.4235652Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:39:49.4236021Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:39:49.4238684Z cuda eval basic_gnn_gcn 2025-09-07T11:40:04.0158924Z pass 2025-09-07T11:40:07.0525104Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:40:07.0526531Z import pynvml # type: ignore[import] 2025-09-07T11:40:09.6995502Z 2025-09-07T11:40:12.1066374Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:40:12.1066770Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:40:12.1071710Z cuda eval basic_gnn_gin 2025-09-07T11:40:24.2885533Z pass 2025-09-07T11:40:27.1923906Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:40:27.1932646Z import pynvml # type: ignore[import] 2025-09-07T11:40:29.8790994Z 2025-09-07T11:40:32.2240110Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:40:32.2240483Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:40:32.2244070Z cuda eval basic_gnn_sage 2025-09-07T11:40:44.2942375Z pass 2025-09-07T11:40:47.3852505Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:40:47.3854467Z import pynvml # type: ignore[import] 2025-09-07T11:40:50.0371347Z 2025-09-07T11:40:50.6437725Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:40:50.6438132Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:40:50.6443528Z cuda eval dcgan 2025-09-07T11:41:03.9476345Z pass 2025-09-07T11:41:06.7728372Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:41:06.7729814Z import pynvml # type: ignore[import] 2025-09-07T11:41:09.4184775Z 2025-09-07T11:41:12.8765397Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:41:12.8765792Z loading model: 0it [00:03, ?it/s] 2025-09-07T11:41:12.8787682Z cuda eval demucs 2025-09-07T11:43:10.0840520Z pass 2025-09-07T11:43:15.1745880Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:43:15.1747326Z import pynvml # type: ignore[import] 2025-09-07T11:43:17.8488876Z 2025-09-07T11:43:19.3069138Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:43:19.3069999Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:43:19.3216487Z cuda eval densenet121 2025-09-07T11:44:06.5898746Z pass 2025-09-07T11:44:10.4956280Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:10.4957723Z import pynvml # type: ignore[import] 2025-09-07T11:44:13.1444265Z 2025-09-07T11:44:13.4136354Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:44:13.4138527Z what(): std::bad_alloc 2025-09-07T11:44:13.6031430Z Run failed with return code: -6 2025-09-07T11:44:13.6031759Z Output: None 2025-09-07T11:44:13.6031974Z Error: None 2025-09-07T11:44:14.1657438Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:14.1658835Z import pynvml # type: ignore[import] 2025-09-07T11:44:16.7967892Z 2025-09-07T11:44:17.0644172Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:44:17.0644771Z what(): std::bad_alloc 2025-09-07T11:44:17.2718286Z Run failed with return code: -6 2025-09-07T11:44:17.2718619Z Output: None 2025-09-07T11:44:17.2718838Z Error: None 2025-09-07T11:44:17.8281936Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:17.8283701Z import pynvml # type: ignore[import] 2025-09-07T11:44:20.4835187Z 2025-09-07T11:44:20.7492386Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:44:20.7493193Z what(): std::bad_alloc 2025-09-07T11:44:20.9406294Z Run failed with return code: -6 2025-09-07T11:44:20.9406638Z Output: None 2025-09-07T11:44:20.9406869Z Error: None 2025-09-07T11:44:20.9448577Z accuracy pass_rate=84.62% 2025-09-07T11:44:20.9455963Z calls_captured gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9460477Z unique_graphs gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9464689Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9469122Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9473205Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9477243Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9481303Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T11:44:20.9482560Z compilation_latency mean=0.000 seconds 2025-09-07T11:44:21.9415646Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *maxautotune-true* ]] 2025-09-07T11:44:21.9417107Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T11:44:21.9418580Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv 2025-09-07T11:44:22.5282525Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:22.5283945Z import pynvml # type: ignore[import] 2025-09-07T11:44:26.3864598Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:26.3866243Z import pynvml # type: ignore[import] 2025-09-07T11:44:29.0440916Z 2025-09-07T11:44:29.2376975Z loading model: 0it [00:00, ?it/s][rank0]:W0907 11:44:29.237000 285434 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T11:44:30.0792609Z 2025-09-07T11:44:30.0793042Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:44:30.0793454Z cuda eval torchrec_dlrm 2025-09-07T11:44:30.0806930Z Traceback (most recent call last): 2025-09-07T11:44:30.0807603Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T11:44:30.0808201Z self.model_iter_fn(model, example_inputs) 2025-09-07T11:44:30.0808780Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:44:30.0809358Z return mod(*inputs) 2025-09-07T11:44:30.0809991Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:44:30.0810693Z return self._call_impl(*args, **kwargs) 2025-09-07T11:44:30.0811339Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:44:30.0811967Z return forward_call(*args, **kwargs) 2025-09-07T11:44:30.0813118Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T11:44:30.0813833Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T11:44:30.0814604Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:44:30.0815291Z return self._call_impl(*args, **kwargs) 2025-09-07T11:44:30.0815911Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:44:30.0816668Z return forward_call(*args, **kwargs) 2025-09-07T11:44:30.0817265Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T11:44:30.0817871Z concatenated_dense = self.inter_arch( 2025-09-07T11:44:30.0818532Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:44:30.0819224Z return self._call_impl(*args, **kwargs) 2025-09-07T11:44:30.0819854Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:44:30.0820498Z return forward_call(*args, **kwargs) 2025-09-07T11:44:30.0821090Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T11:44:30.0821749Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T11:44:30.0822486Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:44:30.0823174Z return self._call_impl(*args, **kwargs) 2025-09-07T11:44:30.0823802Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:44:30.0824434Z return forward_call(*args, **kwargs) 2025-09-07T11:44:30.0825126Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T11:44:30.0825847Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T11:44:30.0826662Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T11:44:30.0827081Z 2025-09-07T11:44:30.0827312Z The above exception was the direct cause of the following exception: 2025-09-07T11:44:30.0827642Z 2025-09-07T11:44:30.0827765Z Traceback (most recent call last): 2025-09-07T11:44:30.0828247Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:44:30.0828759Z ) = runner.load_model( 2025-09-07T11:44:30.0829268Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T11:44:30.0829855Z self.validate_model(model, example_inputs) 2025-09-07T11:44:30.0830424Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T11:44:30.0831023Z raise RuntimeError("Eager run failed") from e 2025-09-07T11:44:30.0831381Z RuntimeError: Eager run failed 2025-09-07T11:44:30.0831571Z 2025-09-07T11:44:30.0831682Z eager_fail_to_run 2025-09-07T11:44:30.7003129Z [rank0]:[W907 11:44:30.986671664 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T11:44:31.7689375Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:44:31.7690826Z import pynvml # type: ignore[import] 2025-09-07T11:44:34.4360963Z 2025-09-07T11:44:36.8684317Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:44:36.8685164Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:44:36.8745793Z cuda eval BERT_pytorch 2025-09-07T11:44:58.6111374Z pass 2025-09-07T11:45:02.1564916Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:45:02.1566338Z import pynvml # type: ignore[import] 2025-09-07T11:45:04.9076079Z 2025-09-07T11:45:07.6249361Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:45:07.6250042Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:45:07.6303140Z cuda eval Background_Matting 2025-09-07T11:45:07.6538009Z pass_due_to_skip 2025-09-07T11:45:09.4561061Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:45:09.4562510Z import pynvml # type: ignore[import] 2025-09-07T11:45:12.1444432Z 2025-09-07T11:45:15.4467977Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:45:15.4468349Z loading model: 0it [00:03, ?it/s] 2025-09-07T11:45:15.4495166Z cuda eval LearningToPaint 2025-09-07T11:45:25.9803784Z pass 2025-09-07T11:45:29.2875555Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:45:29.2876979Z import pynvml # type: ignore[import] 2025-09-07T11:45:31.9455085Z 2025-09-07T11:45:34.0827099Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T11:45:34.4928580Z 2025-09-07T11:45:34.4928915Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:45:34.4929448Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T11:45:34.4930384Z cuda eval Super_SloMo 2025-09-07T11:45:35.0431759Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T11:46:08.9287927Z pass 2025-09-07T11:46:12.5494159Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:46:12.5495933Z import pynvml # type: ignore[import] 2025-09-07T11:46:15.1798966Z 2025-09-07T11:46:16.7370175Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:46:16.7370544Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:46:16.7375792Z cuda eval alexnet 2025-09-07T11:46:26.2790557Z pass 2025-09-07T11:46:29.0873245Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:46:29.0874891Z import pynvml # type: ignore[import] 2025-09-07T11:46:31.7012952Z 2025-09-07T11:46:33.8820741Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:46:33.8821126Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:46:33.8826157Z cuda eval basic_gnn_edgecnn 2025-09-07T11:46:38.5896928Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:46:38.5897997Z return mod(*inputs) 2025-09-07T11:46:38.5898620Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T11:46:38.5899620Z x = self.convs[i](x, edge_index) 2025-09-07T11:46:38.5900021Z File "/tmp/jenkins_pyg/tmpt61i7p0z.py", line 233, in forward 2025-09-07T11:46:38.5900481Z return self.propagate(edge_index, x=x, size=None) 2025-09-07T11:46:38.5900936Z File "/tmp/jenkins_pyg/tmpt61i7p0z.py", line 192, in propagate 2025-09-07T11:46:38.5901522Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T11:46:38.5902412Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T11:46:38.5903327Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T11:46:38.5904052Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T11:46:38.5904782Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T11:46:38.5905587Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward 2025-09-07T11:46:38.5906317Z return self.reduce(x, index, ptr, dim_size, dim, reduce='max') 2025-09-07T11:46:38.5907011Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T11:46:38.5907674Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T11:46:38.5908341Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter 2025-09-07T11:46:38.5909000Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T11:46:38.5909246Z 2025-09-07T11:46:38.5909250Z 2025-09-07T11:46:38.8007292Z pass 2025-09-07T11:46:41.7763058Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:46:41.7764522Z import pynvml # type: ignore[import] 2025-09-07T11:46:44.4265184Z 2025-09-07T11:46:47.0790515Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:46:47.0790900Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:46:47.0792621Z cuda eval basic_gnn_gcn 2025-09-07T11:46:50.3122612Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T11:46:50.3124061Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T11:46:50.3124813Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T11:46:50.3125518Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T11:46:50.3125828Z 2025-09-07T11:46:50.3125833Z 2025-09-07T11:46:50.9887629Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp48c2vt9d.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T11:46:50.9888719Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T11:46:50.9889224Z File "/tmp/jenkins_pyg/tmp48c2vt9d.py", line 188, in propagate 2025-09-07T11:46:50.9889812Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T11:46:50.9890688Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T11:46:50.9891500Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T11:46:50.9892235Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T11:46:50.9893538Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T11:46:50.9894259Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T11:46:50.9894969Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T11:46:50.9895676Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T11:46:50.9896334Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T11:46:50.9896993Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T11:46:50.9897805Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T11:46:50.9898091Z 2025-09-07T11:46:50.9898095Z 2025-09-07T11:46:51.1748606Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp48c2vt9d.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T11:46:51.1749687Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T11:46:51.1750192Z File "/tmp/jenkins_pyg/tmp48c2vt9d.py", line 188, in propagate 2025-09-07T11:46:51.1750800Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T11:46:51.1751690Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T11:46:51.1752496Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T11:46:51.1753228Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T11:46:51.1753955Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T11:46:51.1754663Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T11:46:51.1755375Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T11:46:51.1756089Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T11:46:51.1757134Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T11:46:51.1757808Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T11:46:51.1758494Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T11:46:51.1758796Z 2025-09-07T11:46:51.1758800Z 2025-09-07T11:46:51.3378310Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp48c2vt9d.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T11:46:51.3379412Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T11:46:51.3379917Z File "/tmp/jenkins_pyg/tmp48c2vt9d.py", line 188, in propagate 2025-09-07T11:46:51.3380517Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T11:46:51.3381428Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T11:46:51.3382230Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T11:46:51.3382953Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T11:46:51.3383676Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T11:46:51.3384387Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T11:46:51.3385195Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T11:46:51.3385897Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T11:46:51.3386558Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T11:46:51.3387439Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T11:46:51.3388262Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T11:46:51.3388549Z 2025-09-07T11:46:51.3388554Z 2025-09-07T11:46:51.4594202Z pass 2025-09-07T11:46:54.8504990Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:46:54.8507243Z import pynvml # type: ignore[import] 2025-09-07T11:46:57.4842309Z 2025-09-07T11:46:59.7951600Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:46:59.7952012Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:46:59.7956721Z cuda eval basic_gnn_gin 2025-09-07T11:47:04.6392028Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:47:04.6393116Z return mod(*inputs) 2025-09-07T11:47:04.6393737Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T11:47:04.6394413Z x = self.convs[i](x, edge_index) 2025-09-07T11:47:04.6394811Z File "/tmp/jenkins_pyg/tmp4su5xmue.py", line 225, in forward 2025-09-07T11:47:04.6395241Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T11:47:04.6395693Z File "/tmp/jenkins_pyg/tmp4su5xmue.py", line 182, in propagate 2025-09-07T11:47:04.6396279Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T11:47:04.6397157Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T11:47:04.6397959Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T11:47:04.6398681Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T11:47:04.6399716Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T11:47:04.6400428Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T11:47:04.6401154Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T11:47:04.6401860Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T11:47:04.6402505Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T11:47:04.6403163Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T11:47:04.6403854Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T11:47:04.6404143Z 2025-09-07T11:47:04.6404148Z 2025-09-07T11:47:04.8867295Z pass 2025-09-07T11:47:07.7326855Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:47:07.7328283Z import pynvml # type: ignore[import] 2025-09-07T11:47:10.4392788Z 2025-09-07T11:47:12.8123000Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:12.8123394Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:47:12.8126456Z cuda eval basic_gnn_sage 2025-09-07T11:47:18.2300595Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:47:18.2301655Z return mod(*inputs) 2025-09-07T11:47:18.2302584Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T11:47:18.2303255Z x = self.convs[i](x, edge_index) 2025-09-07T11:47:18.2303669Z File "/tmp/jenkins_pyg/tmpfhwauvpa.py", line 228, in forward 2025-09-07T11:47:18.2304114Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T11:47:18.2304555Z File "/tmp/jenkins_pyg/tmpfhwauvpa.py", line 182, in propagate 2025-09-07T11:47:18.2305262Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T11:47:18.2306143Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T11:47:18.2307068Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T11:47:18.2307808Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T11:47:18.2308523Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T11:47:18.2309235Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T11:47:18.2309960Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T11:47:18.2310673Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T11:47:18.2311338Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T11:47:18.2311996Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter 2025-09-07T11:47:18.2312687Z out = src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T11:47:18.2312973Z 2025-09-07T11:47:18.2312978Z 2025-09-07T11:47:18.4052732Z pass 2025-09-07T11:47:21.2568487Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:47:21.2569937Z import pynvml # type: ignore[import] 2025-09-07T11:47:23.9158393Z 2025-09-07T11:47:24.5203438Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:24.5203826Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:24.5209186Z cuda eval dcgan 2025-09-07T11:47:30.7409129Z pass 2025-09-07T11:47:33.5473347Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:47:33.5474798Z import pynvml # type: ignore[import] 2025-09-07T11:47:36.2126173Z 2025-09-07T11:47:39.6189114Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:47:39.6189474Z loading model: 0it [00:03, ?it/s] 2025-09-07T11:47:39.6210286Z cuda eval demucs 2025-09-07T11:48:12.4383581Z pass 2025-09-07T11:48:15.2755454Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:48:15.2756871Z import pynvml # type: ignore[import] 2025-09-07T11:48:17.9544188Z 2025-09-07T11:48:19.3816319Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:48:19.3816670Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:48:19.3960546Z cuda eval densenet121 2025-09-07T11:49:03.5846035Z Autotune Choices Stats: 2025-09-07T11:49:03.5847240Z {"num_choices": 20, "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} 2025-09-07T11:49:03.6154845Z AUTOTUNE mm(12544x64, 64x128) 2025-09-07T11:49:03.6155508Z strides: [64, 1], [1, 64] 2025-09-07T11:49:03.6156346Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:03.6157183Z 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 2025-09-07T11:49:03.6158372Z 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 2025-09-07T11:49:03.6159842Z 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 2025-09-07T11:49:03.6161040Z 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 2025-09-07T11:49:03.6162259Z triton_mm_16 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 2025-09-07T11:49:03.6163448Z triton_mm_17 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 2025-09-07T11:49:03.6164659Z triton_mm_18 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=4, num_warps=4 2025-09-07T11:49:03.6165881Z 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 2025-09-07T11:49:03.6167092Z 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 2025-09-07T11:49:03.6168498Z 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 2025-09-07T11:49:03.6169563Z SingleProcess AUTOTUNE benchmarking takes 0.4261 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T11:49:04.5318433Z Autotune Choices Stats: 2025-09-07T11:49:04.5319638Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_38", "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": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:04.5455892Z AUTOTUNE mm(12544x96, 96x128) 2025-09-07T11:49:04.5456266Z strides: [96, 1], [1, 96] 2025-09-07T11:49:04.5456568Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:04.5457380Z triton_mm_38 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:04.5458584Z triton_mm_41 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 2025-09-07T11:49:04.5459751Z triton_mm_42 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 2025-09-07T11:49:04.5460936Z triton_mm_44 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 2025-09-07T11:49:04.5462123Z triton_mm_45 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 2025-09-07T11:49:04.5463570Z triton_mm_47 0.0123 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 2025-09-07T11:49:04.5464760Z triton_mm_40 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:04.5466047Z triton_mm_43 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:04.5467352Z triton_mm_46 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 2025-09-07T11:49:04.5468526Z triton_mm_49 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:04.5469560Z SingleProcess AUTOTUNE benchmarking takes 0.3938 seconds and 0.0037 seconds precompiling for 19 choices 2025-09-07T11:49:04.9349421Z Autotune Choices Stats: 2025-09-07T11:49:04.9350930Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_63", "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": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T11:49:04.9536760Z AUTOTUNE mm(12544x128, 128x128) 2025-09-07T11:49:04.9537426Z strides: [128, 1], [1, 128] 2025-09-07T11:49:04.9538222Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:04.9539068Z triton_mm_63 0.0133 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 2025-09-07T11:49:04.9540296Z triton_mm_66 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 2025-09-07T11:49:04.9541859Z triton_mm_67 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=4, num_warps=8 2025-09-07T11:49:04.9543085Z triton_mm_68 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 2025-09-07T11:49:04.9544294Z triton_mm_69 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 2025-09-07T11:49:04.9545594Z triton_mm_70 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=4, num_warps=8 2025-09-07T11:49:04.9546830Z triton_mm_72 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=3, num_warps=4 2025-09-07T11:49:04.9548059Z triton_mm_73 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 2025-09-07T11:49:04.9549256Z triton_mm_64 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 2025-09-07T11:49:04.9550451Z triton_mm_65 0.0143 ms 92.9% 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 2025-09-07T11:49:04.9551496Z SingleProcess AUTOTUNE benchmarking takes 0.3681 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:05.4424069Z Autotune Choices Stats: 2025-09-07T11:49:05.4425985Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_91", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T11:49:05.4558215Z AUTOTUNE mm(12544x160, 160x128) 2025-09-07T11:49:05.4559023Z strides: [160, 1], [1, 160] 2025-09-07T11:49:05.4559566Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:05.4560788Z triton_mm_91 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 2025-09-07T11:49:05.4562336Z triton_mm_92 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 2025-09-07T11:49:05.4563541Z triton_mm_93 0.0143 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 2025-09-07T11:49:05.4564767Z triton_mm_94 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 2025-09-07T11:49:05.4565960Z triton_mm_95 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 2025-09-07T11:49:05.4567161Z triton_mm_97 0.0143 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 2025-09-07T11:49:05.4568359Z triton_mm_88 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:05.4569542Z triton_mm_98 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:05.4570930Z triton_mm_99 0.0154 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:05.4572128Z triton_mm_89 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:05.4573488Z SingleProcess AUTOTUNE benchmarking takes 0.4260 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:05.8700002Z Autotune Choices Stats: 2025-09-07T11:49:05.8701230Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_119", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.014336000196635723, "best_triton_pos": 0} 2025-09-07T11:49:05.8894414Z AUTOTUNE mm(12544x192, 192x128) 2025-09-07T11:49:05.8894979Z strides: [192, 1], [1, 192] 2025-09-07T11:49:05.8895410Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:05.8896287Z triton_mm_119 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 2025-09-07T11:49:05.8897563Z triton_mm_116 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=3, num_warps=4 2025-09-07T11:49:05.8898843Z triton_mm_117 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 2025-09-07T11:49:05.8900093Z triton_mm_118 0.0154 ms 93.3% 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 2025-09-07T11:49:05.8901723Z triton_mm_120 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 2025-09-07T11:49:05.8902980Z triton_mm_122 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 2025-09-07T11:49:05.8904237Z triton_mm_123 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 2025-09-07T11:49:05.8905716Z triton_mm_124 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 2025-09-07T11:49:05.8906986Z triton_mm_113 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 2025-09-07T11:49:05.8908231Z triton_mm_114 0.0174 ms 82.4% 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 2025-09-07T11:49:05.8909318Z SingleProcess AUTOTUNE benchmarking takes 0.3887 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:06.2728313Z Autotune Choices Stats: 2025-09-07T11:49:06.2729551Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_141", "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} 2025-09-07T11:49:06.2872298Z AUTOTUNE mm(12544x224, 224x128) 2025-09-07T11:49:06.2872918Z strides: [224, 1], [1, 224] 2025-09-07T11:49:06.2873320Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:06.2874553Z triton_mm_141 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 2025-09-07T11:49:06.2875866Z triton_mm_142 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=4, num_warps=8 2025-09-07T11:49:06.2877135Z triton_mm_144 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 2025-09-07T11:49:06.2878413Z triton_mm_145 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=4, num_warps=8 2025-09-07T11:49:06.2879686Z triton_mm_147 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 2025-09-07T11:49:06.2880978Z triton_mm_148 0.0164 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:06.2882251Z triton_mm_143 0.0174 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:06.2883501Z triton_mm_138 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 2025-09-07T11:49:06.2889348Z triton_mm_149 0.0184 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:06.2890807Z triton_mm_139 0.0195 ms 84.2% 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 2025-09-07T11:49:06.2892297Z SingleProcess AUTOTUNE benchmarking takes 0.3594 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:06.5933456Z Autotune Choices Stats: 2025-09-07T11:49:06.5934670Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_179", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:06.6069704Z AUTOTUNE mm(3136x128, 128x128) 2025-09-07T11:49:06.6070060Z strides: [128, 1], [1, 128] 2025-09-07T11:49:06.6070349Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:06.6071139Z triton_mm_179 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:06.6071922Z mm 0.0102 ms 90.0% 2025-09-07T11:49:06.6072624Z triton_mm_176 0.0102 ms 90.0% 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 2025-09-07T11:49:06.6073800Z triton_mm_177 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:06.6074960Z triton_mm_178 0.0102 ms 90.0% 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 2025-09-07T11:49:06.6076131Z triton_mm_182 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:06.6077305Z triton_mm_183 0.0102 ms 90.0% 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 2025-09-07T11:49:06.6078833Z triton_mm_184 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:06.6080026Z triton_mm_185 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:06.6081287Z triton_mm_186 0.0102 ms 90.0% 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 2025-09-07T11:49:06.6082318Z SingleProcess AUTOTUNE benchmarking takes 0.2770 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:07.2235126Z Autotune Choices Stats: 2025-09-07T11:49:07.2236353Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_207", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:07.2363577Z AUTOTUNE mm(3136x160, 160x128) 2025-09-07T11:49:07.2363950Z strides: [160, 1], [1, 160] 2025-09-07T11:49:07.2364252Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:07.2365037Z triton_mm_207 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 2025-09-07T11:49:07.2366231Z triton_mm_202 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:07.2367396Z triton_mm_203 0.0102 ms 90.0% 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 2025-09-07T11:49:07.2368851Z triton_mm_208 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 2025-09-07T11:49:07.2370037Z triton_mm_209 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:07.2371208Z triton_mm_210 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:07.2372471Z triton_mm_211 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 2025-09-07T11:49:07.2373976Z triton_mm_212 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:07.2375169Z triton_mm_213 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:07.2375905Z mm 0.0113 ms 81.8% 2025-09-07T11:49:07.2376435Z SingleProcess AUTOTUNE benchmarking takes 0.2670 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:07.5227396Z Autotune Choices Stats: 2025-09-07T11:49:07.5228618Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_232", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:07.5358954Z AUTOTUNE mm(3136x192, 192x128) 2025-09-07T11:49:07.5359260Z strides: [192, 1], [1, 192] 2025-09-07T11:49:07.5359557Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:07.5360328Z triton_mm_232 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 2025-09-07T11:49:07.5361891Z triton_mm_235 0.0102 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 2025-09-07T11:49:07.5363092Z triton_mm_236 0.0102 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 2025-09-07T11:49:07.5364288Z triton_mm_238 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=4, num_warps=8 2025-09-07T11:49:07.5365033Z mm 0.0113 ms 90.9% 2025-09-07T11:49:07.5365714Z triton_mm_227 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:07.5366881Z triton_mm_228 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:07.5368059Z triton_mm_233 0.0113 ms 90.9% 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 2025-09-07T11:49:07.5369241Z triton_mm_234 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:07.5370419Z triton_mm_237 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:07.5371490Z SingleProcess AUTOTUNE benchmarking takes 0.2620 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:07.8211031Z Autotune Choices Stats: 2025-09-07T11:49:07.8212271Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_252", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:07.8337599Z AUTOTUNE mm(3136x224, 224x128) 2025-09-07T11:49:07.8337893Z strides: [224, 1], [1, 224] 2025-09-07T11:49:07.8338192Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:07.8338960Z triton_mm_252 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:07.8346102Z triton_mm_253 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:07.8347311Z triton_mm_257 0.0113 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 2025-09-07T11:49:07.8348522Z triton_mm_258 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 2025-09-07T11:49:07.8349721Z triton_mm_259 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 2025-09-07T11:49:07.8350903Z triton_mm_260 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 2025-09-07T11:49:07.8352113Z triton_mm_261 0.0113 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 2025-09-07T11:49:07.8353621Z triton_mm_262 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 2025-09-07T11:49:07.8354818Z triton_mm_263 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 2025-09-07T11:49:07.8355551Z mm 0.0123 ms 91.7% 2025-09-07T11:49:07.8356086Z SingleProcess AUTOTUNE benchmarking takes 0.2618 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:08.1191172Z Autotune Choices Stats: 2025-09-07T11:49:08.1192403Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_282", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:08.1325319Z AUTOTUNE mm(3136x256, 256x128) 2025-09-07T11:49:08.1325632Z strides: [256, 1], [1, 256] 2025-09-07T11:49:08.1325936Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:08.1326721Z triton_mm_282 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 2025-09-07T11:49:08.1327470Z mm 0.0113 ms 90.9% 2025-09-07T11:49:08.1328161Z triton_mm_278 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:08.1329340Z triton_mm_283 0.0113 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 2025-09-07T11:49:08.1330505Z triton_mm_285 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:08.1331942Z triton_mm_286 0.0113 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 2025-09-07T11:49:08.1333368Z triton_mm_288 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:08.1334549Z triton_mm_276 0.0123 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 2025-09-07T11:49:08.1335837Z triton_mm_277 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:08.1337007Z triton_mm_284 0.0123 ms 83.3% 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 2025-09-07T11:49:08.1338097Z SingleProcess AUTOTUNE benchmarking takes 0.2626 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:08.4205881Z Autotune Choices Stats: 2025-09-07T11:49:08.4207079Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_307", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:08.4334622Z AUTOTUNE mm(3136x288, 288x128) 2025-09-07T11:49:08.4334983Z strides: [288, 1], [1, 288] 2025-09-07T11:49:08.4335273Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:08.4336060Z triton_mm_307 0.0113 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 2025-09-07T11:49:08.4337283Z triton_mm_313 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 2025-09-07T11:49:08.4338373Z mm 0.0123 ms 91.7% 2025-09-07T11:49:08.4339065Z triton_mm_302 0.0123 ms 91.7% 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 2025-09-07T11:49:08.4340234Z triton_mm_303 0.0123 ms 91.7% 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 2025-09-07T11:49:08.4341408Z triton_mm_308 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:08.4342593Z triton_mm_309 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 2025-09-07T11:49:08.4343776Z triton_mm_310 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 2025-09-07T11:49:08.4344952Z triton_mm_311 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:08.4346212Z triton_mm_312 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 2025-09-07T11:49:08.4347240Z SingleProcess AUTOTUNE benchmarking takes 0.2639 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:08.7229158Z Autotune Choices Stats: 2025-09-07T11:49:08.7230377Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_332", "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} 2025-09-07T11:49:08.7363480Z AUTOTUNE mm(3136x320, 320x128) 2025-09-07T11:49:08.7363796Z strides: [320, 1], [1, 320] 2025-09-07T11:49:08.7364110Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:08.7364873Z triton_mm_332 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 2025-09-07T11:49:08.7365625Z mm 0.0123 ms 91.7% 2025-09-07T11:49:08.7366485Z triton_mm_328 0.0123 ms 91.7% 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 2025-09-07T11:49:08.7367671Z triton_mm_333 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:08.7368874Z triton_mm_335 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 2025-09-07T11:49:08.7370050Z triton_mm_336 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 2025-09-07T11:49:08.7371217Z triton_mm_338 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 2025-09-07T11:49:08.7372404Z triton_mm_326 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 2025-09-07T11:49:08.7373817Z triton_mm_327 0.0133 ms 84.6% 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 2025-09-07T11:49:08.7375181Z triton_mm_334 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:08.7376214Z SingleProcess AUTOTUNE benchmarking takes 0.2657 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:09.0248135Z Autotune Choices Stats: 2025-09-07T11:49:09.0249350Z {"num_choices": 19, "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=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:09.0384345Z AUTOTUNE mm(3136x352, 352x128) 2025-09-07T11:49:09.0384729Z strides: [352, 1], [1, 352] 2025-09-07T11:49:09.0385068Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:09.0385856Z triton_mm_357 0.0123 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 2025-09-07T11:49:09.0387077Z triton_mm_358 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.0388282Z triton_mm_361 0.0123 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 2025-09-07T11:49:09.0389479Z triton_mm_363 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 2025-09-07T11:49:09.0390235Z mm 0.0133 ms 92.3% 2025-09-07T11:49:09.0390924Z triton_mm_351 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:09.0392341Z triton_mm_352 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:09.0393510Z triton_mm_353 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 2025-09-07T11:49:09.0394678Z triton_mm_360 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=4, num_warps=8 2025-09-07T11:49:09.0395956Z triton_mm_354 0.0143 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.0396983Z SingleProcess AUTOTUNE benchmarking takes 0.2651 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:09.3275640Z Autotune Choices Stats: 2025-09-07T11:49:09.3276915Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_382", "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} 2025-09-07T11:49:09.3411248Z AUTOTUNE mm(3136x384, 384x128) 2025-09-07T11:49:09.3411590Z strides: [384, 1], [1, 384] 2025-09-07T11:49:09.3411891Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:09.3412668Z triton_mm_382 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 2025-09-07T11:49:09.3414113Z triton_mm_383 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 2025-09-07T11:49:09.3415317Z triton_mm_386 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 2025-09-07T11:49:09.3416329Z mm 0.0133 ms 92.3% 2025-09-07T11:49:09.3417022Z triton_mm_377 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:09.3418185Z triton_mm_378 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 2025-09-07T11:49:09.3419363Z triton_mm_385 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=4, num_warps=8 2025-09-07T11:49:09.3420546Z triton_mm_388 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 2025-09-07T11:49:09.3421727Z triton_mm_376 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 2025-09-07T11:49:09.3422885Z triton_mm_379 0.0143 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.3423900Z SingleProcess AUTOTUNE benchmarking takes 0.2650 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:09.6318194Z Autotune Choices Stats: 2025-09-07T11:49:09.6319407Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_407", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:09.6460058Z AUTOTUNE mm(3136x416, 416x128) 2025-09-07T11:49:09.6460382Z strides: [416, 1], [1, 416] 2025-09-07T11:49:09.6460675Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:09.6461472Z triton_mm_407 0.0123 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 2025-09-07T11:49:09.6462230Z mm 0.0133 ms 92.3% 2025-09-07T11:49:09.6462913Z triton_mm_402 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:09.6464238Z triton_mm_403 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 2025-09-07T11:49:09.6465465Z triton_mm_408 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.6466646Z triton_mm_410 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=4, num_warps=8 2025-09-07T11:49:09.6467823Z triton_mm_411 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:09.6469007Z triton_mm_413 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 2025-09-07T11:49:09.6470189Z triton_mm_401 0.0154 ms 80.0% 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 2025-09-07T11:49:09.6471373Z triton_mm_404 0.0154 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.6472399Z SingleProcess AUTOTUNE benchmarking takes 0.2677 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:09.9376999Z Autotune Choices Stats: 2025-09-07T11:49:09.9378204Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_432", "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} 2025-09-07T11:49:09.9519327Z AUTOTUNE mm(3136x448, 448x128) 2025-09-07T11:49:09.9519656Z strides: [448, 1], [1, 448] 2025-09-07T11:49:09.9519957Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:09.9520729Z triton_mm_432 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 2025-09-07T11:49:09.9521487Z mm 0.0133 ms 92.3% 2025-09-07T11:49:09.9522184Z triton_mm_433 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.9523367Z triton_mm_436 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 2025-09-07T11:49:09.9524544Z triton_mm_426 0.0143 ms 85.7% 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 2025-09-07T11:49:09.9525721Z triton_mm_427 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 2025-09-07T11:49:09.9526890Z triton_mm_428 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 2025-09-07T11:49:09.9528198Z triton_mm_435 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 2025-09-07T11:49:09.9529366Z triton_mm_438 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 2025-09-07T11:49:09.9530550Z triton_mm_429 0.0154 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:09.9531645Z SingleProcess AUTOTUNE benchmarking takes 0.2685 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:10.2436469Z Autotune Choices Stats: 2025-09-07T11:49:10.2438013Z {"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_457", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8"} 2025-09-07T11:49:10.2573589Z AUTOTUNE mm(3136x480, 480x128) 2025-09-07T11:49:10.2573894Z strides: [480, 1], [1, 480] 2025-09-07T11:49:10.2574195Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:10.2574503Z mm 0.0133 ms 100.0% 2025-09-07T11:49:10.2575211Z triton_mm_457 0.0133 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 2025-09-07T11:49:10.2576434Z triton_mm_458 0.0133 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:10.2577635Z triton_mm_451 0.0143 ms 92.9% 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 2025-09-07T11:49:10.2579138Z triton_mm_452 0.0143 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:10.2580312Z triton_mm_453 0.0143 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:10.2581478Z triton_mm_460 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 2025-09-07T11:49:10.2582666Z triton_mm_461 0.0143 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:10.2583852Z triton_mm_463 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 2025-09-07T11:49:10.2585103Z triton_mm_454 0.0154 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:10.2586155Z SingleProcess AUTOTUNE benchmarking takes 0.2685 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:10.5404121Z Autotune Choices Stats: 2025-09-07T11:49:10.5405339Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_494", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:10.5543891Z AUTOTUNE mm(784x256, 256x128) 2025-09-07T11:49:10.5544213Z strides: [256, 1], [1, 256] 2025-09-07T11:49:10.5544812Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:10.5545675Z triton_mm_494 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:10.5546883Z triton_mm_495 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:10.5548075Z triton_mm_496 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:10.5549378Z triton_mm_497 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:10.5550562Z triton_mm_500 0.0092 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 2025-09-07T11:49:10.5551755Z triton_mm_501 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:10.5552500Z mm 0.0102 ms 90.0% 2025-09-07T11:49:10.5553179Z triton_mm_503 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:10.5554356Z triton_mm_504 0.0102 ms 90.0% 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 2025-09-07T11:49:10.5555537Z triton_mm_506 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:10.5556567Z SingleProcess AUTOTUNE benchmarking takes 0.2596 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:11.1578183Z Autotune Choices Stats: 2025-09-07T11:49:11.1579779Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_520", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:11.1713245Z AUTOTUNE mm(784x288, 288x128) 2025-09-07T11:49:11.1713580Z strides: [288, 1], [1, 288] 2025-09-07T11:49:11.1713888Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:11.1714665Z triton_mm_520 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:11.1715865Z triton_mm_521 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:11.1717144Z triton_mm_522 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 2025-09-07T11:49:11.1718350Z triton_mm_519 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 2025-09-07T11:49:11.1719537Z triton_mm_525 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 2025-09-07T11:49:11.1720726Z triton_mm_526 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 2025-09-07T11:49:11.1721474Z mm 0.0113 ms 81.8% 2025-09-07T11:49:11.1722150Z triton_mm_528 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:11.1723522Z triton_mm_529 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 2025-09-07T11:49:11.1724707Z triton_mm_530 0.0113 ms 81.8% 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 2025-09-07T11:49:11.1725733Z SingleProcess AUTOTUNE benchmarking takes 0.2603 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:11.4549261Z Autotune Choices Stats: 2025-09-07T11:49:11.4550460Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_545", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:11.4684792Z AUTOTUNE mm(784x320, 320x128) 2025-09-07T11:49:11.4685128Z strides: [320, 1], [1, 320] 2025-09-07T11:49:11.4685433Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:11.4686221Z triton_mm_545 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:11.4687391Z triton_mm_546 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:11.4688596Z triton_mm_547 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 2025-09-07T11:49:11.4689799Z triton_mm_544 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 2025-09-07T11:49:11.4691324Z triton_mm_550 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:11.4692517Z triton_mm_551 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 2025-09-07T11:49:11.4693510Z mm 0.0113 ms 81.8% 2025-09-07T11:49:11.4694203Z triton_mm_553 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:11.4695372Z triton_mm_554 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:11.4696549Z triton_mm_556 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:11.4697588Z SingleProcess AUTOTUNE benchmarking takes 0.2608 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:11.7561195Z Autotune Choices Stats: 2025-09-07T11:49:11.7562362Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_571", "best_kernel_desc": "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", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:11.7704943Z AUTOTUNE mm(784x352, 352x128) 2025-09-07T11:49:11.7705291Z strides: [352, 1], [1, 352] 2025-09-07T11:49:11.7705578Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:11.7706348Z triton_mm_571 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:11.7707810Z triton_mm_572 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 2025-09-07T11:49:11.7709011Z triton_mm_569 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 2025-09-07T11:49:11.7710193Z triton_mm_570 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:11.7711441Z triton_mm_575 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 2025-09-07T11:49:11.7712625Z triton_mm_576 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 2025-09-07T11:49:11.7713372Z mm 0.0113 ms 81.8% 2025-09-07T11:49:11.7714064Z triton_mm_578 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:11.7715244Z triton_mm_579 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 2025-09-07T11:49:11.7716418Z triton_mm_581 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:11.7717444Z SingleProcess AUTOTUNE benchmarking takes 0.2651 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:12.0553875Z Autotune Choices Stats: 2025-09-07T11:49:12.0555445Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_597", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:12.0690252Z AUTOTUNE mm(784x384, 384x128) 2025-09-07T11:49:12.0690567Z strides: [384, 1], [1, 384] 2025-09-07T11:49:12.0690894Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:12.0691677Z triton_mm_597 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:12.0693129Z triton_mm_594 0.0102 ms 90.0% 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 2025-09-07T11:49:12.0694307Z triton_mm_595 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:12.0695499Z triton_mm_596 0.0102 ms 90.0% 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 2025-09-07T11:49:12.0696665Z triton_mm_600 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:12.0697843Z triton_mm_601 0.0102 ms 90.0% 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 2025-09-07T11:49:12.0698585Z mm 0.0113 ms 81.8% 2025-09-07T11:49:12.0699271Z triton_mm_604 0.0113 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:12.0700436Z triton_mm_603 0.0123 ms 75.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:12.0701823Z triton_mm_606 0.0123 ms 75.0% 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 2025-09-07T11:49:12.0702855Z SingleProcess AUTOTUNE benchmarking takes 0.2622 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:12.3605570Z Autotune Choices Stats: 2025-09-07T11:49:12.3606784Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_620", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:12.3745377Z AUTOTUNE mm(784x416, 416x128) 2025-09-07T11:49:12.3745709Z strides: [416, 1], [1, 416] 2025-09-07T11:49:12.3746028Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:12.3746807Z triton_mm_620 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:12.3748009Z triton_mm_621 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:12.3749206Z triton_mm_622 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 2025-09-07T11:49:12.3749973Z mm 0.0113 ms 90.9% 2025-09-07T11:49:12.3750670Z triton_mm_619 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 2025-09-07T11:49:12.3751868Z triton_mm_625 0.0113 ms 90.9% 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 2025-09-07T11:49:12.3753327Z triton_mm_626 0.0113 ms 90.9% 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 2025-09-07T11:49:12.3754523Z triton_mm_628 0.0123 ms 83.3% 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 2025-09-07T11:49:12.3755708Z triton_mm_629 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:12.3756893Z triton_mm_631 0.0133 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=4, num_warps=8 2025-09-07T11:49:12.3757923Z SingleProcess AUTOTUNE benchmarking takes 0.2694 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:12.6788290Z Autotune Choices Stats: 2025-09-07T11:49:12.6789555Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_647", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:12.6933459Z AUTOTUNE mm(784x448, 448x128) 2025-09-07T11:49:12.6933770Z strides: [448, 1], [1, 448] 2025-09-07T11:49:12.6934078Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:12.6934877Z triton_mm_647 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 2025-09-07T11:49:12.6935639Z mm 0.0113 ms 90.9% 2025-09-07T11:49:12.6936324Z triton_mm_644 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 2025-09-07T11:49:12.6937804Z triton_mm_645 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:12.6938982Z triton_mm_646 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:12.6940160Z triton_mm_651 0.0113 ms 90.9% 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 2025-09-07T11:49:12.6941429Z triton_mm_650 0.0123 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 2025-09-07T11:49:12.6942608Z triton_mm_654 0.0123 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 2025-09-07T11:49:12.6943780Z triton_mm_653 0.0133 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 2025-09-07T11:49:12.6944962Z triton_mm_656 0.0133 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=4, num_warps=8 2025-09-07T11:49:12.6946063Z SingleProcess AUTOTUNE benchmarking takes 0.2804 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:12.9974802Z Autotune Choices Stats: 2025-09-07T11:49:12.9976005Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_672", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:13.0120541Z AUTOTUNE mm(784x480, 480x128) 2025-09-07T11:49:13.0120892Z strides: [480, 1], [1, 480] 2025-09-07T11:49:13.0121188Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:13.0122453Z triton_mm_672 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 2025-09-07T11:49:13.0123237Z mm 0.0113 ms 90.9% 2025-09-07T11:49:13.0123933Z triton_mm_670 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:13.0125129Z triton_mm_671 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:13.0126316Z triton_mm_669 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:13.0127514Z triton_mm_675 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:13.0128708Z triton_mm_676 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:13.0129916Z triton_mm_678 0.0133 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 2025-09-07T11:49:13.0131123Z triton_mm_679 0.0133 ms 76.9% 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 2025-09-07T11:49:13.0132347Z triton_mm_681 0.0133 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=4, num_warps=8 2025-09-07T11:49:13.0133800Z SingleProcess AUTOTUNE benchmarking takes 0.2803 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:13.9204616Z Autotune Choices Stats: 2025-09-07T11:49:13.9205831Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_697", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:13.9356198Z AUTOTUNE mm(784x512, 512x128) 2025-09-07T11:49:13.9356505Z strides: [512, 1], [1, 512] 2025-09-07T11:49:13.9356809Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:13.9357574Z triton_mm_697 0.0102 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 2025-09-07T11:49:13.9358346Z mm 0.0113 ms 90.9% 2025-09-07T11:49:13.9359047Z triton_mm_696 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:13.9360233Z triton_mm_701 0.0113 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 2025-09-07T11:49:13.9361413Z triton_mm_694 0.0123 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 2025-09-07T11:49:13.9362595Z triton_mm_695 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:13.9363748Z triton_mm_700 0.0123 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 2025-09-07T11:49:13.9365173Z triton_mm_703 0.0133 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 2025-09-07T11:49:13.9366370Z triton_mm_704 0.0133 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:13.9367558Z triton_mm_706 0.0143 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 2025-09-07T11:49:13.9368594Z SingleProcess AUTOTUNE benchmarking takes 0.8844 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:14.2496119Z Autotune Choices Stats: 2025-09-07T11:49:14.2497323Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_722", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:14.2646077Z AUTOTUNE mm(784x544, 544x128) 2025-09-07T11:49:14.2659709Z strides: [544, 1], [1, 544] 2025-09-07T11:49:14.2660060Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:14.2660948Z triton_mm_722 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 2025-09-07T11:49:14.2661724Z mm 0.0113 ms 90.9% 2025-09-07T11:49:14.2662444Z triton_mm_720 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:14.2663653Z triton_mm_721 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:14.2665147Z triton_mm_726 0.0113 ms 90.9% 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 2025-09-07T11:49:14.2666343Z triton_mm_719 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:14.2667556Z triton_mm_725 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:14.2668873Z triton_mm_729 0.0133 ms 76.9% 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 2025-09-07T11:49:14.2670060Z triton_mm_728 0.0143 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=4, num_warps=8 2025-09-07T11:49:14.2671243Z triton_mm_731 0.0143 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 2025-09-07T11:49:14.2672253Z SingleProcess AUTOTUNE benchmarking takes 0.2888 seconds and 0.0004 seconds precompiling for 19 choices 2025-09-07T11:49:14.5624677Z Autotune Choices Stats: 2025-09-07T11:49:14.5625994Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_747", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:14.5771542Z AUTOTUNE mm(784x576, 576x128) 2025-09-07T11:49:14.5771870Z strides: [576, 1], [1, 576] 2025-09-07T11:49:14.5772160Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:14.5773207Z triton_mm_747 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 2025-09-07T11:49:14.5774327Z mm 0.0113 ms 90.9% 2025-09-07T11:49:14.5775024Z triton_mm_745 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:14.5776201Z triton_mm_746 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:14.5777377Z triton_mm_751 0.0113 ms 90.9% 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 2025-09-07T11:49:14.5778577Z triton_mm_744 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:14.5779764Z triton_mm_750 0.0123 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 2025-09-07T11:49:14.5780936Z triton_mm_754 0.0133 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:14.5782117Z triton_mm_753 0.0143 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=4, num_warps=8 2025-09-07T11:49:14.5783300Z triton_mm_756 0.0143 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 2025-09-07T11:49:14.5784326Z SingleProcess AUTOTUNE benchmarking takes 0.2738 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:14.8729757Z Autotune Choices Stats: 2025-09-07T11:49:14.8730953Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_772", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:14.8876119Z AUTOTUNE mm(784x608, 608x128) 2025-09-07T11:49:14.8876433Z strides: [608, 1], [1, 608] 2025-09-07T11:49:14.8876725Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:14.8877719Z triton_mm_772 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 2025-09-07T11:49:14.8878919Z triton_mm_770 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:14.8880108Z triton_mm_771 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:14.8881292Z triton_mm_776 0.0113 ms 90.9% 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 2025-09-07T11:49:14.8882030Z mm 0.0123 ms 83.3% 2025-09-07T11:49:14.8882716Z triton_mm_769 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:14.8883891Z triton_mm_775 0.0133 ms 76.9% 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 2025-09-07T11:49:14.8885074Z triton_mm_779 0.0143 ms 71.4% 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 2025-09-07T11:49:14.8886438Z triton_mm_781 0.0143 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 2025-09-07T11:49:14.8887625Z triton_mm_778 0.0154 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 2025-09-07T11:49:14.8888643Z SingleProcess AUTOTUNE benchmarking takes 0.2728 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:15.1852077Z Autotune Choices Stats: 2025-09-07T11:49:15.1853554Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_797", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:15.1999296Z AUTOTUNE mm(784x640, 640x128) 2025-09-07T11:49:15.1999657Z strides: [640, 1], [1, 640] 2025-09-07T11:49:15.1999960Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:15.2000770Z triton_mm_797 0.0102 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 2025-09-07T11:49:15.2001960Z triton_mm_801 0.0113 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 2025-09-07T11:49:15.2002700Z mm 0.0123 ms 83.3% 2025-09-07T11:49:15.2003385Z triton_mm_794 0.0123 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 2025-09-07T11:49:15.2004557Z triton_mm_795 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:15.2005998Z triton_mm_796 0.0123 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 2025-09-07T11:49:15.2007160Z triton_mm_800 0.0133 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 2025-09-07T11:49:15.2008334Z triton_mm_804 0.0143 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:15.2009595Z triton_mm_803 0.0154 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 2025-09-07T11:49:15.2010772Z triton_mm_806 0.0154 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:15.2011796Z SingleProcess AUTOTUNE benchmarking takes 0.2745 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:15.4977233Z Autotune Choices Stats: 2025-09-07T11:49:15.4978451Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_822", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:15.5123951Z AUTOTUNE mm(784x672, 672x128) 2025-09-07T11:49:15.5124276Z strides: [672, 1], [1, 672] 2025-09-07T11:49:15.5124564Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:15.5125348Z triton_mm_822 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:15.5126118Z mm 0.0123 ms 91.7% 2025-09-07T11:49:15.5127147Z triton_mm_820 0.0123 ms 91.7% 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 2025-09-07T11:49:15.5128319Z triton_mm_821 0.0123 ms 91.7% 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 2025-09-07T11:49:15.5129507Z triton_mm_826 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:15.5130703Z triton_mm_819 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 2025-09-07T11:49:15.5131884Z triton_mm_825 0.0133 ms 84.6% 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 2025-09-07T11:49:15.5133336Z triton_mm_829 0.0143 ms 78.6% 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 2025-09-07T11:49:15.5134525Z triton_mm_828 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:15.5135771Z triton_mm_831 0.0154 ms 73.3% 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 2025-09-07T11:49:15.5136781Z SingleProcess AUTOTUNE benchmarking takes 0.2749 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:15.8097211Z Autotune Choices Stats: 2025-09-07T11:49:15.8098445Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_847", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:15.8244670Z AUTOTUNE mm(784x704, 704x128) 2025-09-07T11:49:15.8245050Z strides: [704, 1], [1, 704] 2025-09-07T11:49:15.8245350Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:15.8246118Z triton_mm_847 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:15.8247017Z mm 0.0123 ms 91.7% 2025-09-07T11:49:15.8247706Z triton_mm_845 0.0123 ms 91.7% 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 2025-09-07T11:49:15.8248869Z triton_mm_846 0.0123 ms 91.7% 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 2025-09-07T11:49:15.8250056Z triton_mm_851 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:15.8251238Z triton_mm_844 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 2025-09-07T11:49:15.8252402Z triton_mm_850 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:15.8253811Z triton_mm_854 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:15.8254986Z triton_mm_856 0.0154 ms 73.3% 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 2025-09-07T11:49:15.8256367Z triton_mm_853 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:15.8257391Z SingleProcess AUTOTUNE benchmarking takes 0.2744 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:16.1228131Z Autotune Choices Stats: 2025-09-07T11:49:16.1229371Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_872", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:16.1379992Z AUTOTUNE mm(784x736, 736x128) 2025-09-07T11:49:16.1380309Z strides: [736, 1], [1, 736] 2025-09-07T11:49:16.1380612Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:16.1381413Z triton_mm_872 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:16.1382189Z mm 0.0123 ms 91.7% 2025-09-07T11:49:16.1382895Z triton_mm_870 0.0123 ms 91.7% 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 2025-09-07T11:49:16.1384055Z triton_mm_871 0.0123 ms 91.7% 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 2025-09-07T11:49:16.1385305Z triton_mm_876 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:16.1386501Z triton_mm_869 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 2025-09-07T11:49:16.1387973Z triton_mm_875 0.0143 ms 78.6% 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 2025-09-07T11:49:16.1389160Z triton_mm_879 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:16.1390351Z triton_mm_878 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:16.1391631Z triton_mm_881 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:16.1392653Z SingleProcess AUTOTUNE benchmarking takes 0.2758 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:16.4393461Z Autotune Choices Stats: 2025-09-07T11:49:16.4394695Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_897", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:16.4542533Z AUTOTUNE mm(784x768, 768x128) 2025-09-07T11:49:16.4542839Z strides: [768, 1], [1, 768] 2025-09-07T11:49:16.4543142Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:16.4543913Z triton_mm_897 0.0113 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 2025-09-07T11:49:16.4544675Z mm 0.0123 ms 91.7% 2025-09-07T11:49:16.4545430Z triton_mm_901 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 2025-09-07T11:49:16.4546948Z triton_mm_894 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:16.4548127Z triton_mm_895 0.0133 ms 84.6% 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 2025-09-07T11:49:16.4549297Z triton_mm_896 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 2025-09-07T11:49:16.4550466Z triton_mm_900 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:16.4551646Z triton_mm_904 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:16.4552825Z triton_mm_903 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:16.4554000Z triton_mm_906 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:16.4555014Z SingleProcess AUTOTUNE benchmarking takes 0.2782 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:16.7553508Z Autotune Choices Stats: 2025-09-07T11:49:16.7554736Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_922", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:16.7702085Z AUTOTUNE mm(784x800, 800x128) 2025-09-07T11:49:16.7702442Z strides: [800, 1], [1, 800] 2025-09-07T11:49:16.7702744Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:16.7703552Z triton_mm_922 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:16.7704312Z mm 0.0133 ms 84.6% 2025-09-07T11:49:16.7704997Z triton_mm_920 0.0133 ms 84.6% 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 2025-09-07T11:49:16.7706476Z triton_mm_921 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 2025-09-07T11:49:16.7707655Z triton_mm_926 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:16.7708864Z triton_mm_919 0.0143 ms 78.6% 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 2025-09-07T11:49:16.7710030Z triton_mm_925 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:16.7711212Z triton_mm_929 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:16.7712396Z triton_mm_928 0.0174 ms 64.7% 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 2025-09-07T11:49:16.7713571Z triton_mm_931 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:16.7714591Z SingleProcess AUTOTUNE benchmarking takes 0.2776 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:17.0705318Z Autotune Choices Stats: 2025-09-07T11:49:17.0706580Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_947", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:17.0853863Z AUTOTUNE mm(784x832, 832x128) 2025-09-07T11:49:17.0854194Z strides: [832, 1], [1, 832] 2025-09-07T11:49:17.0854500Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:17.0855297Z triton_mm_947 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:17.0856082Z mm 0.0123 ms 91.7% 2025-09-07T11:49:17.0856779Z triton_mm_945 0.0133 ms 84.6% 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 2025-09-07T11:49:17.0857938Z triton_mm_946 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 2025-09-07T11:49:17.0859118Z triton_mm_951 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:17.0860312Z triton_mm_944 0.0143 ms 78.6% 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 2025-09-07T11:49:17.0861488Z triton_mm_950 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:17.0862918Z triton_mm_954 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:17.0864095Z triton_mm_953 0.0174 ms 64.7% 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 2025-09-07T11:49:17.0865359Z triton_mm_956 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:17.0866479Z SingleProcess AUTOTUNE benchmarking takes 0.2774 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:17.3876772Z Autotune Choices Stats: 2025-09-07T11:49:17.3877975Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_972", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:17.4025871Z AUTOTUNE mm(784x864, 864x128) 2025-09-07T11:49:17.4026195Z strides: [864, 1], [1, 864] 2025-09-07T11:49:17.4026484Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:17.4027262Z triton_mm_972 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:17.4028028Z mm 0.0133 ms 84.6% 2025-09-07T11:49:17.4028718Z triton_mm_970 0.0133 ms 84.6% 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 2025-09-07T11:49:17.4029902Z triton_mm_971 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 2025-09-07T11:49:17.4031380Z triton_mm_976 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:17.4032585Z triton_mm_969 0.0143 ms 78.6% 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 2025-09-07T11:49:17.4033759Z triton_mm_975 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:17.4034946Z triton_mm_978 0.0174 ms 64.7% 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 2025-09-07T11:49:17.4036132Z triton_mm_979 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:17.4037334Z triton_mm_981 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:17.4038347Z SingleProcess AUTOTUNE benchmarking takes 0.2794 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:17.7056089Z Autotune Choices Stats: 2025-09-07T11:49:17.7057320Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_997", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:17.7214134Z AUTOTUNE mm(784x896, 896x128) 2025-09-07T11:49:17.7214430Z strides: [896, 1], [1, 896] 2025-09-07T11:49:17.7214737Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:17.7215803Z triton_mm_997 0.0113 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 2025-09-07T11:49:17.7216554Z mm 0.0123 ms 91.7% 2025-09-07T11:49:17.7217262Z triton_mm_1001 0.0133 ms 84.6% 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 2025-09-07T11:49:17.7218437Z triton_mm_994 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:17.7219709Z triton_mm_995 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 2025-09-07T11:49:17.7220869Z triton_mm_996 0.0143 ms 78.6% 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 2025-09-07T11:49:17.7222054Z triton_mm_1000 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:17.7223238Z triton_mm_1004 0.0164 ms 68.8% 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 2025-09-07T11:49:17.7224426Z triton_mm_1006 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:17.7225690Z triton_mm_1003 0.0184 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:17.7226714Z SingleProcess AUTOTUNE benchmarking takes 0.2809 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:18.0255591Z Autotune Choices Stats: 2025-09-07T11:49:18.0257252Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1022", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:18.0410085Z AUTOTUNE mm(784x928, 928x128) 2025-09-07T11:49:18.0410479Z strides: [928, 1], [1, 928] 2025-09-07T11:49:18.0410792Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:18.0411579Z triton_mm_1022 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.0412349Z mm 0.0133 ms 92.3% 2025-09-07T11:49:18.0413272Z triton_mm_1026 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.0414475Z triton_mm_1020 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 2025-09-07T11:49:18.0415652Z triton_mm_1021 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 2025-09-07T11:49:18.0416840Z triton_mm_1019 0.0154 ms 80.0% 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 2025-09-07T11:49:18.0418028Z triton_mm_1025 0.0164 ms 75.0% 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 2025-09-07T11:49:18.0419212Z triton_mm_1028 0.0184 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 2025-09-07T11:49:18.0420572Z triton_mm_1029 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:18.0421769Z triton_mm_1031 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:18.0422783Z SingleProcess AUTOTUNE benchmarking takes 0.2820 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:18.3457566Z Autotune Choices Stats: 2025-09-07T11:49:18.3458749Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1047", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:18.3608984Z AUTOTUNE mm(784x960, 960x128) 2025-09-07T11:49:18.3609351Z strides: [960, 1], [1, 960] 2025-09-07T11:49:18.3609638Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:18.3610436Z triton_mm_1047 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.3611193Z mm 0.0133 ms 92.3% 2025-09-07T11:49:18.3611895Z triton_mm_1051 0.0133 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.3613310Z triton_mm_1045 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 2025-09-07T11:49:18.3614473Z triton_mm_1046 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 2025-09-07T11:49:18.3615928Z triton_mm_1044 0.0154 ms 80.0% 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 2025-09-07T11:49:18.3617123Z triton_mm_1050 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 2025-09-07T11:49:18.3618303Z triton_mm_1054 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 2025-09-07T11:49:18.3619483Z triton_mm_1053 0.0184 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 2025-09-07T11:49:18.3620660Z triton_mm_1056 0.0195 ms 63.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:18.3621692Z SingleProcess AUTOTUNE benchmarking takes 0.2818 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:18.6688899Z Autotune Choices Stats: 2025-09-07T11:49:18.6690138Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1072", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.01228800043463707, "best_triton_pos": 0} 2025-09-07T11:49:18.6841082Z AUTOTUNE mm(784x992, 992x128) 2025-09-07T11:49:18.6841374Z strides: [992, 1], [1, 992] 2025-09-07T11:49:18.6841678Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:18.6842456Z triton_mm_1072 0.0123 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.6843476Z mm 0.0133 ms 92.3% 2025-09-07T11:49:18.6844184Z triton_mm_1070 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 2025-09-07T11:49:18.6845362Z triton_mm_1071 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 2025-09-07T11:49:18.6846562Z triton_mm_1076 0.0143 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.6847854Z triton_mm_1069 0.0154 ms 80.0% 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 2025-09-07T11:49:18.6849051Z triton_mm_1075 0.0164 ms 75.0% 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 2025-09-07T11:49:18.6850248Z triton_mm_1078 0.0184 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 2025-09-07T11:49:18.6851440Z triton_mm_1079 0.0184 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:18.6852636Z triton_mm_1081 0.0195 ms 63.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:18.6853941Z SingleProcess AUTOTUNE benchmarking takes 0.2850 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:18.9761562Z Autotune Choices Stats: 2025-09-07T11:49:18.9762767Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1115", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009216000325977802, "best_triton_pos": 0} 2025-09-07T11:49:18.9913013Z AUTOTUNE mm(196x512, 512x128) 2025-09-07T11:49:18.9913367Z strides: [512, 1], [1, 512] 2025-09-07T11:49:18.9913673Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:18.9914467Z triton_mm_1115 0.0092 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:18.9915678Z triton_mm_1112 0.0102 ms 90.0% 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 2025-09-07T11:49:18.9916858Z triton_mm_1113 0.0102 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:18.9918046Z triton_mm_1114 0.0102 ms 90.0% 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 2025-09-07T11:49:18.9919211Z triton_mm_1119 0.0102 ms 90.0% 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 2025-09-07T11:49:18.9919949Z mm 0.0113 ms 81.8% 2025-09-07T11:49:18.9920634Z triton_mm_1118 0.0113 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 2025-09-07T11:49:18.9921814Z triton_mm_1122 0.0123 ms 75.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:18.9922997Z triton_mm_1121 0.0133 ms 69.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:18.9924282Z triton_mm_1124 0.0133 ms 69.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:18.9925291Z SingleProcess AUTOTUNE benchmarking takes 0.2686 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:19.5904302Z Autotune Choices Stats: 2025-09-07T11:49:19.5905574Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1138", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:19.6049248Z AUTOTUNE mm(196x544, 544x128) 2025-09-07T11:49:19.6049572Z strides: [544, 1], [1, 544] 2025-09-07T11:49:19.6049872Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:19.6050668Z triton_mm_1138 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:19.6051870Z triton_mm_1139 0.0102 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:19.6053293Z triton_mm_1140 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 2025-09-07T11:49:19.6054058Z mm 0.0113 ms 90.9% 2025-09-07T11:49:19.6054762Z triton_mm_1137 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 2025-09-07T11:49:19.6055966Z triton_mm_1144 0.0113 ms 90.9% 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 2025-09-07T11:49:19.6057427Z triton_mm_1143 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:19.6058619Z triton_mm_1147 0.0133 ms 76.9% 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 2025-09-07T11:49:19.6059817Z triton_mm_1149 0.0133 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=4, num_warps=8 2025-09-07T11:49:19.6061012Z triton_mm_1146 0.0143 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=4, num_warps=8 2025-09-07T11:49:19.6062046Z SingleProcess AUTOTUNE benchmarking takes 0.2700 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:19.8985384Z Autotune Choices Stats: 2025-09-07T11:49:19.8986614Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1165", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:19.9137190Z AUTOTUNE mm(196x576, 576x128) 2025-09-07T11:49:19.9137493Z strides: [576, 1], [1, 576] 2025-09-07T11:49:19.9137799Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:19.9138585Z triton_mm_1165 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 2025-09-07T11:49:19.9139354Z mm 0.0113 ms 90.9% 2025-09-07T11:49:19.9140049Z triton_mm_1162 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 2025-09-07T11:49:19.9141477Z triton_mm_1163 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:19.9142661Z triton_mm_1164 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:19.9143837Z triton_mm_1169 0.0113 ms 90.9% 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 2025-09-07T11:49:19.9145176Z triton_mm_1168 0.0123 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 2025-09-07T11:49:19.9146361Z triton_mm_1172 0.0123 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 2025-09-07T11:49:19.9147554Z triton_mm_1174 0.0133 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=4, num_warps=8 2025-09-07T11:49:19.9148749Z triton_mm_1171 0.0143 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=4, num_warps=8 2025-09-07T11:49:19.9149770Z SingleProcess AUTOTUNE benchmarking takes 0.2710 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:20.2200148Z Autotune Choices Stats: 2025-09-07T11:49:20.2201372Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1190", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:20.2350799Z AUTOTUNE mm(196x608, 608x128) 2025-09-07T11:49:20.2351102Z strides: [608, 1], [1, 608] 2025-09-07T11:49:20.2351387Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:20.2352562Z triton_mm_1190 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 2025-09-07T11:49:20.2353333Z mm 0.0113 ms 90.9% 2025-09-07T11:49:20.2354032Z triton_mm_1187 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 2025-09-07T11:49:20.2355239Z triton_mm_1188 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:20.2356436Z triton_mm_1189 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:20.2357621Z triton_mm_1194 0.0113 ms 90.9% 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 2025-09-07T11:49:20.2358817Z triton_mm_1193 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:20.2360014Z triton_mm_1197 0.0133 ms 76.9% 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 2025-09-07T11:49:20.2361205Z triton_mm_1196 0.0143 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=4, num_warps=8 2025-09-07T11:49:20.2362400Z triton_mm_1199 0.0143 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 2025-09-07T11:49:20.2363541Z SingleProcess AUTOTUNE benchmarking takes 0.2845 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:20.5286846Z Autotune Choices Stats: 2025-09-07T11:49:20.5288085Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1215", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:20.5434677Z AUTOTUNE mm(196x640, 640x128) 2025-09-07T11:49:20.5434999Z strides: [640, 1], [1, 640] 2025-09-07T11:49:20.5435307Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:20.5436085Z triton_mm_1215 0.0102 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 2025-09-07T11:49:20.5436866Z mm 0.0113 ms 90.9% 2025-09-07T11:49:20.5437570Z triton_mm_1212 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:20.5438755Z triton_mm_1213 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:20.5439931Z triton_mm_1214 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:20.5441108Z triton_mm_1219 0.0113 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 2025-09-07T11:49:20.5442288Z triton_mm_1218 0.0123 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 2025-09-07T11:49:20.5443683Z triton_mm_1222 0.0133 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:20.5444875Z triton_mm_1224 0.0143 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 2025-09-07T11:49:20.5446066Z triton_mm_1221 0.0154 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 2025-09-07T11:49:20.5447095Z SingleProcess AUTOTUNE benchmarking takes 0.2713 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:20.8519837Z Autotune Choices Stats: 2025-09-07T11:49:20.8521048Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1240", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:20.8673737Z AUTOTUNE mm(196x672, 672x128) 2025-09-07T11:49:20.8674104Z strides: [672, 1], [1, 672] 2025-09-07T11:49:20.8674407Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:20.8675183Z triton_mm_1240 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 2025-09-07T11:49:20.8675970Z mm 0.0113 ms 90.9% 2025-09-07T11:49:20.8676669Z triton_mm_1238 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:20.8677834Z triton_mm_1239 0.0113 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:20.8679274Z triton_mm_1237 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:20.8680471Z triton_mm_1244 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:20.8681668Z triton_mm_1243 0.0133 ms 76.9% 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 2025-09-07T11:49:20.8682966Z triton_mm_1247 0.0143 ms 71.4% 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 2025-09-07T11:49:20.8684164Z triton_mm_1249 0.0143 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 2025-09-07T11:49:20.8685364Z triton_mm_1246 0.0154 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 2025-09-07T11:49:20.8686386Z SingleProcess AUTOTUNE benchmarking takes 0.2859 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:21.1628415Z Autotune Choices Stats: 2025-09-07T11:49:21.1629661Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1265", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:21.1780128Z AUTOTUNE mm(196x704, 704x128) 2025-09-07T11:49:21.1780488Z strides: [704, 1], [1, 704] 2025-09-07T11:49:21.1780823Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:21.1781617Z triton_mm_1265 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 2025-09-07T11:49:21.1782728Z mm 0.0113 ms 90.9% 2025-09-07T11:49:21.1783436Z triton_mm_1269 0.0113 ms 90.9% 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 2025-09-07T11:49:21.1784644Z triton_mm_1262 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:21.1785936Z triton_mm_1263 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:21.1787123Z triton_mm_1264 0.0123 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 2025-09-07T11:49:21.1788312Z triton_mm_1268 0.0133 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 2025-09-07T11:49:21.1789482Z triton_mm_1272 0.0133 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:21.1790659Z triton_mm_1271 0.0154 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 2025-09-07T11:49:21.1791836Z triton_mm_1274 0.0154 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:21.1792860Z SingleProcess AUTOTUNE benchmarking takes 0.2731 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:21.4768798Z Autotune Choices Stats: 2025-09-07T11:49:21.4770045Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1290", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:21.4929341Z AUTOTUNE mm(196x736, 736x128) 2025-09-07T11:49:21.4929681Z strides: [736, 1], [1, 736] 2025-09-07T11:49:21.4929989Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:21.4932359Z triton_mm_1290 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 2025-09-07T11:49:21.4933401Z mm 0.0123 ms 83.3% 2025-09-07T11:49:21.4934112Z triton_mm_1287 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:21.4935311Z triton_mm_1288 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:21.4936501Z triton_mm_1289 0.0123 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 2025-09-07T11:49:21.4937683Z triton_mm_1294 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:21.4938883Z triton_mm_1293 0.0133 ms 76.9% 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 2025-09-07T11:49:21.4940075Z triton_mm_1297 0.0143 ms 71.4% 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 2025-09-07T11:49:21.4941488Z triton_mm_1299 0.0154 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:21.4942678Z triton_mm_1296 0.0164 ms 62.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:21.4943691Z SingleProcess AUTOTUNE benchmarking takes 0.2773 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:21.7906161Z Autotune Choices Stats: 2025-09-07T11:49:21.7907401Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1315", "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": 0.010239999741315842, "best_triton_pos": 0} 2025-09-07T11:49:21.8061531Z AUTOTUNE mm(196x768, 768x128) 2025-09-07T11:49:21.8061830Z strides: [768, 1], [1, 768] 2025-09-07T11:49:21.8062143Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:21.8062908Z triton_mm_1315 0.0102 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 2025-09-07T11:49:21.8063660Z mm 0.0123 ms 83.3% 2025-09-07T11:49:21.8064351Z triton_mm_1312 0.0123 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 2025-09-07T11:49:21.8065628Z triton_mm_1313 0.0123 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T11:49:21.8066804Z triton_mm_1314 0.0123 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 2025-09-07T11:49:21.8068272Z triton_mm_1319 0.0123 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 2025-09-07T11:49:21.8069455Z triton_mm_1318 0.0133 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 2025-09-07T11:49:21.8072827Z triton_mm_1322 0.0143 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:21.8074182Z triton_mm_1324 0.0154 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:21.8075375Z triton_mm_1321 0.0164 ms 62.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:21.8076417Z SingleProcess AUTOTUNE benchmarking takes 0.2757 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:22.1049717Z Autotune Choices Stats: 2025-09-07T11:49:22.1050943Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1340", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:22.1204936Z AUTOTUNE mm(196x800, 800x128) 2025-09-07T11:49:22.1205270Z strides: [800, 1], [1, 800] 2025-09-07T11:49:22.1205570Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:22.1206346Z triton_mm_1340 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:22.1207118Z mm 0.0123 ms 91.7% 2025-09-07T11:49:22.1208063Z triton_mm_1338 0.0123 ms 91.7% 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 2025-09-07T11:49:22.1209252Z triton_mm_1339 0.0123 ms 91.7% 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 2025-09-07T11:49:22.1210444Z triton_mm_1344 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:22.1211649Z triton_mm_1337 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 2025-09-07T11:49:22.1213107Z triton_mm_1343 0.0143 ms 78.6% 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 2025-09-07T11:49:22.1214318Z triton_mm_1347 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:22.1215511Z triton_mm_1349 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:22.1216703Z triton_mm_1346 0.0174 ms 64.7% 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 2025-09-07T11:49:22.1217736Z SingleProcess AUTOTUNE benchmarking takes 0.2767 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:22.4217685Z Autotune Choices Stats: 2025-09-07T11:49:22.4218939Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1365", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:22.4378610Z AUTOTUNE mm(196x832, 832x128) 2025-09-07T11:49:22.4378934Z strides: [832, 1], [1, 832] 2025-09-07T11:49:22.4379225Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:22.4380014Z triton_mm_1365 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:22.4380944Z mm 0.0123 ms 91.7% 2025-09-07T11:49:22.4381776Z triton_mm_1363 0.0123 ms 91.7% 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 2025-09-07T11:49:22.4382980Z triton_mm_1369 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:22.4384188Z triton_mm_1362 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 2025-09-07T11:49:22.4385430Z triton_mm_1364 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 2025-09-07T11:49:22.4386614Z triton_mm_1368 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:22.4387803Z triton_mm_1372 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:22.4388987Z triton_mm_1374 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:22.4390267Z triton_mm_1371 0.0174 ms 64.7% 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 2025-09-07T11:49:22.4391291Z SingleProcess AUTOTUNE benchmarking takes 0.2792 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:22.7373726Z Autotune Choices Stats: 2025-09-07T11:49:22.7374986Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1390", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:22.7535410Z AUTOTUNE mm(196x864, 864x128) 2025-09-07T11:49:22.7535704Z strides: [864, 1], [1, 864] 2025-09-07T11:49:22.7536020Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:22.7536809Z triton_mm_1390 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:22.7537570Z mm 0.0123 ms 91.7% 2025-09-07T11:49:22.7538274Z triton_mm_1394 0.0123 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:22.7539462Z triton_mm_1387 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 2025-09-07T11:49:22.7540661Z triton_mm_1388 0.0133 ms 84.6% 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 2025-09-07T11:49:22.7541843Z triton_mm_1389 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 2025-09-07T11:49:22.7543273Z triton_mm_1393 0.0143 ms 78.6% 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 2025-09-07T11:49:22.7544470Z triton_mm_1397 0.0164 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:22.7545860Z triton_mm_1396 0.0174 ms 64.7% 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 2025-09-07T11:49:22.7547163Z triton_mm_1399 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:22.7548183Z SingleProcess AUTOTUNE benchmarking takes 0.2784 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:23.0531409Z Autotune Choices Stats: 2025-09-07T11:49:23.0532624Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1415", "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": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:23.0693620Z AUTOTUNE mm(196x896, 896x128) 2025-09-07T11:49:23.0693937Z strides: [896, 1], [1, 896] 2025-09-07T11:49:23.0694260Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:23.0695057Z triton_mm_1415 0.0113 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 2025-09-07T11:49:23.0695821Z mm 0.0123 ms 91.7% 2025-09-07T11:49:23.0696505Z triton_mm_1419 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 2025-09-07T11:49:23.0697907Z triton_mm_1412 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T11:49:23.0699098Z triton_mm_1413 0.0133 ms 84.6% 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 2025-09-07T11:49:23.0700281Z triton_mm_1414 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 2025-09-07T11:49:23.0701462Z triton_mm_1418 0.0143 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:23.0702641Z triton_mm_1422 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:23.0703818Z triton_mm_1424 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:23.0705003Z triton_mm_1421 0.0184 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:23.0706111Z SingleProcess AUTOTUNE benchmarking takes 0.2780 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:23.3900625Z Autotune Choices Stats: 2025-09-07T11:49:23.3901821Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1440", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:23.4057201Z AUTOTUNE mm(196x928, 928x128) 2025-09-07T11:49:23.4057495Z strides: [928, 1], [1, 928] 2025-09-07T11:49:23.4057814Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:23.4058601Z triton_mm_1440 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:23.4059366Z mm 0.0133 ms 84.6% 2025-09-07T11:49:23.4060047Z triton_mm_1438 0.0133 ms 84.6% 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 2025-09-07T11:49:23.4061483Z triton_mm_1439 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 2025-09-07T11:49:23.4062676Z triton_mm_1444 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:23.4063885Z triton_mm_1437 0.0143 ms 78.6% 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 2025-09-07T11:49:23.4065145Z triton_mm_1443 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:23.4066348Z triton_mm_1447 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:23.4067551Z triton_mm_1449 0.0174 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:23.4068732Z triton_mm_1446 0.0184 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:23.4069866Z SingleProcess AUTOTUNE benchmarking takes 0.2992 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:23.7079225Z Autotune Choices Stats: 2025-09-07T11:49:23.7080437Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1465", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:23.7236594Z AUTOTUNE mm(196x960, 960x128) 2025-09-07T11:49:23.7236900Z strides: [960, 1], [1, 960] 2025-09-07T11:49:23.7237191Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:23.7237979Z triton_mm_1465 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:23.7238748Z mm 0.0133 ms 84.6% 2025-09-07T11:49:23.7239442Z triton_mm_1464 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 2025-09-07T11:49:23.7240632Z triton_mm_1469 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:23.7241823Z triton_mm_1462 0.0143 ms 78.6% 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 2025-09-07T11:49:23.7242997Z triton_mm_1463 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 2025-09-07T11:49:23.7244381Z triton_mm_1468 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:23.7245578Z triton_mm_1472 0.0164 ms 68.8% 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 2025-09-07T11:49:23.7246760Z triton_mm_1471 0.0184 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:23.7248028Z triton_mm_1474 0.0195 ms 57.9% 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 2025-09-07T11:49:23.7249134Z SingleProcess AUTOTUNE benchmarking takes 0.2803 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:24.0265048Z Autotune Choices Stats: 2025-09-07T11:49:24.0266340Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_1490", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T11:49:24.0422495Z AUTOTUNE mm(196x992, 992x128) 2025-09-07T11:49:24.0422821Z strides: [992, 1], [1, 992] 2025-09-07T11:49:24.0423127Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T11:49:24.0423912Z triton_mm_1490 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:24.0424698Z mm 0.0133 ms 84.6% 2025-09-07T11:49:24.0425425Z triton_mm_1489 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 2025-09-07T11:49:24.0426616Z triton_mm_1494 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T11:49:24.0428056Z triton_mm_1487 0.0143 ms 78.6% 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 2025-09-07T11:49:24.0429261Z triton_mm_1488 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 2025-09-07T11:49:24.0430444Z triton_mm_1493 0.0154 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T11:49:24.0431631Z triton_mm_1496 0.0184 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T11:49:24.0432817Z triton_mm_1497 0.0184 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T11:49:24.0433997Z triton_mm_1499 0.0195 ms 57.9% 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 2025-09-07T11:49:24.0435023Z SingleProcess AUTOTUNE benchmarking takes 0.2814 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T11:49:42.4068913Z pass 2025-09-07T11:49:47.1514565Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:49:47.1515980Z import pynvml # type: ignore[import] 2025-09-07T11:49:49.7889769Z 2025-09-07T11:49:50.0613755Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:49:50.0614305Z what(): std::bad_alloc 2025-09-07T11:49:50.2602411Z Run failed with return code: -6 2025-09-07T11:49:50.2602818Z Output: None 2025-09-07T11:49:50.2603047Z Error: None 2025-09-07T11:49:50.8189896Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:49:50.8196135Z import pynvml # type: ignore[import] 2025-09-07T11:49:53.4781544Z 2025-09-07T11:49:53.7438527Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:49:53.7439312Z what(): std::bad_alloc 2025-09-07T11:49:53.9791618Z Run failed with return code: -6 2025-09-07T11:49:53.9791968Z Output: None 2025-09-07T11:49:53.9792206Z Error: None 2025-09-07T11:49:54.5428408Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:49:54.5429827Z import pynvml # type: ignore[import] 2025-09-07T11:49:57.1791026Z 2025-09-07T11:49:57.4435623Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_alloc' 2025-09-07T11:49:57.4436193Z what(): std::bad_alloc 2025-09-07T11:49:57.6479974Z Run failed with return code: -6 2025-09-07T11:49:57.6480324Z Output: None 2025-09-07T11:49:57.6480586Z Error: None 2025-09-07T11:49:57.6510528Z accuracy pass_rate=84.62% 2025-09-07T11:49:57.6516924Z calls_captured gmean=0.00x mean=133.846x 2025-09-07T11:49:57.6521511Z unique_graphs gmean=0.00x mean=1.385x 2025-09-07T11:49:57.6525624Z graph_breaks gmean=0.00x mean=0.692x 2025-09-07T11:49:57.6529789Z unique_graph_breaks gmean=0.00x mean=0.154x 2025-09-07T11:49:57.6534226Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T11:49:57.6538778Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T11:49:57.6542545Z cudagraph_skips gmean=0.00x mean=0.538x 2025-09-07T11:49:57.6543805Z compilation_latency mean=13.827 seconds 2025-09-07T11:49:58.6977224Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs_low_precision-true* ]] 2025-09-07T11:49:58.6978786Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T11:49:58.6980302Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --quant --backend inductor --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv 2025-09-07T11:49:59.2592838Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:49:59.2594267Z import pynvml # type: ignore[import] 2025-09-07T11:50:01.8363059Z usage: torchbench.py 2025-09-07T11:50:01.8363384Z [-h] 2025-09-07T11:50:01.8363608Z [--filter FILTER] 2025-09-07T11:50:01.8363866Z [--exclude EXCLUDE] 2025-09-07T11:50:01.8364185Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T11:50:01.8364586Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T11:50:01.8364992Z [--partition-id PARTITION_ID] 2025-09-07T11:50:01.8365291Z [--devices DEVICES] 2025-09-07T11:50:01.8365572Z [--device-index DEVICE_INDEX] 2025-09-07T11:50:01.8366199Z [--repeat REPEAT] 2025-09-07T11:50:01.8366507Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T11:50:01.8366849Z [--randomize-input] 2025-09-07T11:50:01.8367124Z [--threads THREADS] 2025-09-07T11:50:01.8367394Z [--nopython] 2025-09-07T11:50:01.8367629Z [--no-skip] 2025-09-07T11:50:01.8367862Z [--prims-nvfuser] 2025-09-07T11:50:01.8368132Z [--dump-raw-metrics] 2025-09-07T11:50:01.8368417Z [--log-operator-inputs] 2025-09-07T11:50:01.8368706Z [--channels-last] 2025-09-07T11:50:01.8368965Z [--batch-size BATCH_SIZE] 2025-09-07T11:50:01.8369262Z [--iterations ITERATIONS] 2025-09-07T11:50:01.8369672Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T11:50:01.8370079Z [--cosine] 2025-09-07T11:50:01.8370304Z [--freezing] 2025-09-07T11:50:01.8370567Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T11:50:01.8370882Z [--ci] 2025-09-07T11:50:01.8371110Z [--dashboard] 2025-09-07T11:50:01.8371356Z [--skip-fp64-check] 2025-09-07T11:50:01.8371619Z [--fast] 2025-09-07T11:50:01.8371858Z [--only ONLY] 2025-09-07T11:50:01.8372105Z [--multiprocess] 2025-09-07T11:50:01.8372343Z [--ddp] 2025-09-07T11:50:01.8372568Z [--fsdp] 2025-09-07T11:50:01.8373110Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T11:50:01.8373532Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T11:50:01.8373907Z [--dynamic-shapes] 2025-09-07T11:50:01.8374189Z [--propagate-real-tensors] 2025-09-07T11:50:01.8374498Z [--dynamic-batch-only] 2025-09-07T11:50:01.8374787Z [--specialize-int] 2025-09-07T11:50:01.8375048Z [--use-eval-mode] 2025-09-07T11:50:01.8375324Z [--skip-accuracy-check] 2025-09-07T11:50:01.8375634Z [--generate-aot-autograd-stats] 2025-09-07T11:50:01.8375962Z [--inductor-settings] 2025-09-07T11:50:01.8376233Z [--suppress-errors] 2025-09-07T11:50:01.8376506Z [--output OUTPUT] 2025-09-07T11:50:01.8376798Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T11:50:01.8377118Z [--disable-output] 2025-09-07T11:50:01.8377388Z [--baseline BASELINE] 2025-09-07T11:50:01.8377669Z [--part PART] 2025-09-07T11:50:01.8378054Z [--export-profiler-trace] 2025-09-07T11:50:01.8378389Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T11:50:01.8378748Z [--profile-details] 2025-09-07T11:50:01.8379033Z [--export-perfdoctor] 2025-09-07T11:50:01.8379326Z [--diff-branch DIFF_BRANCH] 2025-09-07T11:50:01.8379603Z [--tag TAG] 2025-09-07T11:50:01.8379836Z [--explain] 2025-09-07T11:50:01.8380067Z [--stats] 2025-09-07T11:50:01.8380310Z [--use-warm-peak-memory] 2025-09-07T11:50:01.8380588Z [--print-memory] 2025-09-07T11:50:01.8380862Z [--print-compilation-time] 2025-09-07T11:50:01.8381183Z [--print-dataframe-summary] 2025-09-07T11:50:01.8381495Z [--disable-cudagraphs] 2025-09-07T11:50:01.8381787Z [--disable-split-reductions] 2025-09-07T11:50:01.8382122Z [--disable-persistent-reductions] 2025-09-07T11:50:01.8382470Z [--disable-divisible-by-16] 2025-09-07T11:50:01.8382833Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T11:50:01.8383242Z [--print-graph-breaks] 2025-09-07T11:50:01.8383563Z [--log-graph-breaks] 2025-09-07T11:50:01.8383824Z [--trace-on-xla] 2025-09-07T11:50:01.8384099Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T11:50:01.8384416Z [--collect-outputs] 2025-09-07T11:50:01.8384721Z [--enable-activation-checkpointing] 2025-09-07T11:50:01.8385126Z [--timing] 2025-09-07T11:50:01.8385373Z [--progress] 2025-09-07T11:50:01.8385616Z [--timeout TIMEOUT] 2025-09-07T11:50:01.8385977Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T11:50:01.8386383Z [--no-translation-validation] 2025-09-07T11:50:01.8386686Z [--minify] 2025-09-07T11:50:01.8386928Z [--compiled-autograd] 2025-09-07T11:50:01.8387333Z [--profile_dynamo_cache_lookup] 2025-09-07T11:50:01.8387639Z [--snapshot-memory] 2025-09-07T11:50:01.8387910Z [--retain-output] 2025-09-07T11:50:01.8388183Z [--caching-precompile] 2025-09-07T11:50:01.8388525Z [--cold-start-latency | --warm-start-latency] 2025-09-07T11:50:01.8388861Z [--nnc] 2025-09-07T11:50:01.8389122Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T11:50:01.8389485Z [--amp-dtype {bfloat16,float16}] 2025-09-07T11:50:01.8389805Z [--verbose | --quiet] 2025-09-07T11:50:01.8393386Z [--coverage | --overhead | --speedup-dynamo-ts | --speedup-fx2trt | --speedup-fx2trt-fp16 | --print-fx | --print-aten-ops | --inductor | --quantization {int8dynamic,int8weightonly,int4weightonly,autoquant,noquant} | --export | --export-aot-inductor | --export-nativert | --torchscript-jit-trace | --xla | --backend {aot_eager,aot_eager_decomp_partition,aot_eager_decomp_partition_crossref,aot_eager_decomp_partition_with_mode,aot_eager_default_partitioner,aot_ts,cudagraphs,dynamo_accuracy_minifier_backend,dynamo_minifier_backend,eager,eager_debug,eager_noexcept,inductor,non_leaf_compile_error_TESTING_ONLY,openxla,openxla_eval,pre_dispatch_eager,relu_accuracy_error_TESTING_ONLY,relu_compile_error_TESTING_ONLY,relu_runtime_error_TESTING_ONLY,ts,tvm} | --nothing | --log-conv-args | --recompile-profiler | --find-batch-sizes] 2025-09-07T11:50:01.8397033Z (--accuracy | --performance | --tolerance) 2025-09-07T11:50:01.8397402Z (--training | --inference) 2025-09-07T11:50:01.8397809Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T11:50:02.5336893Z + true 2025-09-07T11:50:02.5338210Z + 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 2025-09-07T11:50:02.5354793Z + for target in "${targets[@]}" 2025-09-07T11:50:02.5355152Z + target_flag=('--performance') 2025-09-07T11:50:02.5355445Z + local target_flag 2025-09-07T11:50:02.5355715Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T11:50:02.5356308Z + target_flag+=(--cold-start-latency) 2025-09-07T11:50:02.5357705Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing-true* ]] 2025-09-07T11:50:02.5360161Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *default-true* ]] 2025-09-07T11:50:02.5362784Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 6 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv 2025-09-07T11:50:03.0966072Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:50:03.0967484Z import pynvml # type: ignore[import] 2025-09-07T11:50:06.8522987Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:50:06.8524423Z import pynvml # type: ignore[import] 2025-09-07T11:50:09.7005753Z 2025-09-07T11:50:09.8993250Z loading model: 0it [00:00, ?it/s][rank0]:W0907 11:50:09.898000 306735 site-packages/torch/fx/_symbolic_trace.py:52] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-09-07T11:50:10.8041514Z 2025-09-07T11:50:10.8041898Z loading model: 0it [00:01, ?it/s] 2025-09-07T11:50:10.8052566Z cuda eval torchrec_dlrm 2025-09-07T11:50:10.8053282Z Traceback (most recent call last): 2025-09-07T11:50:10.8053862Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T11:50:10.8054729Z self.model_iter_fn(model, example_inputs) 2025-09-07T11:50:10.8055426Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T11:50:10.8055999Z return mod(*inputs) 2025-09-07T11:50:10.8056639Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:50:10.8057328Z return self._call_impl(*args, **kwargs) 2025-09-07T11:50:10.8057969Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:50:10.8058611Z return forward_call(*args, **kwargs) 2025-09-07T11:50:10.8059210Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T11:50:10.8059898Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T11:50:10.8060657Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:50:10.8061349Z return self._call_impl(*args, **kwargs) 2025-09-07T11:50:10.8061986Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:50:10.8062625Z return forward_call(*args, **kwargs) 2025-09-07T11:50:10.8063208Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T11:50:10.8063820Z concatenated_dense = self.inter_arch( 2025-09-07T11:50:10.8064601Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:50:10.8065384Z return self._call_impl(*args, **kwargs) 2025-09-07T11:50:10.8066019Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:50:10.8066642Z return forward_call(*args, **kwargs) 2025-09-07T11:50:10.8067232Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T11:50:10.8067922Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T11:50:10.8068662Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T11:50:10.8069346Z return self._call_impl(*args, **kwargs) 2025-09-07T11:50:10.8069970Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T11:50:10.8070598Z return forward_call(*args, **kwargs) 2025-09-07T11:50:10.8071215Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T11:50:10.8071917Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T11:50:10.8072537Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T11:50:10.8072953Z 2025-09-07T11:50:10.8073171Z The above exception was the direct cause of the following exception: 2025-09-07T11:50:10.8073516Z 2025-09-07T11:50:10.8073626Z Traceback (most recent call last): 2025-09-07T11:50:10.8074115Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T11:50:10.8074621Z ) = runner.load_model( 2025-09-07T11:50:10.8075118Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T11:50:10.8075814Z self.validate_model(model, example_inputs) 2025-09-07T11:50:10.8076397Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T11:50:10.8076994Z raise RuntimeError("Eager run failed") from e 2025-09-07T11:50:10.8077357Z RuntimeError: Eager run failed 2025-09-07T11:50:10.8077546Z 2025-09-07T11:50:10.8077636Z eager_fail_to_run 2025-09-07T11:50:11.4293874Z [rank0]:[W907 11:50:11.715693808 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T11:50:12.4874494Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T11:50:12.4876019Z import pynvml # type: ignore[import] 2025-09-07T11:50:15.1974561Z 2025-09-07T11:50:17.7777577Z loading model: 0it [00:00, ?it/s] 2025-09-07T11:50:17.7777992Z loading model: 0it [00:02, ?it/s] 2025-09-07T11:50:17.7830365Z cuda eval BERT_pytorch 2025-09-07T11:50:34.9402948Z 2025-09-07T11:50:35.0575492Z running benchmark: 0% 0/30 [00:00 2025-09-07T12:02:34.7782750Z tx, [v.realize() for v in args], kwargs 2025-09-07T12:02:34.7783419Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py", line 967, in 2025-09-07T12:02:34.7784095Z tx, [v.realize() for v in args], kwargs 2025-09-07T12:02:34.7784726Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 72, in realize 2025-09-07T12:02:34.7785483Z self._cache.realize() 2025-09-07T12:02:34.7786120Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 33, in realize 2025-09-07T12:02:34.7786838Z self.vt = builder.VariableBuilder(tx, self.source)(self.value) 2025-09-07T12:02:34.7787572Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 445, in __call__ 2025-09-07T12:02:34.7788202Z vt = self._wrap(value) 2025-09-07T12:02:34.7788787Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 670, in _wrap 2025-09-07T12:02:34.7789431Z return type_dispatch(self, value) 2025-09-07T12:02:34.7790097Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 2116, in wrap_tensor 2025-09-07T12:02:34.7790802Z example_value = wrap_to_fake_tensor_and_record( 2025-09-07T12:02:34.7791574Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3500, in wrap_to_fake_tensor_and_record 2025-09-07T12:02:34.7792334Z fake_e = wrap_fake_exception( 2025-09-07T12:02:34.7792964Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 2864, in wrap_fake_exception 2025-09-07T12:02:34.7793598Z return fn() 2025-09-07T12:02:34.7794149Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3501, in 2025-09-07T12:02:34.7794808Z lambda: tx.fake_mode.from_tensor( 2025-09-07T12:02:34.7795514Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2989, in from_tensor 2025-09-07T12:02:34.7796223Z return self.fake_tensor_converter.from_real_tensor( 2025-09-07T12:02:34.7796948Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 404, in from_real_tensor 2025-09-07T12:02:34.7797609Z out = self.meta_converter( 2025-09-07T12:02:34.7798217Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 1898, in __call__ 2025-09-07T12:02:34.7798915Z t_desc = self.describer.describe_tensor(t, trace=trace) 2025-09-07T12:02:34.7799644Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 310, in describe_tensor 2025-09-07T12:02:34.7800417Z storage = self.describe_storage(t.untyped_storage(), trace=trace) 2025-09-07T12:02:34.7801932Z torch._dynamo.exc.InternalTorchDynamoError: RuntimeError: Error: accessing tensor output of CUDAGraphs that has been overwritten by a subsequent run. Stack trace: File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T12:02:34.7803455Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T12:02:34.7804164Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1077, in buffered_future_mask 2025-09-07T12:02:34.7805401Z self._future_mask = self._future_mask.to(tensor). To prevent overwriting, clone the tensor outside of torch.compile() or call torch.compiler.cudagraph_mark_step_begin() before each model invocation. 2025-09-07T12:02:34.7806238Z 2025-09-07T12:02:34.7806345Z from user code: 2025-09-07T12:02:34.7806983Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T12:02:34.7807836Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T12:02:34.7808541Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1060, in buffered_future_mask 2025-09-07T12:02:34.7809153Z self._future_mask.size(0) == 0 2025-09-07T12:02:34.7809354Z 2025-09-07T12:02:34.7809995Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T12:02:34.7810776Z 2025-09-07T12:02:34.7810876Z warmup_failed 2025-09-07T12:02:39.1518602Z Run failed with return code: 255 2025-09-07T12:02:39.1519452Z Output: None 2025-09-07T12:02:39.1519697Z Error: None 2025-09-07T12:02:39.7286801Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:02:39.7288261Z import pynvml # type: ignore[import] 2025-09-07T12:02:42.4296602Z 2025-09-07T12:02:43.0496179Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:02:43.0496577Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:02:43.0500839Z cuda eval dcgan 2025-09-07T12:02:49.3161123Z 2025-09-07T12:02:49.4190462Z running benchmark: 0% 0/30 [00:00 2025-09-07T12:09:31.4178174Z tx, [v.realize() for v in args], kwargs 2025-09-07T12:09:31.4178846Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py", line 967, in 2025-09-07T12:09:31.4179516Z tx, [v.realize() for v in args], kwargs 2025-09-07T12:09:31.4180210Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 72, in realize 2025-09-07T12:09:31.4180839Z self._cache.realize() 2025-09-07T12:09:31.4181424Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 33, in realize 2025-09-07T12:09:31.4182148Z self.vt = builder.VariableBuilder(tx, self.source)(self.value) 2025-09-07T12:09:31.4182898Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 445, in __call__ 2025-09-07T12:09:31.4183526Z vt = self._wrap(value) 2025-09-07T12:09:31.4184110Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 670, in _wrap 2025-09-07T12:09:31.4184756Z return type_dispatch(self, value) 2025-09-07T12:09:31.4185487Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 2116, in wrap_tensor 2025-09-07T12:09:31.4186203Z example_value = wrap_to_fake_tensor_and_record( 2025-09-07T12:09:31.4186978Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3500, in wrap_to_fake_tensor_and_record 2025-09-07T12:09:31.4187736Z fake_e = wrap_fake_exception( 2025-09-07T12:09:31.4188369Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 2864, in wrap_fake_exception 2025-09-07T12:09:31.4189005Z return fn() 2025-09-07T12:09:31.4189562Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3501, in 2025-09-07T12:09:31.4190219Z lambda: tx.fake_mode.from_tensor( 2025-09-07T12:09:31.4190864Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2989, in from_tensor 2025-09-07T12:09:31.4191644Z return self.fake_tensor_converter.from_real_tensor( 2025-09-07T12:09:31.4192372Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 404, in from_real_tensor 2025-09-07T12:09:31.4193038Z out = self.meta_converter( 2025-09-07T12:09:31.4193647Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 1898, in __call__ 2025-09-07T12:09:31.4194350Z t_desc = self.describer.describe_tensor(t, trace=trace) 2025-09-07T12:09:31.4195143Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 310, in describe_tensor 2025-09-07T12:09:31.4195968Z storage = self.describe_storage(t.untyped_storage(), trace=trace) 2025-09-07T12:09:31.4197463Z torch._dynamo.exc.InternalTorchDynamoError: RuntimeError: Error: accessing tensor output of CUDAGraphs that has been overwritten by a subsequent run. Stack trace: File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T12:09:31.4198977Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T12:09:31.4199681Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1077, in buffered_future_mask 2025-09-07T12:09:31.4200911Z self._future_mask = self._future_mask.to(tensor). To prevent overwriting, clone the tensor outside of torch.compile() or call torch.compiler.cudagraph_mark_step_begin() before each model invocation. 2025-09-07T12:09:31.4201753Z 2025-09-07T12:09:31.4201856Z from user code: 2025-09-07T12:09:31.4202480Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T12:09:31.4203285Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T12:09:31.4203984Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1060, in buffered_future_mask 2025-09-07T12:09:31.4204597Z self._future_mask.size(0) == 0 2025-09-07T12:09:31.4204801Z 2025-09-07T12:09:31.4205491Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T12:09:31.4206223Z 2025-09-07T12:09:31.4206325Z warmup_failed 2025-09-07T12:09:35.4034773Z Run failed with return code: 255 2025-09-07T12:09:35.4035163Z Output: None 2025-09-07T12:09:35.4035394Z Error: None 2025-09-07T12:09:35.9678957Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:09:35.9680377Z import pynvml # type: ignore[import] 2025-09-07T12:09:38.6669052Z 2025-09-07T12:09:39.2773179Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:09:39.2773534Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:09:39.2779472Z cuda eval dcgan 2025-09-07T12:09:45.6123169Z 2025-09-07T12:09:45.7143257Z running benchmark: 0% 0/30 [00:00 2025-09-07T13:01:23.3641726Z tx, [v.realize() for v in args], kwargs 2025-09-07T13:01:23.3642392Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py", line 967, in 2025-09-07T13:01:23.3643068Z tx, [v.realize() for v in args], kwargs 2025-09-07T13:01:23.3643696Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 72, in realize 2025-09-07T13:01:23.3644317Z self._cache.realize() 2025-09-07T13:01:23.3644879Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 33, in realize 2025-09-07T13:01:23.3645596Z self.vt = builder.VariableBuilder(tx, self.source)(self.value) 2025-09-07T13:01:23.3646399Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 445, in __call__ 2025-09-07T13:01:23.3647041Z vt = self._wrap(value) 2025-09-07T13:01:23.3647636Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 670, in _wrap 2025-09-07T13:01:23.3648268Z return type_dispatch(self, value) 2025-09-07T13:01:23.3648932Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 2116, in wrap_tensor 2025-09-07T13:01:23.3649648Z example_value = wrap_to_fake_tensor_and_record( 2025-09-07T13:01:23.3650498Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3500, in wrap_to_fake_tensor_and_record 2025-09-07T13:01:23.3651246Z fake_e = wrap_fake_exception( 2025-09-07T13:01:23.3651874Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 2864, in wrap_fake_exception 2025-09-07T13:01:23.3652506Z return fn() 2025-09-07T13:01:23.3653224Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3501, in 2025-09-07T13:01:23.3653904Z lambda: tx.fake_mode.from_tensor( 2025-09-07T13:01:23.3654548Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2989, in from_tensor 2025-09-07T13:01:23.3655266Z return self.fake_tensor_converter.from_real_tensor( 2025-09-07T13:01:23.3655996Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 404, in from_real_tensor 2025-09-07T13:01:23.3656674Z out = self.meta_converter( 2025-09-07T13:01:23.3657271Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 1898, in __call__ 2025-09-07T13:01:23.3657975Z t_desc = self.describer.describe_tensor(t, trace=trace) 2025-09-07T13:01:23.3658706Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 310, in describe_tensor 2025-09-07T13:01:23.3659485Z storage = self.describe_storage(t.untyped_storage(), trace=trace) 2025-09-07T13:01:23.3661082Z torch._dynamo.exc.InternalTorchDynamoError: RuntimeError: Error: accessing tensor output of CUDAGraphs that has been overwritten by a subsequent run. Stack trace: File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T13:01:23.3662616Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T13:01:23.3663309Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1077, in buffered_future_mask 2025-09-07T13:01:23.3664543Z self._future_mask = self._future_mask.to(tensor). To prevent overwriting, clone the tensor outside of torch.compile() or call torch.compiler.cudagraph_mark_step_begin() before each model invocation. 2025-09-07T13:01:23.3665539Z 2025-09-07T13:01:23.3665633Z from user code: 2025-09-07T13:01:23.3666271Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T13:01:23.3667091Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T13:01:23.3667779Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1060, in buffered_future_mask 2025-09-07T13:01:23.3668395Z self._future_mask.size(0) == 0 2025-09-07T13:01:23.3668606Z 2025-09-07T13:01:23.3669224Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T13:01:23.3669971Z 2025-09-07T13:01:23.3670063Z warmup_failed 2025-09-07T13:01:29.9565173Z Run failed with return code: 255 2025-09-07T13:01:29.9565571Z Output: None 2025-09-07T13:01:29.9565800Z Error: None 2025-09-07T13:01:30.5331362Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:01:30.5340303Z import pynvml # type: ignore[import] 2025-09-07T13:01:33.2463984Z 2025-09-07T13:01:33.8678962Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:01:33.8679348Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:01:33.8684072Z cuda eval dcgan 2025-09-07T13:01:42.8962734Z Autotune Choices Stats: 2025-09-07T13:01:42.8964766Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.14643199741840363, "best_triton_pos": 1, "best_triton_time": 0.20684799551963806, "best_triton_kernel": "triton_convolution2d_31", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T13:01:42.9053968Z AUTOTUNE convolution(1024x512x4x4, 1x512x4x4) 2025-09-07T13:01:42.9054369Z strides: [8192, 1, 2048, 512], [8192, 1, 2048, 512] 2025-09-07T13:01:42.9054741Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:01:42.9055076Z convolution 0.1464 ms 100.0% 2025-09-07T13:01:42.9055953Z triton_convolution2d_31 0.2068 ms 70.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:01:42.9057409Z triton_convolution2d_30 0.2345 ms 62.4% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:01:42.9058885Z triton_convolution2d_32 0.2765 ms 53.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:01:42.9060520Z triton_convolution2d_27 0.3318 ms 44.1% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:01:42.9061996Z triton_convolution2d_28 0.4628 ms 31.6% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:01:42.9063480Z triton_convolution2d_29 0.8520 ms 17.2% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=4, KERNEL_W=4, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:01:42.9064646Z SingleProcess AUTOTUNE benchmarking takes 0.2592 seconds and 0.5350 seconds precompiling for 7 choices 2025-09-07T13:01:43.4140883Z Autotune Choices Stats: 2025-09-07T13:01:43.4142258Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_3", "best_kernel_desc": "ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, 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", "best_time": 0.5283839702606201, "best_triton_pos": 0} 2025-09-07T13:01:43.4231091Z AUTOTUNE convolution(1024x3x64x64, 64x3x4x4) 2025-09-07T13:01:43.4231457Z strides: [12288, 1, 192, 3], [48, 1, 12, 3] 2025-09-07T13:01:43.4231803Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:01:43.4232728Z triton_convolution2d_3 0.5284 ms 100.0% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, 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 2025-09-07T13:01:43.4234190Z triton_convolution2d_0 0.5499 ms 96.1% ALLOW_TF32=True, BLOCK_K=16, 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 2025-09-07T13:01:43.4241795Z triton_convolution2d_4 0.5663 ms 93.3% ALLOW_TF32=True, BLOCK_K=16, 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=8 2025-09-07T13:01:43.4243283Z triton_convolution2d_5 0.6267 ms 84.3% ALLOW_TF32=True, 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=8 2025-09-07T13:01:43.4244182Z convolution 0.7434 ms 71.1% 2025-09-07T13:01:43.4245214Z triton_convolution2d_2 0.8100 ms 65.2% ALLOW_TF32=True, 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 2025-09-07T13:01:43.4246692Z triton_convolution2d_1 0.8602 ms 61.4% ALLOW_TF32=True, 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 2025-09-07T13:01:43.4247858Z SingleProcess AUTOTUNE benchmarking takes 0.2561 seconds and 0.0004 seconds precompiling for 7 choices 2025-09-07T13:01:43.7124805Z Autotune Choices Stats: 2025-09-07T13:01:43.7126418Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.3051519989967346, "best_triton_pos": 1, "best_triton_time": 0.4997119903564453, "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=4, KERNEL_W=4, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T13:01:43.7213519Z AUTOTUNE convolution(1024x64x32x32, 128x64x4x4) 2025-09-07T13:01:43.7213918Z strides: [65536, 1, 2048, 64], [1024, 1, 256, 64] 2025-09-07T13:01:43.7214285Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:01:43.7214598Z convolution 0.3052 ms 100.0% 2025-09-07T13:01:43.7215476Z triton_convolution2d_9 0.4997 ms 61.1% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7217125Z triton_convolution2d_10 0.5745 ms 53.1% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7218592Z triton_convolution2d_11 0.6103 ms 50.0% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7220064Z triton_convolution2d_12 0.6113 ms 49.9% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7221607Z triton_convolution2d_7 0.7557 ms 40.4% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7223070Z triton_convolution2d_6 0.7793 ms 39.2% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7224513Z triton_convolution2d_8 2.6204 ms 11.6% ALLOW_TF32=True, 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 2025-09-07T13:01:43.7225761Z SingleProcess AUTOTUNE benchmarking takes 0.2973 seconds and 0.0006 seconds precompiling for 8 choices 2025-09-07T13:01:44.0306177Z Autotune Choices Stats: 2025-09-07T13:01:44.0307870Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.3020800054073334, "best_triton_pos": 1, "best_triton_time": 0.506879985332489, "best_triton_kernel": "triton_convolution2d_16", "best_triton_kernel_desc": "ALLOW_TF32=True, 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"} 2025-09-07T13:01:44.0397932Z AUTOTUNE convolution(1024x128x16x16, 256x128x4x4) 2025-09-07T13:01:44.0398328Z strides: [32768, 1, 2048, 128], [2048, 1, 512, 128] 2025-09-07T13:01:44.0398695Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:01:44.0399020Z convolution 0.3021 ms 100.0% 2025-09-07T13:01:44.0400049Z triton_convolution2d_16 0.5069 ms 59.6% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0401545Z triton_convolution2d_18 0.5253 ms 57.5% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0403021Z triton_convolution2d_17 0.5908 ms 51.1% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0404472Z triton_convolution2d_19 0.6308 ms 47.9% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0405943Z triton_convolution2d_13 0.7148 ms 42.3% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0407408Z triton_convolution2d_14 0.7444 ms 40.6% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0408880Z triton_convolution2d_15 2.3603 ms 12.8% ALLOW_TF32=True, 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 2025-09-07T13:01:44.0410130Z SingleProcess AUTOTUNE benchmarking takes 0.3175 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:01:44.3432800Z Autotune Choices Stats: 2025-09-07T13:01:44.3434464Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.2805759906768799, "best_triton_pos": 1, "best_triton_time": 0.5304319858551025, "best_triton_kernel": "triton_convolution2d_23", "best_triton_kernel_desc": "ALLOW_TF32=True, 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"} 2025-09-07T13:01:44.3520702Z AUTOTUNE convolution(1024x256x8x8, 512x256x4x4) 2025-09-07T13:01:44.3521129Z strides: [16384, 1, 2048, 256], [4096, 1, 1024, 256] 2025-09-07T13:01:44.3521525Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:01:44.3521857Z convolution 0.2806 ms 100.0% 2025-09-07T13:01:44.3522762Z triton_convolution2d_23 0.5304 ms 52.9% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3524252Z triton_convolution2d_24 0.5632 ms 49.8% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3525717Z triton_convolution2d_26 0.5816 ms 48.2% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3527177Z triton_convolution2d_25 0.5888 ms 47.7% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3528886Z triton_convolution2d_21 0.7311 ms 38.4% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3530357Z triton_convolution2d_20 0.7905 ms 35.5% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3531923Z triton_convolution2d_22 1.9651 ms 14.3% ALLOW_TF32=True, 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 2025-09-07T13:01:44.3533342Z SingleProcess AUTOTUNE benchmarking takes 0.3114 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:01:45.7100578Z 2025-09-07T13:01:45.8141208Z running benchmark: 0% 0/30 [00:00> $GITHUB_ENV 2025-09-07T13:04:17.3534950Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-09-07T13:04:17.3547927Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:04:17.3548309Z env: 2025-09-07T13:04:17.3548533Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:04:17.3548876Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:04:17.3549350Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:04:17.3549936Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:04:17.3550448Z ##[endgroup] 2025-09-07T13:04:17.3580115Z + [[ -n '' ]] 2025-09-07T13:04:17.3580463Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T13:04:17.6693236Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T13:04:18.8343826Z Collecting boto3==1.35.33 2025-09-07T13:04:18.9135646Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-09-07T13:04:18.9525720Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 3.5 MB/s eta 0:00:00 2025-09-07T13:04:19.1159784Z Collecting psutil==7.0.0 2025-09-07T13:04:19.1284490Z 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) 2025-09-07T13:04:19.2431159Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 2.4 MB/s eta 0:00:00 2025-09-07T13:04:19.2644547Z Collecting pynvml==12.0.0 2025-09-07T13:04:19.2766346Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-09-07T13:04:19.3065755Z Collecting jmespath<2.0.0,>=0.7.1 2025-09-07T13:04:19.3190175Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-09-07T13:04:20.1218655Z Collecting botocore<1.36.0,>=1.35.33 2025-09-07T13:04:20.1345740Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-09-07T13:04:21.0833642Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 13.9 MB/s eta 0:00:00 2025-09-07T13:04:21.1602816Z Collecting s3transfer<0.11.0,>=0.10.0 2025-09-07T13:04:21.1726784Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-09-07T13:04:21.1809890Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 11.2 MB/s eta 0:00:00 2025-09-07T13:04:21.2230576Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-09-07T13:04:21.2355819Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-09-07T13:04:21.2420005Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 8.0 MB/s eta 0:00:00 2025-09-07T13:04:21.2486920Z 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) 2025-09-07T13:04:21.2499818Z 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) 2025-09-07T13:04:21.5693173Z Installing collected packages: nvidia-ml-py, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-09-07T13:04:21.5694247Z Attempting uninstall: nvidia-ml-py 2025-09-07T13:04:21.5699981Z Found existing installation: nvidia-ml-py 11.525.84 2025-09-07T13:04:21.5737658Z Uninstalling nvidia-ml-py-11.525.84: 2025-09-07T13:04:21.5760975Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-09-07T13:04:21.6465791Z Attempting uninstall: psutil 2025-09-07T13:04:21.6473267Z Found existing installation: psutil 5.9.8 2025-09-07T13:04:21.6622197Z Uninstalling psutil-5.9.8: 2025-09-07T13:04:21.6630623Z Successfully uninstalled psutil-5.9.8 2025-09-07T13:04:22.3895207Z 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 2025-09-07T13:04:22.5003974Z + DEVICE_NAME= 2025-09-07T13:04:22.5004227Z + DEVICE_TYPE= 2025-09-07T13:04:22.5004463Z + command -v nvidia-smi 2025-09-07T13:04:22.5005264Z + python3 -mpip install torch==2.7.1 2025-09-07T13:04:22.5005580Z /usr/bin/nvidia-smi 2025-09-07T13:04:22.8104569Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T13:04:23.0636150Z Collecting torch==2.7.1 2025-09-07T13:04:23.1443186Z Downloading torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) 2025-09-07T13:05:24.2629171Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 946.0 kB/s eta 0:00:00 2025-09-07T13:05:26.4533169Z Collecting nvidia-nccl-cu12==2.26.2 2025-09-07T13:05:26.4668570Z Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) 2025-09-07T13:05:36.8304794Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 7.2 MB/s eta 0:00:00 2025-09-07T13:05:37.3765214Z Collecting filelock 2025-09-07T13:05:37.3899996Z Downloading filelock-3.19.1-py3-none-any.whl (15 kB) 2025-09-07T13:05:37.4330103Z Collecting sympy>=1.13.3 2025-09-07T13:05:37.4461877Z Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB) 2025-09-07T13:05:37.6819476Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 26.9 MB/s eta 0:00:00 2025-09-07T13:05:37.7335566Z Collecting nvidia-cusolver-cu12==11.7.1.2 2025-09-07T13:05:37.7470056Z Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) 2025-09-07T13:05:51.7991699Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 5.0 MB/s eta 0:00:00 2025-09-07T13:05:52.2216664Z Collecting nvidia-curand-cu12==10.3.7.77 2025-09-07T13:05:52.2356203Z Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) 2025-09-07T13:05:56.7702922Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 11.8 MB/s eta 0:00:00 2025-09-07T13:05:56.9406360Z Collecting nvidia-cufft-cu12==11.3.0.4 2025-09-07T13:05:56.9539087Z Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) 2025-09-07T13:06:15.9391930Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 4.5 MB/s eta 0:00:00 2025-09-07T13:06:16.4733948Z Collecting nvidia-nvtx-cu12==12.6.77 2025-09-07T13:06:16.4872742Z Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) 2025-09-07T13:06:16.4993722Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.3/89.3 KB 8.1 MB/s eta 0:00:00 2025-09-07T13:06:16.5288870Z Collecting nvidia-cusparse-cu12==12.5.4.2 2025-09-07T13:06:16.5424695Z Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) 2025-09-07T13:06:40.0764133Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 5.5 MB/s eta 0:00:00 2025-09-07T13:06:40.6694739Z Collecting fsspec 2025-09-07T13:06:40.6832174Z Downloading fsspec-2025.9.0-py3-none-any.whl (199 kB) 2025-09-07T13:06:40.7043790Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.3/199.3 KB 10.1 MB/s eta 0:00:00 2025-09-07T13:06:40.7267207Z Collecting nvidia-cufile-cu12==1.11.1.6 2025-09-07T13:06:40.7404019Z Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) 2025-09-07T13:06:40.8305753Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 12.9 MB/s eta 0:00:00 2025-09-07T13:06:40.8666876Z Collecting nvidia-cudnn-cu12==9.5.1.17 2025-09-07T13:06:40.8802647Z Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) 2025-09-07T13:07:29.1360174Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.8 MB/s eta 0:00:00 2025-09-07T13:07:30.5889545Z Collecting nvidia-cublas-cu12==12.6.4.1 2025-09-07T13:07:30.6038364Z Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) 2025-09-07T13:08:10.6124814Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 2.4 MB/s eta 0:00:00 2025-09-07T13:08:11.7249249Z Collecting nvidia-cuda-nvrtc-cu12==12.6.77 2025-09-07T13:08:11.7381817Z Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) 2025-09-07T13:08:13.3149850Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 12.9 MB/s eta 0:00:00 2025-09-07T13:08:13.3977551Z Collecting nvidia-cusparselt-cu12==0.6.3 2025-09-07T13:08:13.4109772Z Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) 2025-09-07T13:08:25.2444833Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 10.8 MB/s eta 0:00:00 2025-09-07T13:08:25.6379813Z Requirement already satisfied: typing-extensions>=4.10.0 in /home/david/.local/lib/python3.10/site-packages (from torch==2.7.1) (4.15.0) 2025-09-07T13:08:25.6660911Z Collecting nvidia-cuda-runtime-cu12==12.6.77 2025-09-07T13:08:25.6796158Z Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) 2025-09-07T13:08:25.7283008Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 KB 19.5 MB/s eta 0:00:00 2025-09-07T13:08:25.7575747Z Collecting nvidia-nvjitlink-cu12==12.6.85 2025-09-07T13:08:25.7709312Z Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) 2025-09-07T13:08:26.7401291Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 17.5 MB/s eta 0:00:00 2025-09-07T13:08:26.8212892Z Collecting triton==3.3.1 2025-09-07T13:08:26.8346571Z Downloading triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) 2025-09-07T13:08:37.0971945Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 7.1 MB/s eta 0:00:00 2025-09-07T13:08:37.5343585Z Collecting networkx 2025-09-07T13:08:37.5484442Z Downloading networkx-3.4.2-py3-none-any.whl (1.7 MB) 2025-09-07T13:08:37.7488055Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 8.6 MB/s eta 0:00:00 2025-09-07T13:08:37.7881070Z Collecting jinja2 2025-09-07T13:08:37.8017360Z Downloading jinja2-3.1.6-py3-none-any.whl (134 kB) 2025-09-07T13:08:37.8218644Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.9/134.9 KB 7.0 MB/s eta 0:00:00 2025-09-07T13:08:37.8494911Z Collecting nvidia-cuda-cupti-cu12==12.6.80 2025-09-07T13:08:37.8633523Z Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) 2025-09-07T13:08:39.1854644Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 6.7 MB/s eta 0:00:00 2025-09-07T13:08:39.2379107Z 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) 2025-09-07T13:08:39.2650825Z Collecting mpmath<1.4,>=1.1.0 2025-09-07T13:08:39.2784149Z Downloading mpmath-1.3.0-py3-none-any.whl (536 kB) 2025-09-07T13:08:39.3768036Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 5.5 MB/s eta 0:00:00 2025-09-07T13:08:39.5819550Z Collecting MarkupSafe>=2.0 2025-09-07T13:08:39.5957809Z Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) 2025-09-07T13:08:39.9778600Z 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 2025-09-07T13:08:44.5529971Z WARNING: The scripts proton and proton-viewer are installed in '/home/david/.local/bin' which is not on PATH. 2025-09-07T13:08:44.5530918Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:08:48.9291248Z WARNING: The script isympy is installed in '/home/david/.local/bin' which is not on PATH. 2025-09-07T13:08:48.9292095Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:09:24.9100901Z WARNING: The scripts torchfrtrace and torchrun are installed in '/home/david/.local/bin' which is not on PATH. 2025-09-07T13:09:24.9101859Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T13:09:25.2524605Z 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 2025-09-07T13:09:25.8206389Z + echo DEVICE_NAME= 2025-09-07T13:09:25.8206706Z + echo DEVICE_TYPE= 2025-09-07T13:09:25.8276231Z ##[group]Run set -eux 2025-09-07T13:09:25.8276518Z set -eux 2025-09-07T13:09:25.8276751Z  2025-09-07T13:09:25.8276985Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-09-07T13:09:25.8277353Z  echo "Missing github-token input" 2025-09-07T13:09:25.8277689Z  exit 1 2025-09-07T13:09:25.8277913Z fi 2025-09-07T13:09:25.8290752Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:25.8291150Z env: 2025-09-07T13:09:25.8291378Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:25.8291726Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:25.8292194Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:25.8292991Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:25.8293504Z DEVICE_NAME: 2025-09-07T13:09:25.8293743Z DEVICE_TYPE: 2025-09-07T13:09:25.8294213Z GITHUB_TOKEN: *** 2025-09-07T13:09:25.8294442Z ##[endgroup] 2025-09-07T13:09:25.8457457Z + [[ -z *** ]] 2025-09-07T13:09:25.8537195Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-09-07T13:09:25.8537649Z with: 2025-09-07T13:09:25.8538153Z github-token: *** 2025-09-07T13:09:25.8538514Z env: 2025-09-07T13:09:25.8538734Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:25.8539076Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:25.8539543Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:25.8540243Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:25.8540740Z DEVICE_NAME: 2025-09-07T13:09:25.8540972Z DEVICE_TYPE: 2025-09-07T13:09:25.8541201Z ##[endgroup] 2025-09-07T13:09:25.8656739Z ##[group]Run set -eux 2025-09-07T13:09:25.8657039Z set -eux 2025-09-07T13:09:25.8657272Z  2025-09-07T13:09:25.8657764Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T13:09:25.8670814Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:25.8671216Z env: 2025-09-07T13:09:25.8671443Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:25.8671788Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:25.8672266Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:25.8672862Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:25.8673378Z DEVICE_NAME: 2025-09-07T13:09:25.8673608Z DEVICE_TYPE: 2025-09-07T13:09:25.8674093Z GITHUB_TOKEN: *** 2025-09-07T13:09:25.8674323Z ##[endgroup] 2025-09-07T13:09:25.8788365Z + python3 /home/david/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525309334 i-01a21955dc3821a00-1004 2025-09-07T13:09:26.8530808Z setting job-id=49775768449 2025-09-07T13:09:26.8531395Z setting job-name=cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T13:09:26.8720582Z ##[group]Run set -eux 2025-09-07T13:09:26.8720891Z set -eux 2025-09-07T13:09:26.8721122Z  2025-09-07T13:09:26.8721330Z if [[ -n "" ]]; then 2025-09-07T13:09:26.8721623Z  source "" 2025-09-07T13:09:26.8721866Z fi 2025-09-07T13:09:26.8722084Z  2025-09-07T13:09:26.8722473Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-09-07T13:09:26.8723021Z  --schema-version "${SCHEMA_VERSION}" \ 2025-09-07T13:09:26.8723387Z  --repo "${REPO}" \ 2025-09-07T13:09:26.8723710Z  --head-branch "${HEAD_BRANCH}" \ 2025-09-07T13:09:26.8724046Z  --head-sha "${HEAD_SHA}" \ 2025-09-07T13:09:26.8724614Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-09-07T13:09:26.8724989Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-09-07T13:09:26.8725326Z  --job-id "${JOB_ID}" \ 2025-09-07T13:09:26.8725634Z  --job-name "${JOB_NAME}" 2025-09-07T13:09:26.8738948Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:26.8739346Z env: 2025-09-07T13:09:26.8739574Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:26.8739919Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:26.8740400Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:26.8740990Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:26.8741507Z DEVICE_NAME: 2025-09-07T13:09:26.8741741Z DEVICE_TYPE: 2025-09-07T13:09:26.8741971Z SCHEMA_VERSION: v3 2025-09-07T13:09:26.8742215Z REPO: pytorch/pytorch 2025-09-07T13:09:26.8742487Z HEAD_BRANCH: refs/heads/main 2025-09-07T13:09:26.8742831Z HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T13:09:26.8743187Z WORKFLOW_RUN_ID: 17525309334 2025-09-07T13:09:26.8743448Z RUN_ATTEMPT: 1 2025-09-07T13:09:26.8743687Z JOB_ID: 49775768449 2025-09-07T13:09:26.8744131Z JOB_NAME: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T13:09:26.8744636Z ##[endgroup] 2025-09-07T13:09:26.8843047Z + [[ -n '' ]] 2025-09-07T13:09:26.8845326Z + python3 /home/david/_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 49775768449 --job-name 'cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)' 2025-09-07T13:09:26.9242822Z ##[group]Run set -eux 2025-09-07T13:09:26.9243113Z set -eux 2025-09-07T13:09:26.9243332Z  2025-09-07T13:09:26.9243578Z if [[ -n "" ]]; then 2025-09-07T13:09:26.9243855Z  source "" 2025-09-07T13:09:26.9244097Z fi 2025-09-07T13:09:26.9244299Z  2025-09-07T13:09:26.9244706Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-09-07T13:09:26.9258328Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:26.9258732Z env: 2025-09-07T13:09:26.9258953Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:26.9259309Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:26.9259782Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:26.9260399Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:26.9260911Z DEVICE_NAME: 2025-09-07T13:09:26.9261131Z DEVICE_TYPE: 2025-09-07T13:09:26.9261358Z ##[endgroup] 2025-09-07T13:09:26.9370048Z + [[ -n '' ]] 2025-09-07T13:09:26.9370845Z + python3 /home/david/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-09-07T13:09:27.8538894Z /home/david/.local/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:276: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:81.) 2025-09-07T13:09:27.8540167Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-09-07T13:09:29.5151764Z ##[group]Run set -eux 2025-09-07T13:09:29.5152051Z set -eux 2025-09-07T13:09:29.5152286Z  2025-09-07T13:09:29.5152544Z # TODO (huydhn): Implement this part 2025-09-07T13:09:29.5152955Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-09-07T13:09:29.5166130Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:29.5166535Z env: 2025-09-07T13:09:29.5166763Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:29.5167106Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:29.5167809Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:29.5168401Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:29.5168912Z DEVICE_NAME: 2025-09-07T13:09:29.5169147Z DEVICE_TYPE: 2025-09-07T13:09:29.5169375Z ##[endgroup] 2025-09-07T13:09:29.5250092Z + echo 'dependencies={}' 2025-09-07T13:09:29.5443774Z ##[group]Run set -eux 2025-09-07T13:09:29.5444080Z set -eux 2025-09-07T13:09:29.5444337Z  2025-09-07T13:09:29.5444548Z if [[ -n "" ]]; then 2025-09-07T13:09:29.5444828Z  source "" 2025-09-07T13:09:29.5445070Z fi 2025-09-07T13:09:29.5445293Z  2025-09-07T13:09:29.5445550Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-09-07T13:09:29.5446004Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-09-07T13:09:29.5446506Z  # We don't want the job to fail if the directory doesn't exist 2025-09-07T13:09:29.5446925Z  exit 0 2025-09-07T13:09:29.5447158Z fi 2025-09-07T13:09:29.5447359Z  2025-09-07T13:09:29.5447602Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-09-07T13:09:29.5448096Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T13:09:29.5448671Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T13:09:29.5449101Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T13:09:29.5449590Z  --runners "${RUNNER_INFO}" \ 2025-09-07T13:09:29.5449951Z  --dependencies "${DEPENDENCIES}" \ 2025-09-07T13:09:29.5450395Z  --dry-run 2025-09-07T13:09:29.5450638Z else 2025-09-07T13:09:29.5451031Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T13:09:29.5451600Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T13:09:29.5452047Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T13:09:29.5452412Z  --runners "${RUNNER_INFO}" \ 2025-09-07T13:09:29.5452753Z  --dependencies "${DEPENDENCIES}" 2025-09-07T13:09:29.5453281Z fi 2025-09-07T13:09:29.5466586Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:29.5466988Z env: 2025-09-07T13:09:29.5467221Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:29.5467553Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:29.5468023Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:29.5468623Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:29.5469144Z DEVICE_NAME: 2025-09-07T13:09:29.5469364Z DEVICE_TYPE: 2025-09-07T13:09:29.5469628Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-09-07T13:09:29.5469950Z DRY_RUN: false 2025-09-07T13:09:29.5471325Z BENCHMARK_METADATA: {"timestamp": 1757250566, "schema_version": "v3", "name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525309334, "run_attempt": 1, "job_id": 49775768449} 2025-09-07T13:09:29.5473295Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 1121, "extra_info": {"hostname": "c3fe6811bb8d"}, "name": "cuda", "type": "NVIDIA A100-SXM4-40GB", "gpu_count": 1, "avail_gpu_mem_in_gb": 39}] 2025-09-07T13:09:29.5474141Z DEPENDENCIES: {} 2025-09-07T13:09:29.5474370Z ##[endgroup] 2025-09-07T13:09:29.5570944Z + [[ -n '' ]] 2025-09-07T13:09:29.5571230Z + [[ ! -d test/test-reports ]] 2025-09-07T13:09:29.5571539Z + [[ false == \t\r\u\e ]] 2025-09-07T13:09:29.5574907Z + python3 /home/david/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757250566, "schema_version": "v3", "name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525309334, "run_attempt": 1, "job_id": 49775768449}' --runners '[{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 1121, "extra_info": {"hostname": "c3fe6811bb8d"}, "name": "cuda", "type": "NVIDIA A100-SXM4-40GB", "gpu_count": 1, "avail_gpu_mem_in_gb": 39}]' --dependencies '{}' 2025-09-07T13:09:29.7053316Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:29.7440578Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role 2025-09-07T13:09:30.0112034Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:30.3350499Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:30.5074684Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:30.7232888Z 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/17525309334/49775768449/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:30.9417204Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:09:31.1490289Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:31.3375903Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:31.5323031Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:31.7079379Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:31.8958727Z 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/17525309334/49775768449/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:32.1389581Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:32.3114010Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:09:32.4724633Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:09:32.6337058Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:32.8342543Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:32.9896830Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:09:33.1728009Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:33.3767080Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:09:33.6372456Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:33.8273065Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_dynamic_torchbench_amp_training_cuda_performance.json 2025-09-07T13:09:33.9891700Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:34.1480874Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:34.3119731Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json 2025-09-07T13:09:34.5166322Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json 2025-09-07T13:09:34.7015373Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:09:34.8639306Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:35.0050056Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:35.2301879Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json 2025-09-07T13:09:35.3936567Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:35.5550227Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_max_autotune_torchbench_amp_training_cuda_performance.json 2025-09-07T13:09:35.7498847Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:09:35.9775825Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:09:36.2325895Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json 2025-09-07T13:09:36.4492095Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:36.6192855Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:36.7832643Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json 2025-09-07T13:09:36.9580474Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json 2025-09-07T13:09:37.0991301Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json 2025-09-07T13:09:37.2643776Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525309334/49775768449/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json 2025-09-07T13:09:37.5198576Z ##[group]Run cat test/**/*_toprint.log || true 2025-09-07T13:09:37.5198984Z cat test/**/*_toprint.log || true 2025-09-07T13:09:37.5211972Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:37.5212372Z env: 2025-09-07T13:09:37.5212598Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:37.5213235Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:37.5213694Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:37.5214306Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:37.5214816Z DEVICE_NAME: 2025-09-07T13:09:37.5215048Z DEVICE_TYPE: 2025-09-07T13:09:37.5215285Z ##[endgroup] 2025-09-07T13:09:37.5362540Z cat: 'test/**/*_toprint.log': No such file or directory 2025-09-07T13:09:37.5492483Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-09-07T13:09:37.5493007Z kill "$MONITOR_SCRIPT_PID" 2025-09-07T13:09:37.5504921Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:37.5505333Z env: 2025-09-07T13:09:37.5505563Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:37.5505908Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:37.5506365Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:37.5506963Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:37.5507472Z DEVICE_NAME: 2025-09-07T13:09:37.5507705Z DEVICE_TYPE: 2025-09-07T13:09:37.5508076Z MONITOR_SCRIPT_PID: 9617 2025-09-07T13:09:37.5508331Z ##[endgroup] 2025-09-07T13:09:37.5800095Z Prepare all required actions 2025-09-07T13:09:37.5800578Z Getting action download info 2025-09-07T13:09:37.9243311Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T13:09:38.7412643Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-09-07T13:09:41.1043624Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-09-07T13:09:41.1044004Z with: 2025-09-07T13:09:41.1044376Z file-suffix: test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T13:09:41.1044836Z s3-bucket: gha-artifacts 2025-09-07T13:09:41.1045106Z env: 2025-09-07T13:09:41.1045321Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:41.1045660Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:41.1046115Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:41.1046773Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:41.1047279Z DEVICE_NAME: 2025-09-07T13:09:41.1047503Z DEVICE_TYPE: 2025-09-07T13:09:41.1047727Z ##[endgroup] 2025-09-07T13:09:41.1206087Z ##[group]Run # Remove any previous test jsons if they exist 2025-09-07T13:09:41.1206574Z # Remove any previous test jsons if they exist 2025-09-07T13:09:41.1206960Z rm -f test-jsons-*.zip 2025-09-07T13:09:41.1207382Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-09-07T13:09:41.1220500Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:41.1220895Z env: 2025-09-07T13:09:41.1221121Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:41.1221462Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:41.1221915Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:41.1222509Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:41.1223028Z DEVICE_NAME: 2025-09-07T13:09:41.1223265Z DEVICE_TYPE: 2025-09-07T13:09:41.1223653Z FILE_SUFFIX: test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T13:09:41.1224110Z ##[endgroup] 2025-09-07T13:09:41.1374338Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.1399296Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.1424388Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.1498295Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.1601150Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.1722261Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.1759431Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.1870291Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.1893284Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.1989638Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.2113511Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.2148290Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2173031Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2198152Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2236447Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2259836Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2284981Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2392736Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.2494673Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.2594509Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.2626267Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2651139Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2674357Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2711365Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2748384Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2773450Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2796554Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2834059Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2859051Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.2894206Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.2930906Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.3066028Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.3179134Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.3297736Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.3333061Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.3356032Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.3393062Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.3430897Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.json (deflated 99%) 2025-09-07T13:09:41.3454268Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.json (deflated 99%) 2025-09-07T13:09:41.3550708Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.json (deflated 99%) 2025-09-07T13:09:41.3625272Z ##[group]Run # Remove any previous test reports if they exist 2025-09-07T13:09:41.3625780Z # Remove any previous test reports if they exist 2025-09-07T13:09:41.3626185Z rm -f test-reports-*.zip 2025-09-07T13:09:41.3626665Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-09-07T13:09:41.3639494Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:41.3639887Z env: 2025-09-07T13:09:41.3640117Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:41.3640461Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:41.3640917Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:41.3641515Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:41.3642040Z DEVICE_NAME: 2025-09-07T13:09:41.3642279Z DEVICE_TYPE: 2025-09-07T13:09:41.3642661Z FILE_SUFFIX: test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T13:09:41.3643103Z ##[endgroup] 2025-09-07T13:09:41.3804599Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T13:09:41.3805642Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:09:41.3806678Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3807932Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T13:09:41.3808977Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3809946Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:09:41.3810934Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance.csv (deflated 50%) 2025-09-07T13:09:41.3811988Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance.csv (deflated 50%) 2025-09-07T13:09:41.3813235Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance.csv (deflated 49%) 2025-09-07T13:09:41.3814300Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3815294Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance.csv (deflated 48%) 2025-09-07T13:09:41.3816200Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance.csv (deflated 48%) 2025-09-07T13:09:41.3817194Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T13:09:41.3818142Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_accuracy.csv (deflated 52%) 2025-09-07T13:09:41.3819132Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T13:09:41.3820188Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:09:41.3821113Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3822214Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 53%) 2025-09-07T13:09:41.3823358Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3824539Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3825760Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T13:09:41.3826834Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 56%) 2025-09-07T13:09:41.3827801Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3828826Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:09:41.3829822Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 64%) 2025-09-07T13:09:41.3830824Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T13:09:41.3831927Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 53%) 2025-09-07T13:09:41.3833072Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 53%) 2025-09-07T13:09:41.3834118Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_performance.csv (deflated 48%) 2025-09-07T13:09:41.3835016Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 54%) 2025-09-07T13:09:41.3835916Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_accuracy.csv (deflated 52%) 2025-09-07T13:09:41.3836804Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 54%) 2025-09-07T13:09:41.3837731Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_performance.csv (deflated 50%) 2025-09-07T13:09:41.3838776Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T13:09:41.3839794Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_accuracy.csv (deflated 53%) 2025-09-07T13:09:41.3840689Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_performance.csv (deflated 48%) 2025-09-07T13:09:41.3841613Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_performance.csv (deflated 51%) 2025-09-07T13:09:41.3842556Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_accuracy.csv (deflated 52%) 2025-09-07T13:09:41.3843479Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_performance.csv (deflated 48%) 2025-09-07T13:09:41.3844492Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T13:09:41.3845593Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T13:09:41.3847493Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T13:09:41.3873045Z ##[group]Run # Remove any previous usage logs if they exist 2025-09-07T13:09:41.3873523Z # Remove any previous usage logs if they exist 2025-09-07T13:09:41.3873891Z rm -f logs-*.zip 2025-09-07T13:09:41.3874249Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true 2025-09-07T13:09:41.3874777Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true 2025-09-07T13:09:41.3886712Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:41.3887106Z env: 2025-09-07T13:09:41.3887320Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:41.3887763Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:41.3888370Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:41.3889051Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:41.3889555Z DEVICE_NAME: 2025-09-07T13:09:41.3889788Z DEVICE_TYPE: 2025-09-07T13:09:41.3890168Z FILE_SUFFIX: test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T13:09:41.3890617Z ##[endgroup] 2025-09-07T13:09:41.4109375Z adding: usage_log.txt (deflated 91%) 2025-09-07T13:09:41.4122967Z 2025-09-07T13:09:41.4123340Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip) 2025-09-07T13:09:41.4266423Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-09-07T13:09:41.4266974Z # Remove any previous debugging artifacts if they exist 2025-09-07T13:09:41.4267398Z rm -f debug-*.zip 2025-09-07T13:09:41.4267708Z if [ -d 'test/debug' ]; then 2025-09-07T13:09:41.4268081Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-09-07T13:09:41.4268424Z fi 2025-09-07T13:09:41.4280186Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:41.4280578Z env: 2025-09-07T13:09:41.4280804Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:41.4281151Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:41.4281627Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:41.4282222Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:41.4282745Z DEVICE_NAME: 2025-09-07T13:09:41.4282984Z DEVICE_TYPE: 2025-09-07T13:09:41.4283375Z FILE_SUFFIX: test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449 2025-09-07T13:09:41.4283819Z ##[endgroup] 2025-09-07T13:09:41.4475436Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:09:41.4475769Z with: 2025-09-07T13:09:41.4476000Z s3-bucket: gha-artifacts 2025-09-07T13:09:41.4476335Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:41.4476696Z retention-days: 14 2025-09-07T13:09:41.4476946Z if-no-files-found: warn 2025-09-07T13:09:41.4477222Z path: test-jsons-*.zip 2025-09-07T13:09:41.4477480Z name: artifact 2025-09-07T13:09:41.4477712Z region: us-east-1 2025-09-07T13:09:41.4477928Z env: 2025-09-07T13:09:41.4478143Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:41.4478480Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:41.4478945Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:41.4479537Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:41.4480052Z DEVICE_NAME: 2025-09-07T13:09:41.4480285Z DEVICE_TYPE: 2025-09-07T13:09:41.4480512Z ##[endgroup] 2025-09-07T13:09:41.7843566Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T13:09:41.7844047Z With the provided path, there will be 1 file uploaded 2025-09-07T13:09:41.7844537Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:41.7852461Z Starting upload of test-jsons-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:09:42.1535566Z Finished upload of test-jsons-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:09:42.1840380Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:09:42.1840732Z with: 2025-09-07T13:09:42.1840959Z s3-bucket: gha-artifacts 2025-09-07T13:09:42.1841292Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:42.1841642Z retention-days: 14 2025-09-07T13:09:42.1841904Z if-no-files-found: error 2025-09-07T13:09:42.1842189Z path: test-reports-*.zip 2025-09-07T13:09:42.1842459Z name: artifact 2025-09-07T13:09:42.1842683Z region: us-east-1 2025-09-07T13:09:42.1842916Z env: 2025-09-07T13:09:42.1843131Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:42.1843470Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:42.1844197Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:42.1844802Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:42.1845404Z DEVICE_NAME: 2025-09-07T13:09:42.1845644Z DEVICE_TYPE: 2025-09-07T13:09:42.1845871Z ##[endgroup] 2025-09-07T13:09:42.5214148Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T13:09:42.5214612Z With the provided path, there will be 1 file uploaded 2025-09-07T13:09:42.5215072Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:42.5223002Z Starting upload of test-reports-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:09:42.7177644Z Finished upload of test-reports-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:09:42.7450841Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:09:42.7451183Z with: 2025-09-07T13:09:42.7451428Z s3-bucket: gha-artifacts 2025-09-07T13:09:42.7451771Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:42.7452132Z retention-days: 14 2025-09-07T13:09:42.7452384Z if-no-files-found: ignore 2025-09-07T13:09:42.7452673Z path: logs-*.zip 2025-09-07T13:09:42.7453188Z name: artifact 2025-09-07T13:09:42.7453427Z region: us-east-1 2025-09-07T13:09:42.7453647Z env: 2025-09-07T13:09:42.7453870Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:42.7454215Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:42.7454684Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:42.7455274Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:42.7455782Z DEVICE_NAME: 2025-09-07T13:09:42.7456009Z DEVICE_TYPE: 2025-09-07T13:09:42.7456234Z ##[endgroup] 2025-09-07T13:09:43.0808432Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T13:09:43.0808901Z With the provided path, there will be 1 file uploaded 2025-09-07T13:09:43.0809412Z Uploading to s3 prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:43.0817553Z Starting upload of logs-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:09:43.2523650Z Finished upload of logs-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:09:43.2743974Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T13:09:43.2744327Z with: 2025-09-07T13:09:43.2744554Z s3-bucket: gha-artifacts 2025-09-07T13:09:43.2744986Z s3-prefix: pytorch/pytorch/17525309334/1/artifact 2025-09-07T13:09:43.2745343Z retention-days: 14 2025-09-07T13:09:43.2745609Z if-no-files-found: ignore 2025-09-07T13:09:43.2745893Z path: debug-*.zip 2025-09-07T13:09:43.2746135Z name: artifact 2025-09-07T13:09:43.2746356Z region: us-east-1 2025-09-07T13:09:43.2746587Z env: 2025-09-07T13:09:43.2746803Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:43.2747145Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:43.2747614Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:43.2748227Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:43.2748744Z DEVICE_NAME: 2025-09-07T13:09:43.2748982Z DEVICE_TYPE: 2025-09-07T13:09:43.2749209Z ##[endgroup] 2025-09-07T13:09:43.6063082Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-09-07T13:09:43.6264536Z ##[group]Run # shellcheck disable=SC2156 2025-09-07T13:09:43.6265018Z # shellcheck disable=SC2156 2025-09-07T13:09:43.6265629Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-09-07T13:09:43.6278641Z shell: /usr/bin/bash -e {0} 2025-09-07T13:09:43.6278937Z env: 2025-09-07T13:09:43.6279162Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:43.6279495Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:43.6279966Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:43.6280704Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:43.6281220Z DEVICE_NAME: 2025-09-07T13:09:43.6281550Z DEVICE_TYPE: 2025-09-07T13:09:43.6281770Z ##[endgroup] 2025-09-07T13:09:44.3529271Z Prepare all required actions 2025-09-07T13:09:44.3529682Z Getting action download info 2025-09-07T13:09:44.4879774Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-09-07T13:09:44.4880155Z with: 2025-09-07T13:09:44.4880373Z job_id: 49775768449 2025-09-07T13:09:44.4880825Z job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T13:09:44.4881362Z workflow_name: inductor-A100-perf-nightly 2025-09-07T13:09:44.4881705Z workflow_run_id: 17525309334 2025-09-07T13:09:44.4881985Z workflow_attempt: 1 2025-09-07T13:09:44.4882229Z env: 2025-09-07T13:09:44.4882430Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:44.4882767Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:44.4883246Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:44.4883838Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:44.4884352Z DEVICE_NAME: 2025-09-07T13:09:44.4884616Z DEVICE_TYPE: 2025-09-07T13:09:44.4884831Z ##[endgroup] 2025-09-07T13:09:44.5118426Z ##[group]Run echo "workflow_id: 17525309334" 2025-09-07T13:09:44.5118791Z echo "workflow_id: 17525309334" 2025-09-07T13:09:44.5119123Z echo "workflow_attempt: 1" 2025-09-07T13:09:44.5119505Z echo "workflow_Name: inductor-A100-perf-nightly" 2025-09-07T13:09:44.5119909Z echo "job_id: 49775768449" 2025-09-07T13:09:44.5120463Z echo "job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)" 2025-09-07T13:09:44.5121034Z echo "artifact_prefix: " 2025-09-07T13:09:44.5121336Z python3 --version 2025-09-07T13:09:44.5134305Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:44.5134696Z env: 2025-09-07T13:09:44.5134924Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:44.5135278Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:44.5135750Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:44.5136342Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:44.5136855Z DEVICE_NAME: 2025-09-07T13:09:44.5137084Z DEVICE_TYPE: 2025-09-07T13:09:44.5137299Z ##[endgroup] 2025-09-07T13:09:44.5229020Z workflow_id: 17525309334 2025-09-07T13:09:44.5229339Z workflow_attempt: 1 2025-09-07T13:09:44.5229616Z workflow_Name: inductor-A100-perf-nightly 2025-09-07T13:09:44.5229948Z job_id: 49775768449 2025-09-07T13:09:44.5230392Z job_name: cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100) 2025-09-07T13:09:44.5230904Z artifact_prefix: 2025-09-07T13:09:44.5243570Z Python 3.10.12 2025-09-07T13:09:44.5398237Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T13:09:44.5398562Z with: 2025-09-07T13:09:44.5398760Z shell: bash 2025-09-07T13:09:44.5398989Z timeout_minutes: 5 2025-09-07T13:09:44.5399247Z max_attempts: 5 2025-09-07T13:09:44.5399506Z retry_wait_seconds: 30 2025-09-07T13:09:44.5400059Z 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 2025-09-07T13:09:44.5400682Z polling_interval_seconds: 1 2025-09-07T13:09:44.5400969Z warning_on_retry: true 2025-09-07T13:09:44.5401234Z continue_on_error: false 2025-09-07T13:09:44.5401484Z env: 2025-09-07T13:09:44.5401699Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:44.5402032Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:44.5402498Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:44.5403096Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:44.5403725Z DEVICE_NAME: 2025-09-07T13:09:44.5403954Z DEVICE_TYPE: 2025-09-07T13:09:44.5404180Z ##[endgroup] 2025-09-07T13:09:44.9279239Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T13:09:45.2324499Z Collecting python-dateutil==2.8.2 2025-09-07T13:09:45.3056556Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-09-07T13:09:45.4797100Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 247.7/247.7 KB 1.4 MB/s eta 0:00:00 2025-09-07T13:09:46.2095387Z Collecting boto3==1.35.42 2025-09-07T13:09:46.2217963Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-09-07T13:09:46.4145627Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.2/139.2 KB 676.9 kB/s eta 0:00:00 2025-09-07T13:09:46.8287692Z Collecting pandas==2.1.3 2025-09-07T13:09:46.8411226Z Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-09-07T13:09:47.5871851Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.3/12.3 MB 17.0 MB/s eta 0:00:00 2025-09-07T13:09:47.6490723Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/david/.local/lib/python3.10/site-packages (0.6.7) 2025-09-07T13:09:47.6509295Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil==2.8.2) (1.16.0) 2025-09-07T13:09:47.6558396Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/david/.local/lib/python3.10/site-packages (from boto3==1.35.42) (0.10.4) 2025-09-07T13:09:47.6563929Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/david/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.0.1) 2025-09-07T13:09:47.6569286Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/david/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.35.99) 2025-09-07T13:09:47.8797448Z Collecting tzdata>=2022.1 2025-09-07T13:09:47.8906002Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-09-07T13:09:47.9835516Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 347.8/347.8 KB 3.7 MB/s eta 0:00:00 2025-09-07T13:09:48.5362974Z Collecting numpy<2,>=1.22.4 2025-09-07T13:09:48.5478607Z Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-09-07T13:09:49.1806751Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 18.6 MB/s eta 0:00:00 2025-09-07T13:09:49.4420916Z Collecting pytz>=2020.1 2025-09-07T13:09:49.4535280Z Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) 2025-09-07T13:09:49.5851782Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 509.2/509.2 KB 3.9 MB/s eta 0:00:00 2025-09-07T13:09:49.5945125Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/david/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-09-07T13:09:49.5953088Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/david/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-09-07T13:09:49.6023312Z 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) 2025-09-07T13:09:49.6162906Z Requirement already satisfied: packaging>=17.0 in /home/david/.local/lib/python3.10/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-09-07T13:09:49.6279346Z Requirement already satisfied: mypy-extensions>=0.3.0 in 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boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 pytz-2025.2 tzdata-2025.2 2025-09-07T13:09:57.6233871Z Command completed after 1 attempt(s). 2025-09-07T13:09:57.6429634Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T13:09:57.6439306Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T13:09:57.6439846Z  --workflow-run-id "17525309334" \ 2025-09-07T13:09:57.6440263Z  --workflow-name "inductor-A100-perf-nightly" \ 2025-09-07T13:09:57.6440673Z  --workflow-run-attempt "1" \ 2025-09-07T13:09:57.6441006Z  --job-id "49775768449" \ 2025-09-07T13:09:57.6441548Z  --job-name "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)" \ 2025-09-07T13:09:57.6442109Z  --local-path "" \ 2025-09-07T13:09:57.6442416Z  --artifact-prefix "" 2025-09-07T13:09:57.6455750Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T13:09:57.6456149Z env: 2025-09-07T13:09:57.6456365Z GIT_DEFAULT_BRANCH: main 2025-09-07T13:09:57.6456707Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T13:09:57.6457174Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5230 2025-09-07T13:09:57.6457771Z DOCKER_CONTAINER_ID: 7a39923717525ac00415e6a8978e22f7c3baef3b0b6f88aefd1b039335dbb7d6 2025-09-07T13:09:57.6458281Z DEVICE_NAME: 2025-09-07T13:09:57.6458500Z DEVICE_TYPE: 2025-09-07T13:09:57.6458729Z ##[endgroup] 2025-09-07T13:10:00.5114446Z repo: pytorch/pytorch 2025-09-07T13:10:00.5114839Z Search for test log in s3 bucket: ossci-utilization 2025-09-07T13:10:00.5115424Z Downloading logs-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:10:00.5116217Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf-1-6-linux.aws.a100_49775768449.zip 2025-09-07T13:10:00.5116861Z Converted Log Model: UtilizationMetadata: 2025-09-07T13:10:00.5118414Z UtilizationMetadata(level='metadata', workflow_id='17525309334', job_id='49775768449', workflow_name='inductor-A100-perf-nightly', job_name='cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757235253, gpu_count=1, cpu_count=96, gpu_type='pynvml', error=None) 2025-09-07T13:10:00.5120034Z [Db Segments] detected pytest cmd: 4, generated segments: 4 2025-09-07T13:10:00.5120431Z [db model] Peek db timeseries 2025-09-07T13:10:00.5120712Z :{ 2025-09-07T13:10:00.5120924Z "created_at": 1757250599, 2025-09-07T13:10:00.5121212Z "type": "utilization", 2025-09-07T13:10:00.5121465Z "tags": [ 2025-09-07T13:10:00.5121932Z "record" 2025-09-07T13:10:00.5122160Z ], 2025-09-07T13:10:00.5122381Z "time_stamp": 1757235253, 2025-09-07T13:10:00.5122659Z "repo": "pytorch/pytorch", 2025-09-07T13:10:00.5122956Z "workflow_id": 17525309334, 2025-09-07T13:10:00.5123243Z "run_attempt": 1, 2025-09-07T13:10:00.5123498Z "job_id": 49775768449, 2025-09-07T13:10:00.5123801Z "workflow_name": "inductor-A100-perf-nightly", 2025-09-07T13:10:00.5124371Z "job_name": "cuda12.8-py3.10-gcc9-sm80 / test (inductor_torchbench_perf, 1, 6, linux.aws.a100)", 2025-09-07T13:10:00.5124889Z "json_data": "{}" 2025-09-07T13:10:00.5125130Z } 2025-09-07T13:10:00.5125632Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525309334/1/49775768449/metadata 2025-09-07T13:10:00.5126592Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525309334/1/49775768449/metadata 2025-09-07T13:10:00.5127591Z Writing 1018 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525309334/1/49775768449/time_series 2025-09-07T13:10:00.5128609Z Done! 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http.https://github.com/.extraheader 2025-09-07T13:10:01.3164093Z Entering 'third_party/composable_kernel' 2025-09-07T13:10:01.3188691Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3291157Z Entering 'third_party/cpp-httplib' 2025-09-07T13:10:01.3315255Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3371776Z Entering 'third_party/cpuinfo' 2025-09-07T13:10:01.3395942Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3492694Z Entering 'third_party/cudnn_frontend' 2025-09-07T13:10:01.3517065Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3598880Z Entering 'third_party/cutlass' 2025-09-07T13:10:01.3624492Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3723436Z Entering 'third_party/fbgemm' 2025-09-07T13:10:01.3748910Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3835572Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T13:10:01.3859903Z http.https://github.com/.extraheader 2025-09-07T13:10:01.3901606Z Entering 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'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T13:10:01.4730691Z http.https://github.com/.extraheader 2025-09-07T13:10:01.4833487Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T13:10:01.4857246Z http.https://github.com/.extraheader 2025-09-07T13:10:01.4901641Z Entering 'third_party/flatbuffers' 2025-09-07T13:10:01.4926820Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5008686Z Entering 'third_party/fmt' 2025-09-07T13:10:01.5033562Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5127382Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T13:10:01.5153403Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5311220Z Entering 'third_party/gloo' 2025-09-07T13:10:01.5337525Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5425373Z Entering 'third_party/googletest' 2025-09-07T13:10:01.5450746Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5505506Z Entering 'third_party/ideep' 2025-09-07T13:10:01.5531194Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5630690Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T13:10:01.5654713Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5755034Z Entering 'third_party/ittapi' 2025-09-07T13:10:01.5781353Z http.https://github.com/.extraheader 2025-09-07T13:10:01.5920033Z Entering 'third_party/kineto' 2025-09-07T13:10:01.5947104Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6043195Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T13:10:01.6067964Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6126129Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T13:10:01.6150555Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6251400Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T13:10:01.6276558Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6347924Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T13:10:01.6372918Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6428049Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T13:10:01.6451917Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6548077Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T13:10:01.6572265Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6653735Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T13:10:01.6677102Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6762046Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T13:10:01.6787184Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6880132Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T13:10:01.6904585Z http.https://github.com/.extraheader 2025-09-07T13:10:01.6977743Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T13:10:01.7002005Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8165002Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T13:10:01.8191804Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8347496Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T13:10:01.8373719Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8444928Z Entering 'third_party/kleidiai' 2025-09-07T13:10:01.8471874Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8557193Z Entering 'third_party/mimalloc' 2025-09-07T13:10:01.8583540Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8673858Z Entering 'third_party/nlohmann' 2025-09-07T13:10:01.8700379Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8771531Z Entering 'third_party/onnx' 2025-09-07T13:10:01.8797493Z http.https://github.com/.extraheader 2025-09-07T13:10:01.8971424Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T13:10:01.8996303Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9077805Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T13:10:01.9104971Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9145006Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T13:10:01.9169025Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9262424Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T13:10:01.9286504Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9381517Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T13:10:01.9405619Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9439720Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T13:10:01.9464208Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9556533Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T13:10:01.9580510Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9675705Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T13:10:01.9700571Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9738237Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T13:10:01.9761729Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9849217Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T13:10:01.9873337Z http.https://github.com/.extraheader 2025-09-07T13:10:01.9965816Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T13:10:01.9989629Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0145252Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T13:10:02.0169387Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0267395Z Entering 'third_party/pocketfft' 2025-09-07T13:10:02.0293506Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0326316Z Entering 'third_party/protobuf' 2025-09-07T13:10:02.0351716Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0457957Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T13:10:02.0481708Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0574737Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T13:10:02.0600126Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0727093Z Entering 'third_party/psimd' 2025-09-07T13:10:02.0753177Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0845180Z Entering 'third_party/pthreadpool' 2025-09-07T13:10:02.0870574Z http.https://github.com/.extraheader 2025-09-07T13:10:02.0941206Z Entering 'third_party/pybind11' 2025-09-07T13:10:02.0966257Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1058529Z Entering 'third_party/python-peachpy' 2025-09-07T13:10:02.1083412Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1178915Z Entering 'third_party/sleef' 2025-09-07T13:10:02.1203385Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1237009Z Entering 'third_party/tensorpipe' 2025-09-07T13:10:02.1262655Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1359095Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T13:10:02.1382928Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1456779Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T13:10:02.1480206Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1520156Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T13:10:02.1544109Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1639557Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T13:10:02.1663420Z http.https://github.com/.extraheader 2025-09-07T13:10:02.1763282Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T13:10:02.1786707Z http.https://github.com/.extraheader 2025-09-07T13:10:02.2148503Z Post job cleanup. 2025-09-07T13:10:02.3113216Z [command]/usr/bin/git version 2025-09-07T13:10:02.3148408Z git version 2.51.0 2025-09-07T13:10:02.3187408Z Temporarily overriding HOME='/home/david/_work/_temp/10ff617e-d19d-4ca0-b07c-dfdeba6ed42a' before making global git config changes 2025-09-07T13:10:02.3188316Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T13:10:02.3192157Z [command]/usr/bin/git config --global --add safe.directory /home/david/_work/pytorch/pytorch 2025-09-07T13:10:02.3289504Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T13:10:02.3321522Z [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' || :" 2025-09-07T13:10:02.3552766Z Entering 'android/libs/fbjni' 2025-09-07T13:10:02.3594924Z Entering 'third_party/FP16' 2025-09-07T13:10:02.3637949Z Entering 'third_party/FXdiv' 2025-09-07T13:10:02.3680525Z Entering 'third_party/NNPACK' 2025-09-07T13:10:02.3722951Z Entering 'third_party/NVTX' 2025-09-07T13:10:02.3765721Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T13:10:02.3807882Z Entering 'third_party/XNNPACK' 2025-09-07T13:10:02.3866867Z Entering 'third_party/aiter' 2025-09-07T13:10:02.3910751Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T13:10:02.3961113Z Entering 'third_party/benchmark' 2025-09-07T13:10:02.4003669Z Entering 'third_party/composable_kernel' 2025-09-07T13:10:02.4056183Z Entering 'third_party/cpp-httplib' 2025-09-07T13:10:02.4098971Z Entering 'third_party/cpuinfo' 2025-09-07T13:10:02.4142342Z Entering 'third_party/cudnn_frontend' 2025-09-07T13:10:02.4185020Z Entering 'third_party/cutlass' 2025-09-07T13:10:02.4238137Z Entering 'third_party/fbgemm' 2025-09-07T13:10:02.4283514Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T13:10:02.4323937Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T13:10:02.4372213Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T13:10:02.4413018Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T13:10:02.4463478Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T13:10:02.4503879Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T13:10:02.4543931Z Entering 'third_party/fbgemm/external/json' 2025-09-07T13:10:02.4587169Z Entering 'third_party/flash-attention' 2025-09-07T13:10:02.4630362Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T13:10:02.4677331Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T13:10:02.4727827Z Entering 'third_party/flatbuffers' 2025-09-07T13:10:02.4773177Z Entering 'third_party/fmt' 2025-09-07T13:10:02.4816229Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T13:10:02.4859243Z Entering 'third_party/gloo' 2025-09-07T13:10:02.4901445Z Entering 'third_party/googletest' 2025-09-07T13:10:02.4944187Z Entering 'third_party/ideep' 2025-09-07T13:10:02.4986267Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T13:10:02.5034839Z Entering 'third_party/ittapi' 2025-09-07T13:10:02.5077181Z Entering 'third_party/kineto' 2025-09-07T13:10:02.5120165Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T13:10:02.5160348Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T13:10:02.5203048Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T13:10:02.5243344Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T13:10:02.5283533Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T13:10:02.5322890Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T13:10:02.5365422Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T13:10:02.5406125Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T13:10:02.5446489Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T13:10:02.5488175Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T13:10:02.5530395Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T13:10:02.5570932Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T13:10:02.5613635Z Entering 'third_party/kleidiai' 2025-09-07T13:10:02.5655099Z Entering 'third_party/mimalloc' 2025-09-07T13:10:02.5697610Z Entering 'third_party/nlohmann' 2025-09-07T13:10:02.5742281Z Entering 'third_party/onnx' 2025-09-07T13:10:02.5803054Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T13:10:02.5847937Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T13:10:02.5891756Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T13:10:02.5931438Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T13:10:02.5970622Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T13:10:02.6010268Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T13:10:02.6051922Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T13:10:02.6091799Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T13:10:02.6131386Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T13:10:02.6170657Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T13:10:02.6212124Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T13:10:02.6254259Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T13:10:02.6315753Z Entering 'third_party/pocketfft' 2025-09-07T13:10:02.6358348Z Entering 'third_party/protobuf' 2025-09-07T13:10:02.6403828Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T13:10:02.6444497Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T13:10:02.6486832Z Entering 'third_party/psimd' 2025-09-07T13:10:02.6528717Z Entering 'third_party/pthreadpool' 2025-09-07T13:10:02.6570930Z Entering 'third_party/pybind11' 2025-09-07T13:10:02.6613454Z Entering 'third_party/python-peachpy' 2025-09-07T13:10:02.6654839Z Entering 'third_party/sleef' 2025-09-07T13:10:02.6697210Z Entering 'third_party/tensorpipe' 2025-09-07T13:10:02.6740008Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T13:10:02.6779172Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T13:10:02.6819880Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T13:10:02.6859704Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T13:10:02.6899355Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T13:10:02.6960847Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T13:10:02.6991119Z [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' || :" 2025-09-07T13:10:02.7216217Z Entering 'android/libs/fbjni' 2025-09-07T13:10:02.7257854Z Entering 'third_party/FP16' 2025-09-07T13:10:02.7300202Z Entering 'third_party/FXdiv' 2025-09-07T13:10:02.7342034Z Entering 'third_party/NNPACK' 2025-09-07T13:10:02.7384061Z Entering 'third_party/NVTX' 2025-09-07T13:10:02.7426765Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T13:10:02.7468570Z Entering 'third_party/XNNPACK' 2025-09-07T13:10:02.7527117Z Entering 'third_party/aiter' 2025-09-07T13:10:02.7569745Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T13:10:02.7619555Z Entering 'third_party/benchmark' 2025-09-07T13:10:02.7662060Z Entering 'third_party/composable_kernel' 2025-09-07T13:10:02.7714398Z Entering 'third_party/cpp-httplib' 2025-09-07T13:10:02.7755946Z Entering 'third_party/cpuinfo' 2025-09-07T13:10:02.7800657Z Entering 'third_party/cudnn_frontend' 2025-09-07T13:10:02.7843248Z Entering 'third_party/cutlass' 2025-09-07T13:10:02.7895130Z Entering 'third_party/fbgemm' 2025-09-07T13:10:02.7939832Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T13:10:02.7981141Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T13:10:02.8030856Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T13:10:02.8071974Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T13:10:02.8124014Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T13:10:02.8164730Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T13:10:02.8205674Z 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